An experimentally validated genome-scale metabolic reconstruction of Klebsiella pneumoniae MGH 78578, iYL1228

Klebsiella pneumoniae is a Gram-negative bacterium of the family Enterobacteriaceae that possesses diverse metabolic capabilities: many strains are leading causes of hospital-acquired infections that are often refractory to multiple antibiotics, yet other strains are metabolically engineered and used for production of commercially valuable chemicals. To study its metabolism, we constructed a genome-scale metabolic model (iYL1228) for strain MGH 78578, experimentally determined its biomass composition, experimentally determined its ability to grow on a broad range of carbon, nitrogen, phosphorus and sulfur sources, and assessed the ability of the model to accurately simulate growth versus no growth on these substrates. The model contains 1,228 genes encoding 1,188 enzymes that catalyze 1,970 reactions and accurately simulates growth on 84% of the substrates tested. Furthermore, quantitative comparison of growth rates between the model and experimental data for nine of the substrates also showed good agreement. The genome-scale metabolic reconstruction for K. pneumoniae presented here thus provides an experimentally validated in silico platform for further studies of this important industrial and biomedical organism.     

Identification of novel mimicry epitopes for cardiac myosin heavy chain-α that induce autoimmune myocarditis in A/J mice

Myocarditis is one cause of sudden cardiac death in young adolescents, and individuals affected with myocarditis can develop dilated cardiomyopathy, a frequent reason for heart transplantation. Exposure to environmental microbes has been suspected in the initiation of heart autoimmunity, but the direct causal link is lacking. We report here identification of novel mimicry epitopes that bear sequences similar to those in cardiac myosin heavy chain (MYHC)-α 334–352. These epitopes represent Bacillus spp., Magnetospirillum gryphiswaldense, Cryptococcus neoformans and Zea mays. The mimicry peptides induced varying degrees of myocarditis in A/J mice reminiscent of the disease induced with MYHC-α 334–352. We demonstrate that the mimics induce cross-reactive T cell responses for MYHC-α 334–352 as verified by MHC class II IA^k/tetramer staining and Th-1 and Th-17 cytokines similar to those of MYHC-α 334–352. The data suggest that exposure to environmental microbes which are otherwise innocuous can predispose to heart autoimmunity by molecular mimicry.     

ARE GREENBEARDS INTRAGENOMIC OUTLAWS?

Greenbeard genes identify copies of themselves in other individuals and cause their bearer to behave nepotistically toward those individuals. Hence, they can be favored by kin selection, irrespective of the degree of genealogical relationship between social partners. Although greenbeards were initially developed as a thought experiment, a number of recent discoveries of greenbeard alleles in real populations have led to a resurgence of interest in their evolutionary dynamics and consequences. One issue over which there has been disagreement is whether greenbeards lead to intragenomic conflict. Here, to clarify the "outlaw" status of greenbeards, we develop population genetic models that formally examine selection of greenbeard phenotypes under the control of different loci. We find that, in many cases, greenbeards are not outlaws because selection for or against the greenbeard phenotype is the same across all loci. In contrast, when social interactions are between genealogical kin, we find that greenbeards can be outlaws because different genes can be selected in different directions. Hence, the outlaw status of greenbeard genes crucially depends upon the particular biological details. We also clarify whether greenbeards are favored due to direct or indirect fitness effects and address the relationship of the greenbeard effect to sexual antagonism and reciprocity.     

Stochasticity in reproductive opportunity and the evolution of egg limitation in insects

Is reproduction by adult female insects limited by the finite time available to locate hosts (time limitation) or by the finite supply of eggs (egg limitation)? An influential model predicted that stochasticity in reproductive opportunity favors elevated fecundity, rendering egg limitation sufficiently rare that its importance would be greatly diminished. Here, I use models to explore how stochasticity shapes fecundity, the likelihood of egg limitation, and the ecological importance of egg limitation. The models make three predictions. First, whereas spatially stochastic environments favor increased fecundity, temporally stochastic environments favor increases, decreases, or intermediate maxima in fecundity, depending on egg costs. Second, even when spatially or temporally stochastic environments favor life histories with less‐frequent egg limitation, stochasticity still increases the proportion of all eggs laid in the population that is laid by females destined to become egg limited. This counterintuitive result is explained by noting that stochasticity concentrates reproduction in the hands of a few females that are likely to become egg limited. Third, spatially or temporally stochastic environments amplify the constraints imposed by time and eggs on total reproduction by the population. I conclude that both egg and time constraints are fundamental in shaping insect reproductive behavior and population dynamics in stochastic environments.     

Effects of founding genetic variation on adaptation to a novel resource

Population genetic theory predicts that adaptation in novel environments is enhanced by genetic variation for fitness. However, theory also predicts that under strong selection, demographic stochasticity can drive populations to extinction before they can adapt. We exposed wheat-adapted populations of the flour beetle (Tribolium castaneum) to a novel suboptimal corn resource, to test the effects of founding genetic variation on population decline and subsequent extinction or adaptation. As previously reported, genetically diverse populations were less likely to go extinct. Here, we show that among surviving populations, genetically diverse groups recovered faster after the initial population decline. Within two years, surviving populations significantly increased their fitness on corn via increased fecundity, increased egg survival, faster larval development, and higher rate of egg cannibalism. However, founding genetic variation only enhanced the increase in fecundity, despite existing genetic variation-and apparent lack of trade-offs-for egg survival and larval development time. Thus, during adaptation to novel habitats the positive impact of genetic variation may be restricted to only a few traits, although change in many life-history traits may be necessary to avoid extinction. Despite severe initial maladaptation and low population size, genetic diversity can thus overcome the predicted high extinction risk in new habitats.     

Castor phospholipid:diacylglycerol acyltransferase facilitates efficient metabolism of hydroxy fatty acids in transgenic Arabidopsis

Producing unusual fatty acids (FAs) in crop plants has been a long-standing goal of green chemistry. However, expression of the enzymes that catalyze the primary synthesis of these unusual FAs in transgenic plants typically results in low levels of the desired FA. For example, seed-specific expression of castor (Ricinus communis) fatty acid hydroxylase (RcFAH) in Arabidopsis (Arabidopsis thaliana) resulted in only 17% hydroxy fatty acids (HFAs) in the seed oil. In order to increase HFA levels, we investigated castor phospholipid:diacylglycerol acyltransferase (PDAT). We cloned cDNAs encoding three putative PDAT enzymes from a castor seed cDNA library and coexpressed them with RcFAH12. One isoform, RcPDAT1A, increased HFA levels to 27%. Analysis of HFA-triacylglycerol molecular species and regiochemistry, along with analysis of the HFA content of phosphatidylcholine, indicates that RcPDAT1A functions as a PDAT in vivo. Expression of RcFAH12 alone leads to a significant decrease in FA content of seeds. Coexpression of RcPDAT1A and RcDGAT2 (for diacylglycerol acyltransferase 2) with RcFAH12 restored FA levels to nearly wild-type levels, and this was accompanied by a major increase in the mass of HFAs accumulating in the seeds. We show the usefulness of RcPDAT1A for engineering plants with high levels of HFAs and alleviating bottlenecks due to the production of unusual FAs in transgenic oilseeds.     

Evolutionary ecology of plant-microbe interactions: soil microbial structure alters selection on plant traits

? Below-ground microbial communities influence plant diversity, plant productivity, and plant community composition. Given these strong ecological effects, are interactions with below-ground microbes also important for understanding natural selection on plant traits? ? Here, we manipulated below-ground microbial communities and the soil moisture environment on replicated populations of Brassica rapa to examine how microbial community structure influences selection on plant traits and mediates plant responses to abiotic environmental stress. ? In soils with experimentally simplified microbial communities, plants were smaller, had reduced chlorophyll content, produced fewer flowers, and were less fecund when compared with plant populations grown in association with more complex soil microbial communities. Selection on plant growth and phenological traits also was stronger when plants were grown in simplified, less diverse soil microbial communities, and these effects typically were consistent across soil moisture treatments. ? Our results suggest that microbial community structure affects patterns of natural selection on plant traits. Thus, the below-ground microbial community can influence evolutionary processes, just as recent studies have demonstrated that microbial diversity can influence plant community and ecosystem processes.     

Proteome analysis of leaves of the desiccation-tolerant grass, Sporobolus stapfianus, in response to dehydration

Drought and its affects on agricultural production is a serious issue facing global efforts to increase food supplies and ensure food security for the growing world population. Understanding how plants respond to dehydration is an important prerequisite for developing strategies for crop improvement in drought tolerance. This has proved to be a difficult task as all of the current research plant models do not tolerate cellular dehydration well and, like all crops, they succumb to the effects of a relatively small water deficit of −4 MPa or less. For these reasons many researchers have started to investigate the usefulness of resurrection plants, plants that can survive extremes of dehydration to the point of desiccation, to provide answers as to how plants tolerate water loss. We have chosen to investigate the leaf proteome response of the desiccation-tolerant grass Sporobolus stapfianus Gandoger to dehydration to a water content that encompasses the initiation of the cellular protection response evident in these plants. We used a combination of two-dimensional Difference Gel Electrophoresis (2D-DIGE) and liquid chromatography-tandem-mass spectrometry to compare the proteomes of young leaves from hydrated plants to those dehydrated to approximately 30% relative water content. High-resolution 2D-DIGE revealed 96 significantly different proteins and 82 of these spots yielded high-quality protein assignments by tandem-mass spectrometry. Inferences from the bioinformatic annotations of these proteins revealed the possible involvement of protein kinase-based signaling cascades and brassinosteroid involvement in the regulation of the cellular protection response. Enzymes of glycolysis, both cytoplasmic and plastidic, as well as five enzymes of the Calvin cycle increased in abundance. However, the RuBisCO large subunit and associated proteins were reduced, indicating a loss of carbon fixation but a continued need to supply the necessary carbon skeletons for the constituents involved in cell protection. Changes in abundance of several proteins that appear to have a function in chromatin structure and function indicate that these structures undergo significant changes as a result of dehydration. These observations give a unique “snap-shot” of the proteome of S. stapfianus at a critical point in the passage towards desiccation.     

Validation of heavy-water stable isotope probing for the characterization of rapidly responding soil bacteria

Rapid responses of bacteria to sudden changes in their environment can have important implications for the structure and function of microbial communities. In this study, we used heavy-water stable isotope probing (H2(18)O-SIP) to identify bacteria that respond to soil rewetting. First, we conducted experiments to address uncertainties regarding the H2(18)O-SIP method. Using liquid chromatography-mass spectroscopy (LC-MS), we determined that oxygen from H2(18)O was incorporated into all structural components of DNA. Although this incorporation was uneven, we could effectively separate 18O-labeled and unlabeled DNAs derived from laboratory cultures and environmental samples that were incubated with H2(18)O. We found no evidence for ex vivo exchange of oxygen atoms between DNA and extracellular H2O, suggesting that 18O incorporation into DNA is relatively stable. Furthermore, the rate of 18O incorporation into bacterial DNA was high (within 48 to 72 h), coinciding with pulses of CO2 generated from soil rewetting. Second, we examined shifts in the bacterial composition of grassland soils following rewetting, using H2(18)O-SIP and bar-coded pyrosequencing of 16S rRNA genes. For some groups of soil bacteria, we observed coherent responses at a relatively course taxonomic resolution. Following rewetting, the relative recovery of Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria increased, while the relative recovery of Chloroflexi and Deltaproteobacteria decreased. Together, our results suggest that H2(18)O-SIP is effective at identifying metabolically active bacteria that influence soil carbon dynamics. Our results contribute to the ecological classification of soil bacteria while providing insight into some of the functional traits that influence the structure and function of microbial communities under dynamic soil moisture regimes.