Characterization of mutant growth in mono-culture.

<p>(A and B): Un-evolved K and L strains were grown in mono-culture in glucose minimal medium supplemented with 10 mg/L lysine or leucine, respectively. Concentrations of strain K (blue circles), strain L (red diamonds), leucine (orange triangles), lysine (green squares), and glucose (black x) in mono-cultures of strains K and L are shown. (C and D): Survival of strains K (panel C) and L (panel D), in mono-culture in glucose minimal medium without amino acid supplementation. The error bars represent standard deviations across three replicate measurements.</p

Adaptive evolution of the co-culture.

<p>Three parallel co-cultures were performed, represented as a purple solid line (co-culture 4), a green short dashed line (co-culture 5), and a black dotted line (co-culture 6). (A) Growth rates were calculated based on the starting and ending OD values for each passage. (B) Genomic DNA was extracted from frozen samples of the co-culture taken at the end of each passage (OD≈0.2). Relative populations of K and L were estimated using qPCR and used to calculate the ratio of K to L. The error bars represent standard deviations calculated using the method described in <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108297#pone.0108297.s002" target="_blank">File S2</a></b>.</p

Computational model predictions of co-culture composition and growth rates.

<p>The model was constrained using either amino acid uptake (panels A and C) or release rates (panels B and D). Panels A and B display the predicted K:L ratio at a co-culture OD≈0.2. The color map indicates the value of K:L ratio. Panels C and D show the predicted average growth rate of co-culture, indicated by the color map. The evolutionary trajectory of co-culture 4 is shown on panels A through D, where the open circles indicate passages 1,4,7,10,12,15,19 and 21. The estimated uptake or release rates for evolved K^ev and L^ev strains in each passage were then used to constrain the model. Panel E compares the model predicted K:L ratio and average growth rate of the co-culture near OD600≈0.2 to the estimated experimental values. Blue diamonds and red triangles denote the predictions when the model was constrained by the estimated uptake rates for co-culture 4 and 6, respectively. Green squares and purple circles denote the predictions when the model was constrained by the estimated release rates for the two co-cultures for co-culture 4 and 6, respectively.</p

Mutant phenotypes during growth in mono-culture.

<p>*The amino acid requirements represent the amount of leucine or lysine required for production of 1 gDW of cells.</p>‡<p>The uptake rates are estimated as the product of the growth rate and amino acid requirements.</p><p>Mutant phenotypes during growth in mono-culture.</p

Mono-culture of K^ev and L^ev.

<p>Three randomly selected colonies of K^ev (or L^ev) from passage 19 of co-culture 4 and passage 18 of co-culture 6 were inoculated in glucose minimal medium with various amounts of lysine (for K^ev strains, panel A) or leucine (for L^ev strains, panel B). Each colony was tested in three replicate mono-cultures. The growth rates were calculated for the evolved and un-evolved parental strains (control). The error bars represent the standard deviations across biological replicates.</p

Comparisons between un-evolved co-cultures L+K and hybrid co-cultures containing L+K^ev or L^ev+K.

<p>Cells from 10 colonies of K^ev (or L^ev) at each selected passage were grown individually in co-culture with the un-evolved partner strain (L or K). The growth rate and change in OD600 for each hybrid co-culture was normalized to the growth rate and change in OD600 of the un-evolved co-culture grown on the same microplate. The resulting growth rate ratios and change in OD600 ratios are shown as blue diamonds (L+K^ev) and red squares (L^ev+K), respectively, in panels A and B (isolates from co-culture 4) and panels D and E (isolates from co-culture 6). The error bars indicate the standard deviations based on 10 separate hybrid co-cultures each with four replicates (n = 40). The dashed lines indicate the behavior of the un-evolved co-culture (L+K). Panels C and F shows the K:L ratio in L+K^ev and L^ev+K in hybrid co-cultures and the un-evolved co-culture. The hybrid co-cultures contained evolved isolates from co-culture 4 (panel C) or co-culture 6 (panel F). The error bars indicate the standard deviations based on hybrid co-cultures using three different isolates and three measurements for each passage (n = 9), see <b><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108297#pone.0108297.s002" target="_blank">File S2</a></b> for details. The shaded bands in C and F show the mean ± the standard deviation for the K:L ratio in the un-evolved co-culture at an OD600 of 0.2 when grown in 96 well plates (1.62±0.14).</p

Fabrication of Novel Magnetic Nanoparticles of Multifunctionality for Water Decontamination

Efficient and powerful water purifiers are in increasing need because we are facing a more and more serious problem of water pollution. Here, we demonstrate the design of versatile magnetic nanoadsorbents (M-QAC) that exhibit excellent disinfection and adsorption performances at the same time. The M-QAC is constructed by a Fe₃O₄ core surrounded by a polyethylenimine-derived corona. When dispersed in water, the M-QAC particles are able to interact simultaneously with multiple contaminants, including pathogens and heavy metallic cations and anions, in minutes. Subsequently, the M-QACs along with those contaminants can be easily removed and recollected by using a magnet. Meanwhile, the mechanisms of disinfection are investigated by using TEM and SEM, and the adsorption mechanisms are analyzed by XPS. In a practical application, M-QACs are applied to polluted river water 8000-fold greater in mass, producing clean water with the concentrations of all major pollutants below the drinking water standard of China. The adsorption ability of M-QAC could be regenerated for continuous use in a facile manner. With more virtues, such as low-cost fabrication and easy scaling up, the M-QAC have been shown to be a very promising multifunctional water purifier with rational design and to have great potential for real water purification applications

An image reconstruction algorithm for 3D electrical impedance mammography

The Sussex MK4 electrical impedance mammography (EIM) system is especially designed for 3D breast screening. It aims to diagnose breast cancer at an early stage when it is most treatable. Planar electrodes are employed in this system. The challenge with planar electrodes is the inaccuracy and poor sensitivity in the vertical direction for 3D imaging. An enhanced image reconstruction algorithm using a duo-mesh method is proposed to improve the vertical accuracy and sensitivity. The novel part of the enhanced image reconstruction algorithm is the correction term. To evaluate the new algorithm, an image processing based error analysis method is presented, which not only can precisely assess the error of the reconstructed image but also locate the center and outline the shape of the object of interests. Although the enhanced image reconstruction algorithm and the image processing based error analysis method are designed for the Sussex MK4 system, they are applicable to all electrical impedance tomography (EIT) systems, regardless of the hardware design. To validate the enhanced algorithm, performance results from simulations, phantoms and patients are presented

Responses of ecosystem water use efficiency to spring snow and summer water addition with or without nitrogen addition in a temperate steppe - Fig 5

<p>Relationships of water use efficiency (WUEnep and WUEgep, μmol mmol^-1) with dynamics of soil moisture (SM, V/V, %) (A and B) in plots with N addition (solid symbols) and without N addition (hollow symbols) across three growing seasons.</p

Responses of ecosystem water use efficiency to spring snow and summer water addition with or without nitrogen addition in a temperate steppe

<div><p>Water use efficiency (WUE) is an important indicator of ecosystem functioning but how ecosystem WUE responds to climate change including precipitation and nitrogen (N) deposition increases is still unknown. To investigate such responses, an experiment with a randomized block design with water (spring snowfall or summer water addition) and nitrogen addition was conducted in a temperate steppe of northern China. We investigated net ecosystem CO₂ production (NEP), gross ecosystem production (GEP) and evapotranspiration (ET) to calculate ecosystem WUE (WUEnep = NEP/ET or WUEgep = GEP/ET) under spring snow and summer water addition with or without N addition from 2011 to 2013. The results showed that spring snow addition only had significant effect on ecosystem WUE in 2013 and summer water addition showed positive effect on ecosystem WUE in 2011 and 2013, as their effects on NEP and GEP is stronger than ET. N addition increased ecosystem WUE in 2012 and 2013 both in spring snow addition and summer water addition for its increasing effects on NEP and GEP but no effect on ET. Summer water addition had less but N addition had greater increasing effects on ecosystem WUE as natural precipitation increase indicating that natural precipitation regulates ecosystem WUE responses to water and N addition. Moreover, WUE was tightly related with atmospheric vapor-pressure deficit (VPD), photosynthetic active radiation (PAR), precipitation and soil moisture indicating the regulation of climate drivers on ecosystem WUE. In addition, it also was affected by aboveground net primary production (ANPP). The study suggests that ecosystem WUE responses to water and N addition is determined by the change in carbon process rather than that in water process, which are regulated by climate change in the temperate steppe of northern China.</p></div