Lipase activity assay with purified ROL.

<p>(A) Measurement of the lipase activities of mROL^WT and mROL^imp using <i>p</i>-nitrophenyl esters with various acyl chain lengths (C2–C16) as substrates. The resultant <i>p</i>-nitrophenol was quantified to estimate the lipase activities. (B) Relative lipase activities normalized with the values obtained for mROL^WT. The values are presented as mean ± standard error of the mean (SEM) based on at least three independent measurements. (C) Competitive lipase activity assay with purified mROL^WT and mROL^imp. Lipase activities were determined in the presence of the peptidase substrate, Suc-Ile-Ile-Trp-MCA, dissolved in dimethyl sulfoxide (DMSO). The <i>P</i>-values were determined using the Student’s <i>t</i>-test. * <i>P</i> < 0.05.</p

Activity assay using yeast cell surface engineering.

<p>(A) Peptidase activity assay of mROL^WT, mROL^imp, and mROL^imp2 displayed on the yeast cell surface. (B) Lipase activity assay of mROL^WT, mROL^imp, and mROL^imp2 displayed on the yeast cell surface. The resultant <i>p</i>-nitrophenol was quantified to estimate the lipase activities. The peptidase and lipase activities were corrected by the number of displayed enzymes (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124545#pone.0124545.s003" target="_blank">S3 Fig</a>). The values are presented as mean ± SEM based on three independent measurements. The <i>P</i>-values were determined using one-way analysis of variance followed by Tukey’s test for multiple comparisons. ** <i>P</i> < 0.01.</p

Sequence alignment of <i>Rhizopus oryzae</i> lipase (ROL) and ROL-related lipases.

<p>The full-length primary sequences of ROL, <i>R</i>. <i>niveus</i> lipase (RNL), <i>R</i>. <i>stolonifer</i> lipase (RSL), and <i>R</i>. <i>chinensis</i> lipase (RCL) are presented. Multiple-sequence alignments were generated using the ClustalW program (<a href="http://www.ebi.ac.uk/Tools/msa/clustalw2/" target="_blank">http://www.ebi.ac.uk/Tools/msa/clustalw2/</a>). The underlined sequences in the propeptide of ROL (Ser20–Gly37 and Ser38–Glu57) indicate the regions that are essential for secretion and folding of mROL, respectively. The underlined sequences in the mature domain of ROL (Phe183–Asp189) indicate the lid domain. The shadowed region indicates residues that were replaced with hydrophilic amino acids (VDDDDK). In the original host, <i>R</i>. <i>oryzae</i>, the propeptide is also cleaved between the Ala97 and Ser98 residues [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124545#pone.0124545.ref021" target="_blank">21</a>]; however in <i>P</i>. <i>pastoris</i> and <i>S</i>. <i>cerevisiae</i>, the secondary cleavage has not been observed [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124545#pone.0124545.ref014" target="_blank">14</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124545#pone.0124545.ref022" target="_blank">22</a>]. Therefore, in this study, we defined the propeptide domain as the region between residues 1 and 69 and the mature domain as the region between residues 70 and 366 of ROL.</p

Structure of mROL^WT, modeled using the SWISS-MODEL program.

<p>The structure of mROL^WT was modeled based on the open-lid structure of <i>Rhizomucor miehei</i> lipase (Protein Data Bank [PDB] ID: 4TGL), and visualized using PyMOL. The active site residues, S242, D301, and H354, are colored orange. The magenta-colored α-helix represents the lid domain. Green residues indicate hydrophilic amino acids and white residues indicate hydrophobic amino acids.</p

Analysis of the structures and stabilities of mROL^WT and mROL^imp.

<p>(A) Circular dichroism spectra of mROL^WT and mROL^imp. (B) The thermal stabilities of mROL^WT and mROL^imp. The negative ellipticities at 222 nm were measured to determine the fraction folded. The values are presented as mean ± SEM based on three independent measurements. The <i>P</i>-value was determined using a two-factor ANOVA with mROLs and temperatures as independent factors.</p

Definitive screening design enables optimization of LC–ESI–MS/MS parameters in proteomics

<p>In proteomics, more than 100,000 peptides are generated from the digestion of human cell lysates. Proteome samples have a broad dynamic range in protein abundance; therefore, it is critical to optimize various parameters of LC–ESI–MS/MS to comprehensively identify these peptides. However, there are many parameters for LC–ESI–MS/MS analysis. In this study, we applied definitive screening design to simultaneously optimize 14 parameters in the operation of monolithic capillary LC–ESI–MS/MS to increase the number of identified proteins and/or the average peak area of MS1. The simultaneous optimization enabled the determination of two-factor interactions between LC and MS. Finally, we found two parameter sets of monolithic capillary LC–ESI–MS/MS that increased the number of identified proteins by 8.1% or the average peak area of MS1 by 67%. The definitive screening design would be highly useful for high-throughput analysis of the best parameter set in LC–ESI–MS/MS systems.</p> <p>Definitive screening design enables simultaneous optimization of LC-ESI-MS/MS parameters in proteomics.</p

High-throughput evaluation of T7 promoter variants using biased randomization and DNA barcoding

<div><p>Cis-regulatory elements (CREs) are one of the important factors in controlling gene expression and elucidation of their roles has been attracting great interest. We have developed an improved method for analyzing a large variety of mutant CRE sequences in a simple and high-throughput manner. In our approach, mutant CREs with unique barcode sequences were obtained by biased randomization in a single PCR amplification. The original T7 promoter sequence was randomized by biased randomization, and the target number of base substitutions was set to be within the range of 0 to 5. The DNA library and subsequent transcribed RNA library were sequenced by next generation sequencers (NGS) to quantify transcriptional activity of each mutant. We succeeded in producing a randomized T7 promoter library with high coverage rate at each target number of base substitutions. In a single NGS analysis, we quantified the transcriptional activity of 7847 T7 promoter variants. We confirmed that the bases from −9 to −7 play an important role in the transcriptional activity of the T7 promoter. This information coincides with the previous researches and demonstrated the validity of our methodology. Furthermore, using an <i>in vitro</i> transcription/translation system, we found that transcriptional activities of these T7 variants were well correlated with the resultant protein abundance. We demonstrate that our method enables simple and high-throughput analysis of the effects of various CRE mutations on transcriptional regulation.</p></div

Strategy for construction of DNA and RNA samples.

<p>(A) Strategy for construction of DNA samples. DNA samples were constructed by two PCRs. The first PCR was performed to add universal sequence, a randomized T7 promoter, and a barcode sequence to the template. A second PCR was performed to amplify the DNA samples over 30 cycles. (B) Theoretical distribution of the number of base substitution for each randomization ratio. Blue line shows the retention rate at 90%. Orange line shows the retention rate at 70%. Black line shows the retention rate at 50%.</p

The nucleotide bias at each position of the T7 promoter library.

<p>The nucleotide bias at each position of the T7 promoter library.</p