Engineered split in Pfu DNA polymerase fingers domain improves incorporation of nucleotide γ-phosphate derivative

Using compartmentalized self-replication (CSR), we evolved a version of Pyrococcus furiosus (Pfu) DNA polymerase that tolerates modification of the γ-phosphate of an incoming nucleotide. A Q484R mutation in α-helix P of the fingers domain, coupled with an unintended translational termination-reinitiation (split) near the finger tip, dramatically improve incorporation of a bulky γ-phosphate-O-linker-dabcyl substituent. Whether synthesized by coupled translation from a bicistronic (−1 frameshift) clone, or reconstituted from separately expressed and purified fragments, split Pfu mutant behaves identically to wild-type DNA polymerase with respect to chromatographic behavior, steady-state kinetic parameters (for dCTP), and PCR performance. Although naturally-occurring splits have been identified previously in the finger tip region of T4 gp43 variants, this is the first time a split (in combination with a point mutation) has been shown to broaden substrate utilization. Moreover, this latest example of a split hyperthermophilic archaeal DNA polymerase further illustrates the modular nature of the Family B DNA polymerase structure

An accurate and interpretable model for siRNA efficacy prediction

BACKGROUND: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging. RESULTS: We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions. CONCLUSION: The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web a

An algorithm for classifying tumors based on genomic aberrations and selecting representative tumor models

<p>Abstract</p> <p>Background</p> <p>Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose.</p> <p>Method</p> <p>To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.</p> <p>Result</p> <p>We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC), colorectal cancer (CRC), and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes.</p> <p>Conclusions</p> <p>We developed an algorithm for cancer classification based on genome-wide patterns of copy number aberrations and demonstrated its superiority to existing clustering methods. The algorithm was applied to define genomic subgroups of three cancer types and identify cell lines representative of these subgroups. Our data enabled the assembly of representative cell line panels for testing drug candidates.</p

Cellular delivery of small interfering RNA by a non-covalently attached cell-penetrating peptide: quantitative analysis of uptake and biological effect

Cell-penetrating peptides (CPPs) have evolved as promising new tools to deliver nucleic acids into cells. So far, the majority of these delivery systems require a covalent linkage between carrier and cargo. To exploit the higher flexibility of a non-covalent strategy, we focused on the characterisation of a novel carrier peptide termed MPGα, which spontaneously forms complexes with nucleic acids. Using a luciferase-targeted small interfering RNA (siRNA) as cargo, we optimised the conditions for MPGα-mediated transfection of mammalian cells. In this system, reporter gene activity could be inhibited up to 90% with an IC(50) value in the sub-nanomolar range. As a key issue, we addressed the cellular uptake mechanism of MPGα/siRNA complexes applying various approaches. First, transfection of HeLa cells with MPGα/siRNA complexes in the presence of several inhibitors of endocytosis showed a significant reduction of the RNA interference (RNAi) effect. Second, confocal laser microscopy revealed a punctual intracellular pattern rather than a diffuse distribution of fluorescently labelled RNA-cargo. These data provide strong evidence of an endocytotic pathway contributing significantly to the uptake of MPGα/siRNA complexes. Finally, we quantified the intracellular number of siRNA molecules after MPGα-mediated transfection. The amount of siRNA required to induce half maximal RNAi was 10 000 molecules per cell. Together, the combination of methods provided allows for a detailed side by side quantitative analysis of cargo internalisation and related biological effects. Thus, the overall efficiency of a given delivery technique as well as the mechanism of uptake can be assessed

Myosin II Motor Proteins with Different Functions Determine the Fate of Lamellipodia Extension during Cell Spreading

Non-muscle cells express multiple myosin-II motor proteins myosin IIA, myosin IIB and myosin IIC transcribed from different loci in the human genome. Due to a significant homology in their sequences, these ubiquitously expressed myosin II motor proteins are believed to have overlapping cellular functions, but the mechanistic details are not elucidated. The present study uncovered a mechanism that coordinates the distinctly localized myosin IIA and myosin IIB with unexpected opposite mechanical roles in maneuvering lamellipodia extension, a critical step in the initiation of cell invasion, spreading, and migration. Myosin IIB motor protein by localizing at the front drives lamellipodia extension during cell spreading. On the other hand, myosin IIA localizes next to myosin IIB and attenuates or retracts lamellipodia extension. Myosin IIA and IIB increase cell adhesion by regulating focal contacts formation in the spreading margins and central part of the spreading cell, respectively. Spreading cells expressing both myosin IIA and myosin IIB motor proteins display an organized actin network consisting of retrograde filaments, arcs and central filaments attached to focal contacts. This organized actin network especially arcs and focal contacts formation in the spreading margins were lost in myosin IIÂ cells. Surprisingly, myosin IIB̂ cells displayed long parallel actin filaments connected to focal contacts in the spreading margins. Thus, with different roles in the regulation of the actin network and focal contacts formation, both myosin IIA and IIB determine the fate of lamellipodia extension during cell spreading

Dissecting Oct3/4-Regulated Gene Networks in Embryonic Stem Cells by Expression Profiling

POU transcription factor Pou5f1 (Oct3/4) is required to maintain ES cells in an undifferentiated state. Here we show that global expression profiling of Oct3/4-manipulated ES cells delineates the downstream target genes of Oct3/4. Combined with data from genome-wide chromatin-immunoprecipitation (ChIP) assays, this analysis identifies not only primary downstream targets of Oct3/4, but also secondary or tertiary targets. Furthermore, the analysis also reveals that downstream target genes are regulated either positively or negatively by Oct3/4. Identification of a group of genes that show both activation and repression depending on Oct3/4 expression levels provides a possible mechanism for the requirement of appropriate Oct3/4 expression to maintain undifferentiated ES cells. As a proof-of-principle study, one of the downstream genes, Tcl1, has been analyzed in detail. We show that Oct3/4 binds to the promoter region of Tcl1 and activates its transcription. We also show that Tcl1 is involved in the regulation of proliferation, but not differentiation, in ES cells. These findings suggest that the global expression profiling of gene-manipulated ES cells can help to delineate the structure and dynamics of gene regulatory networks