Synthesis of Short Peptides with Perfluoroalkyl Side Chains and Evaluation of Their Cellular Uptake Efficiency.

With an increasing demand for macromolecular biotherapeutics, the issue of their poor cell-penetrating abilities requires viable and relevant solutions. Herein, we report tripeptides bearing an amino acid with a perfluoroalkyl (RF ) group adjacent to the α-carbon. RF -containing tripeptides were synthesized and evaluated for their ability to transport a conjugated hydrophilic dye (Alexa Fluor 647) into the cells. RF -containing tripeptides with the fluorophore showed high cellular uptake efficiency and none of them were cytotoxic. Interestingly, we demonstrated that the absolute configuration of perfluoroalkylated amino acids (RF -AAs) affects not only nanoparticle formation but also the cell permeability of the tripeptides. These novel RF -containing tripeptides are potentially useful as short and noncationic cell-penetrating peptides (CPPs).

Differential expression analysis using a model-based gene clustering algorithm for RNA-seq data.

BACKGROUND: RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering is used to classify DEGs with similar expression patterns for the subsequent analyses of data from experiments such as time-courses or multi-group comparisons. However, gene clustering has rarely been used for analyzing simple two-group data or differential expression (DE). In this study, we report that a model-based clustering algorithm implemented in an R package, MBCluster.Seq, can also be used for DE analysis. RESULTS: The input data originally used by MBCluster.Seq is DEGs, and the proposed method (called MBCdeg) uses all genes for the analysis. The method uses posterior probabilities of genes assigned to a cluster displaying non-DEG pattern for overall gene ranking. We compared the performance of MBCdeg with conventional R packages such as edgeR, DESeq2, and TCC that are specialized for DE analysis using simulated and real data. Our results showed that MBCdeg outperformed other methods when the proportion of DEG (PDEG) was less than 50%. However, the DEG identification using MBCdeg was less consistent than with conventional methods. We compared the effects of different normalization algorithms using MBCdeg, and performed an analysis using MBCdeg in combination with a robust normalization algorithm (called DEGES) that was not implemented in MBCluster.Seq. The new analysis method showed greater stability than using the original MBCdeg with the default normalization algorithm. CONCLUSIONS: MBCdeg with DEGES normalization can be used in the identification of DEGs when the PDEG is relatively low. As the method is based on gene clustering, the DE result includes information on which expression pattern the gene belongs to. The new method may be useful for the analysis of time-course and multi-group data, where the classification of expression patterns is often required.

Rhinoceros beetle horn development reveals deep parallels with dung beetles.

Beetle horns are attractive models for studying the evolution of novel traits, as they display diverse shapes, sizes, and numbers among closely related species within the family Scarabaeidae. Horns radiated prolifically and independently in two distant subfamilies of scarabs, the dung beetles (Scarabaeinae), and the rhinoceros beetles (Dynastinae). However, current knowledge of the mechanisms underlying horn diversification remains limited to a single genus of dung beetles, Onthophagus. Here we unveil 11 horn formation genes in a rhinoceros beetle, Trypoxylus dichotomus. These 11 genes are mostly categorized as larval head- and appendage-patterning genes that also are involved in Onthophagus horn formation, suggesting the same suite of genes was recruited in each lineage during horn evolution. Although our RNAi analyses reveal interesting differences in the functions of a few of these genes, the overwhelming conclusion is that both head and thoracic horns develop similarly in Trypoxylus and Onthophagus, originating in the same developmental regions and deploying similar portions of appendage patterning networks during their growth. Our findings highlight deep parallels in the development of rhinoceros and dung beetle horns, suggesting either that both horn types arose in the common ancestor of all scarabs, a surprising reconstruction of horn evolution that would mean the majority of scarab species (~35,000) actively repress horn growth, or that parallel origins of these extravagant structures resulted from repeated co-option of the same underlying developmental processes.

Gene regulatory network and its constituent transcription factors that control nitrogen-deficiency responses in rice.

Increase in the nitrogen (N)-use efficiency and optimization of N response in crop species are urgently needed. Although transcription factor-based genetic engineering is a promising approach for achieving these goals, transcription factors that play key roles in the response to N deficiency have not been studied extensively. Here, we performed RNA-seq analysis of root samples of 20 Asian rice (Oryza sativa) accessions with differential nutrient uptake. Data obtained from plants exposed to N-replete and N-deficient conditions were subjected to coexpression analysis and machine learning-based pathway inference to dissect the gene regulatory network required for the response to N deficiency. Four transcription factors, including members of the G2-like and bZIP families, were predicted to function as key regulators of gene transcription within the network in response to N deficiency. Cotransfection assays validated inferred novel regulatory pathways, and further analyses using genome-edited knockout lines suggested that these transcription factors are important for N-deficiency responses in planta. Many of the N deficiency-responsive genes, including those encoding key regulators within the network, were coordinately regulated by transcription factors belonging to different families. Transcription factors identified in this study could be valuable for the modification of N response and metabolism.

Silhouette Scores for Arbitrary Defined Groups in Gene Expression Data and Insights into Differential Expression Results.

BACKGROUND: Hierarchical Sample clustering (HSC) is widely performed to examine associations within expression data obtained from microarrays and RNA sequencing (RNA-seq). Researchers have investigated the HSC results with several possible criteria for grouping (e.g., sex, age, and disease types). However, the evaluation of arbitrary defined groups still counts in subjective visual inspection. RESULTS: To objectively evaluate the degree of separation between groups of interest in the HSC dendrogram, we propose to use Silhouette scores. Silhouettes was originally developed as a graphical aid for the validation of data clusters. It provides a measure of how well a sample is classified when it was assigned to a cluster by according to both the tightness of the clusters and the separation between them. It ranges from 1.0 to - 1.0, and a larger value for the average silhouette (AS) over all samples to be analyzed indicates a higher degree of cluster separation. The basic idea to use an AS is to replace the term cluster by group when calculating the scores. We investigated the validity of this score using simulated and real data designed for differential expression (DE) analysis. We found that larger (or smaller) AS values agreed well with both higher (or lower) degrees of separation between different groups and higher percentages of differentially expressed genes (PDEG). We also found that the AS values were generally independent on the number of replicates (Nrep). Although the PDEG values depended on Nrep, we confirmed that both AS and PDEG values were close to zero when samples in the data showed an intermingled nature between the groups in the HSC dendrogram. CONCLUSION: Silhouettes is useful for exploring data with predefined group labels. It would help provide both an objective evaluation of HSC dendrograms and insights into the DE results with regard to the compared groups.

Evaluation of methods for differential expression analysis on multi-group RNA-seq count data.

BACKGROUND: RNA-seq is a powerful tool for measuring transcriptomes, especially for identifying differentially expressed genes or transcripts (DEGs) between sample groups. A number of methods have been developed for this task, and several evaluation studies have also been reported. However, those evaluations so far have been restricted to two-group comparisons. Accumulations of comparative studies for multi-group data are also desired. METHODS: We compare 12 pipelines available in nine R packages for detecting differential expressions (DE) from multi-group RNA-seq count data, focusing on three-group data with or without replicates. We evaluate those pipelines on the basis of both simulation data and real count data. RESULTS: As a result, the pipelines in the TCC package performed comparably to or better than other pipelines under various simulation scenarios. TCC implements a multi-step normalization strategy (called DEGES) that internally uses functions provided by other representative packages (edgeR, DESeq2, and so on). We found considerably different numbers of identified DEGs (18.5 ~ 45.7% of all genes) among the pipelines for the same real dataset but similar distributions of the classified expression patterns. We also found that DE results can roughly be estimated by the hierarchical dendrogram of sample clustering for the raw count data. CONCLUSION: We confirmed the DEGES-based pipelines implemented in TCC performed well in a three-group comparison as well as a two-group comparison. We recommend using the DEGES-based pipeline that internally uses edgeR (here called the EEE-E pipeline) for count data with replicates (especially for small sample sizes). For data without replicates, the DEGES-based pipeline with DESeq2 (called SSS-S) can be recommended.

Impact of denervation-induced muscle atrophy on housekeeping gene expression in mice.

INTRODUCTION: Immobilization induced by experimental denervation leads to rapid and progressive alterations in structural and biochemical properties of skeletal muscle. Real-time reverse transcription-polymerase chain reaction (RT-PCR) is a popular method of elucidating the molecular mechanisms involved in muscle atrophy. Identification of suitable reference genes that are not affected by experimental conditions is a critical step in accurate normalization of real-time RT-PCR. METHODS: We investigated the impact of denervation-induced muscle atrophy for 2 weeks on the expression of common housekeeping genes. RESULTS: Denervation differentially affected the expression levels of these genes. RefFinder software identified TATA box binding protein (Tbp) as the most stable gene and showed that the stability of glyceraldehyde-3-phosphate dehydrogenase (Gapdh) and hypoxanthine guanine phosphoribosyl transferase (Hprt) genes was low, even though they are widely used for normalization. CONCLUSIONS: The appropriate reference gene for normalization of genes of interest in denervated muscle is Tbp.

Enhanced clustering-based differential expression analysis method for RNA-seq data.

RNA-seq is a tool for measuring gene expression and is commonly used to identify differentially expressed genes (DEGs). Gene clustering has been widely used to classify DEGs with similar expression patterns, but rarely used to identify DEGs themselves. We recently reported that the clustering-based method (called MBCdeg1 and 2) for identifying DEGs has great potential. However, these methods left room for improvement. This study reports on the improvement (named MBCdeg3). We compared a total of six competing methods: three conventional R packages (edgeR, DESeq2, and TCC) and three versions of MBCdeg (i.e., MBCdeg1, 2, and 3) corresponding to three different normalization algorithms. As MBCdeg3 performs well in many simulation scenarios of RNA-seq count data, MBCdeg3 replaces MBCdeg1 and 2 in our previous report. •MBCdeg3 is a method for both identification and classification of DEGs from RNA-seq count data.•MBCdeg3 is available as a function of R, which is common in the field of expression analysis.•MBCdeg3 performs well in a variety of simulation scenarios for RNA-seq count data.

TCC: an R package for comparing tag count data with robust normalization strategies.

BACKGROUND: Differential expression analysis based on "next-generation" sequencing technologies is a fundamental means of studying RNA expression. We recently developed a multi-step normalization method (called TbT) for two-group RNA-seq data with replicates and demonstrated that the statistical methods available in four R packages (edgeR, DESeq, baySeq, and NBPSeq) together with TbT can produce a well-ranked gene list in which true differentially expressed genes (DEGs) are top-ranked and non-DEGs are bottom ranked. However, the advantages of the current TbT method come at the cost of a huge computation time. Moreover, the R packages did not have normalization methods based on such a multi-step strategy. RESULTS: TCC (an acronym for Tag Count Comparison) is an R package that provides a series of functions for differential expression analysis of tag count data. The package incorporates multi-step normalization methods, whose strategy is to remove potential DEGs before performing the data normalization. The normalization function based on this DEG elimination strategy (DEGES) includes (i) the original TbT method based on DEGES for two-group data with or without replicates, (ii) much faster methods for two-group data with or without replicates, and (iii) methods for multi-group comparison. TCC provides a simple unified interface to perform such analyses with combinations of functions provided by edgeR, DESeq, and baySeq. Additionally, a function for generating simulation data under various conditions and alternative DEGES procedures consisting of functions in the existing packages are provided. Bioinformatics scientists can use TCC to evaluate their methods, and biologists familiar with other R packages can easily learn what is done in TCC. CONCLUSION: DEGES in TCC is essential for accurate normalization of tag count data, especially when up- and down-regulated DEGs in one of the samples are extremely biased in their number. TCC is useful for analyzing tag count data in various scenarios ranging from unbiased to extremely biased differential expression. TCC is available at http://www.iu.a.u-tokyo.ac.jp/~kadota/TCC/ and will appear in Bioconductor (http://bioconductor.org/) from ver. 2.13.

Zygotic amplification of secondary piRNAs during silkworm embryogenesis.

PIWI-interacting RNAs (piRNAs) are 23-30-nucleotide-long small RNAs that act as sequence-specific silencers of transposable elements in animal gonads. In flies, genetics and deep sequencing data have led to a hypothesis for piRNA biogenesis called the ping-pong cycle, where antisense primary piRNAs initiate an amplification loop to generate sense secondary piRNAs. However, to date, the process of the ping-pong cycle has never been monitored at work. Here, by large-scale profiling of piRNAs from silkworm ovary and embryos of different developmental stages, we demonstrate that maternally inherited antisense-biased piRNAs trigger acute amplification of secondary sense piRNA production in zygotes, at a time coinciding with zygotic transcription of sense transposon mRNAs. These results provide on-site evidence for the ping-pong cycle.

The silkworm W chromosome is a source of female-enriched piRNAs.

In the silkworm, Bombyx mori, the W chromosome plays a dominant role in female determination. However, neither protein-coding genes nor transcripts have so far been isolated from the W chromosome. Instead, a large amount of functional transposable elements and their remnants are accumulated on the W chromosome. PIWI-interacting RNAs (piRNAs) are 23-30-nt-long small RNAs that potentially act as sequence-specific guides for PIWI proteins to silence transposon activity in animal gonads. In this study, by comparing ovary- and testis-derived piRNAs, we identified numerous female-enriched piRNAs. Our data indicated that female-enriched piRNAs are derived from the W chromosome. Moreover, comparative analyses on piRNA profiles from a series of W chromosome mutant strains revealed a striking enrichment of a specific set of transposon-derived piRNAs in the putative sex-determining region. Collectively, we revealed the nature of the silkworm W chromosome as a source of piRNAs.

Implicit visuomotor processing for quick online reactions is robust against aging.

It is well established that humans can react more quickly to a visual stimulus in the visual field center than to one in the visual periphery and that the reaction to a stimulus in the visual periphery markedly deteriorates with aging. These tendencies are true in conventional discrimination-reaction tasks. Surprisingly, however, we found that they are entirely different when reactions are induced by the same visual stimuli during reaching movements. The reaction time for a stimulus in the visual periphery was significantly faster than in the central vision, and age-related slowing of reactions to the stimulus in the visual periphery were quite small, compared to that observed in the conventional reaction tasks. This inconsistent slowing of reactions in different motor conditions underscores a distinctive visuomotor pathway for online control, which is more robust against age-related deterioration.

Evaluating methods for ranking differentially expressed genes applied to microArray quality control data.

BACKGROUND: Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and reproducibility. In our previous studies, we evaluated eight gene ranking methods applied to only Affymetrix GeneChip data. A more general evaluation that also includes other microarray platforms, such as the Agilent or Illumina systems, is desirable for determining which methods are suitable for each platform and which method has better inter-platform reproducibility. RESULTS: We compared the eight gene ranking methods using the MicroArray Quality Control (MAQC) datasets produced by five manufacturers: Affymetrix, Applied Biosystems, Agilent, GE Healthcare, and Illumina. The area under the curve (AUC) was used as a measure for both sensitivity and specificity. Although the highest AUC values can vary with the definition of "true" DEGs, the best methods were, in most cases, either the weighted average difference (WAD), rank products (RP), or intensity-based moderated t statistic (ibmT). The percentages of overlapping genes (POGs) across different test sites were mainly evaluated as a measure for both intra- and inter-platform reproducibility. The POG values for WAD were the highest overall, irrespective of the choice of microarray platform. The high intra- and inter-platform reproducibility of WAD was also observed at a higher biological function level. CONCLUSION: These results for the five microarray platforms were consistent with our previous ones based on 36 real experimental datasets measured using the Affymetrix platform. Thus, recommendations made using the MAQC benchmark data might be universally applicable.

Mass identification of transcriptional units expressed from the Bombyx mori nucleopolyhedrovirus genome.

In order to identify the transcriptional units expressed from an entire nucleopolyhedrovirus (NPV) genome during infection, we constructed a full-length-enriched cDNA library from Bombyx mori NPV (BmNPV)-infected BmN cells. We randomly sequenced 11,520 clones from both ends to obtain a total of 4679 BmNPV-derived transcriptional units. The data revealed a number of novel transcripts, including putative non-coding RNAs, most of which are expressed from recognized baculovirus early or late promoter motifs. These findings provide new insights into the complex transcriptional regulation of an NPV genome and suggest roles for as-yet-uncharacterized transcripts.

Effects of Daily Hand Activities on Age-Related Declines of Dynamic Motor Function in Individual Fingers.

The present study examined the effects of daily activities of the hands on finger motor function in older adults. Maximum tapping frequency with each finger during single-finger tapping and alternate movements of index-middle, middle-ring, and ring-little finger pairs during double-finger tapping were compared between older adults who used their hands actively in their daily lives and those who did not. The active participants had significantly faster tapping rates for the ring finger in the single-finger tapping and the middle-ring finger pair in the double-finger tapping than did the inactive participants. Thus, daily activity of the hands in older adults could be effective at preventing the loss of dynamic motor function in individual fingers, especially with greater difficulty in movement, resulting from the degeneration with age.

Spatial Accuracy of Predictive Saccades Determines the Performance of Continuous Visuomotor Action.

In a table tennis rally, players perform interceptive actions on a moving ball continuously in a short time, such that the acquisition process of visual information is an important determinant of the performance of the action. However, because it is technically hard to measure gaze movement in a real game, little is known about how gaze behavior is conducted during the continuous visuomotor actions and contributes to the performance. To examine these points, we constructed a novel psychophysical experiment model enabling a continuous visuomotor task without spatial movement of any body parts, including the arm and head, and recorded the movement of the gaze and effector simultaneously at high spatiotemporal resolution. In the task, Gabor patches (target) moved one after another at a constant speed from right to left at random vertical positions on an LC display. Participants hit the target with a cursor moving vertically on the left side of the display by controlling their prehensile force on a force sensor. Participants hit the target with the cursor using a rapid-approaching movement (rapid cursor approach, RCA). Their gaze also showed rapid saccadic approaching movement (saccadic eye approach, SEA), reaching the predicted arrival point of the target earlier than the cursor. The RCA reached in or near the Hit zone in the successful (Hit) trial, but ended up away from it in the unsuccessful (Miss) trial, suggesting the spatial accuracy of the RCA determines the task's success. The SEA in the Hit trial ended nearer the target than the Miss trial. The spatial accuracy of the RCA diminished when the target disappeared 100 ms just after the end of the SEA, suggesting that visual information acquired after the saccade acted as feedback information to correct the cursor movement online for the cursor to reach the target. There was a target speed condition that the target disappearance did not compromise RCA's spatial accuracy, implying the possible RCA correction based on the post-saccadic gaze location information. These experiments clarified that gaze behavior conducted during fast continuous visuomotor actions enables online correction of the ongoing interceptive movement of an effector, improving visuomotor performance.

Bezafibrate induces plasminogen activator inhibitor-1 gene expression in a CLOCK-dependent circadian manner.

A functional interaction between peroxisome proliferator-activated receptor alpha (PPARalpha) and components of the circadian clock has been suggested, but whether these transcriptional factors interact to regulate the expression of their target genes remains obscure. Here we used a PPARalpha ligand, bezafibrate, to search for PPARalpha-regulated genes that are expressed in a CLOCK-dependent circadian manner. Microarray analyses using hepatic RNA isolated from bezafibrate treated-wild type, Clock mutant (Clk/Clk), and PPARalpha-null mice revealed that 136 genes are transcriptionally regulated by PPARalpha in a CLOCK-dependent manner. Among them, we focused on the plasminogen activator inhibitor-1 (PAI-1) gene, because its expression typically shows circadian variation, and it has transcriptional response elements for both PPAR and CLOCK. The bezafibrate-induced expression of PAI-1 mRNA was attenuated in Clk/Clk mice and in PPARalpha-null mice. The protein levels of PPARalpha were reduced in Clk/Clk hepatocytes. However, the overexpression of PPARalpha could not rescue bezafibrate-induced PAI-1 expression in Clk/Clk hepatocytes, suggesting that impaired bezafibrate-induced PAI-1 expression in Clk/Clk mice is not due to reduced PPARalpha expression. Luciferase reporter and chromatin immunoprecipitation analyses using primary hepatocytes demonstrated that DNA binding of both PPARalpha and CLOCK is essential for bezafibrate-induced PAI-1 gene expression. Pull-down assays in vitro showed that both PPARalpha and its heterodimerized partner retinoic acid receptor-alpha can serve as potential interaction targets of CLOCK. The present findings revealed that molecular interaction between the circadian clock and the lipid metabolism regulator affects the bezafibrate-induced gene expression.

Response of the Pseudomonas host chromosomal transcriptome to carriage of the IncP-7 plasmid pCAR1.

Plasmid carriage requires appropriate expression of the genes on the plasmid or host chromosome through cooperative transcriptional regulation. To clarify the impact of plasmid carriage on the host chromosome, we compared the chromosomal RNA maps of plasmid-free and plasmid-containing host strains using the incompatibility group P-7 archetype plasmid pCAR1, which is involved in carbazole degradation, and three distinct Pseudomonas strains. The possession of pCAR1 altered gene expression related to the iron acquisition systems in each host. Expression of the major siderophore pyoverdine was greater in plasmid-containing P. putida KT2440 and P. aeruginosa PAO1 than in the plasmid-free host strains, in part due to the expression of carbazole-degradative genes on pCAR1. The mexEFoprN operon encoding an efflux pump of the resistance-nodulation-cell division family was specifically upregulated by the carriage of pCAR1 in P. putida KT2440, whereas the expression of orthologous genes in the other species remained unaltered. Induction of the mexEFoprN genes increased the resistance of pCAR1-containing KT2440 to chloramphenicol compared with pCAR1-free KT2440. Our findings indicate that the possession of pCAR1 altered the growth rate of the host via the expression of genes on pCAR1 and the host chromosomes.

Ketogenic diet disrupts the circadian clock and increases hypofibrinolytic risk by inducing expression of plasminogen activator inhibitor-1.

OBJECTIVE: Metabolic disorders such as diabetes and obesity are considered risk factors for cardiovascular diseases by increasing levels of blood plasminogen activator inhibitor-1 (PAI-1). Ketogenic diets (KDs) have been used as an approach to weight loss in both obese and nonobese individuals. We examined circadian changes in plasma PAI-1 and its mRNA expression levels in tissues from mice fed with a KD (KD mice), to evaluate its effects on fibrinolytic functions. METHODS AND RESULTS: Two weeks on the kDa increased plasma levels of free fatty acids and ketones accompanied by hypoglycemia in mice. Plasma PAI-1 concentrations were extremely elevated in accordance with mRNA expression levels in the heart and liver, but not in the kidneys of KD mice. Circadian expression of PAI-1 mRNA was phase-advanced for 4.7, 7.9, and 7.8 hours in the heart, kidney, and adipose tissues, respectively, as well as that of circadian genes mPer2 and DBP in KD mice, suggesting that peripheral clocks were phase-advanced by ketosis despite feeding ad libitum under a periodic light-dark cycle. The circadian clock that regulates behavioral activity rhythms was also phase-advanced, and its free-running period was significantly shortened in KD mice. CONCLUSIONS: Our findings suggest that ketogenic status increases hypofibrinolytic risk by inducing abnormal circadian expression of PAI-1.

Effect of quercetin on the gene expression profile of the mouse intestine.

BALB/c mice were administered with quercetin or its derivatives (quercetin-3-glucoside, quercetin-4'-glucoside and rutin, 5 or 50 mg/kg BW) for 2 weeks. The mucosa of the small intestine were recovered and subjected to a microarray analysis using Affymetrix Mouse Genome 430 2.0 Array. A cluster analysis shows that only the "low dose group" had a significantly different gene expression profile from the negative control group.