An Ab Initio Description of the Mott Metal-Insulator Transition of M2_{2} Vanadium Dioxide

Using an \textit{ab initio} approach based on the GW approximation which includes strong local \textbf{k}-space correlations, the Metal-Insulator Transition of M$_2$ vanadium dioxide is broken down into its component parts and investigated. Similarly to the M$_{1}$ structure, the Peierls pairing of the M$_{2}$ structure results in bonding-antibonding splitting which stabilizes states in which the majority of the charge density resides on the Peierls chain. This is insufficient to drop all of the bonding states into the lower Hubbard band however. An antiferroelectric distortion on the neighboring vanadium chain is required to reduce the repulsion felt by the Peierls bonding states by increasing the distances between the vanadium and apical oxygen atoms, lowering the potential overlap thus reducing the charge density accumulation and thereby the electronic repulsion. The antibonding states are simultaneously pushed into the upper Hubbard band. The data indicate that sufficiently modified GW calculations are able to describe the interplay of the atomic and electronic structures occurring in Mott metal-insulator transitions.Comment: 10 Pages, 7 Figure

A part of differentially expressed genes/proteins between CL and JU.

<p>We present the major differentially expressed proteins of curiosity in this table. An expanded table is available in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135008#pone.0135008.s004" target="_blank">S3 Table</a>. The fold changes (FCs) were calculated using the formula: FC = Log₂ (JU/CL). “↑” and “↓” indicate higher expression in JU and CL, respectively. “–” indicates no significant difference between the two stages (no variation, n.v.).</p><p>^a: The Student’s <i>t</i>-test was used to compare the mRNA expressions between the two stages and the difference was considered significant when <i>p</i> <0.05.</p><p>A part of differentially expressed genes/proteins between CL and JU.</p

A part of differentially expressed genes/proteins between CL and JU.

<p>We present the major differentially expressed proteins of curiosity in this table. An expanded table is available in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135008#pone.0135008.s004" target="_blank">S3 Table</a>. The fold changes (FCs) were calculated using the formula: FC = Log₂ (JU/CL). “↑” and “↓” indicate higher expression in JU and CL, respectively. “–” indicates no significant difference between the two stages (no variation, n.v.).</p><p>^a: The Student’s <i>t</i>-test was used to compare the mRNA expressions between the two stages and the difference was considered significant when <i>p</i> <0.05.</p><p>A part of differentially expressed genes/proteins between CL and JU.</p

The primers of 30 interested genes and reference genes.

<p>The primers of 30 interested genes and reference genes.</p

Statistics of protein identification.

<p>More details were provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135008#pone.0135008.s002" target="_blank">S1 Table</a>.</p><p>^a: include one hit from the decoy database.</p><p>Statistics of protein identification.</p

Protein identification and GO analysis.

<p>a. A Venn diagram showing the numbers of proteins identified from each sample. The number in the bracket indicates a hit from the decoy database. b. Results of GO analysis (the "biological process" category). More information of GO analysis is provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0135008#pone.0135008.s003" target="_blank">S2 Table</a>.</p

Quantitative analysis between the two developmental stages.

<p>a. The scatter plot distributions of the FCs of the 240 proteins that were detectable in both stages. The Y axis represent FC and the X axis represents the log₂ transformation of total spectra from the four runs. The range of one SD of the mean is indicated by dashed lines. Those proteins fell out of the range are candidate differentially expressed proteins. b. The distributions of the 117 differentially expressed proteins. All proteins have the H-sc of at least ten.</p

A Label-Free Proteomic Analysis on Competent Larvae and Juveniles of the Pacific Oyster <i>Crassostrea gigas</i>

<div><p>Current understandings on the molecular mechanisms underlying bivalve metamorphosis are still fragmentary, and a comprehensive description is required. In this study, using a large-scale label-free proteomic approach, we described and compared the proteomes of competent larvae (CL) and juveniles (JU) of the Pacific oyster, <i>Crassostrea gigas</i>. A total of 788 proteins were identified: 392 in the CL proteome and 636 in the JU proteome. Gene Ontology analysis of the proteome from each sample revealed active metabolic processes in both stages. Further quantitative analyses revealed 117 proteins that were differentially expressed between the two samples. These proteins were divided into eight groups: cytoskeleton and cell adhesion, protein synthesis and degradation, immunity and stress response, development of particular tissues, signal regulation, metabolism and energy supply, transport, and other proteins. A certification experiment using real-time PCR assay confirmed 20 of 30 examined genes exhibited the same trends at the mRNA and protein levels. The differentially expressed proteins may play roles in tissue remodeling, signal transduction, and organ development during and after metamorphosis. Novel roles were proposed for some differentially expressed proteins, such as chymotrypsin. The results of this work provide an overview of metamorphosis and post-metamorphosis development of <i>C</i>. <i>gigas</i> at the protein level. Future studies on the functions of the differentially expressed proteins will help to obtain a more in-depth understanding of bivalve metamorphosis.</p></div

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production