A transfection compound series based on a versatile Tris linkage

The family of cationic lipid transfection reagents described here demonstrates a modular design that offers potential for the ready synthesis of a wide variety of molecular variants. The key feature of these new molecules is the use of Tris as a linker for joining the hydrophobic domain to a cationic head group. The molecular design offers the opportunity to conveniently synthesise compounds differing in charge, the number and nature of hydrophobic groups in the hydrophobic domain and the characteristics of the spacer between the cationic and hydrophobic moieties. We show that prototype reagents of this design can deliver reporter genes into cultured cells with efficiencies rivaling those of established cationic lipid transfection reagents. A feature of these reagents is that they are not dependent on formulation with a neutral lipid for activity.     

Contribution of regions distal to glycine-160 to the anticoagulant activity of tissue factor pathway inhibitor

The functions of the first two Kunitz domains of tissue factor pathway inhibitor (TFPI) are well defined as active site-directed inhibitors of factor VIIa and factor Xa. The anticoagulant properties of the third Kunitz domain and C-terminal region were probed using altered forms of TFPI. TFPI-160 contains the first two Kunitz domains. K1K2C contains the first two Kunitz domains and the basic C-terminus. Neither TFPI-160 nor K1K2C contains the third Kunitz domain. In amidolytic assays containing calcium, TFPI-160 is a less potent inhibitor of factor Xa than TFPI. However, addition of the C-terminus in K1K2C nearly restores inhibitory activity to that of TFPI, indicating that the third Kunitz domain is not required for direct inhibition of factor Xa. When compared in assays containing phospholipids and factor Va, K1K2C and TFPI-160 are poor inhibitors compared to TFPI, demonstrating that the third Kunitz domain is required for the full anticoagulant activity of TFPI. TFPI was further characterized in amidolytic assays performed with Gla-domainless factor Xa and in prothrombin activation assays using submicellar concentrations of short-chain phospholipids (C6PS). TFPI and K1K2C are worse inhibitors of Gla-domainless factor Xa, compared to wild-type factor Xa, while TFPI-160 inhibits both forms of factor Xa equally, suggesting a C-terminus/Gla domain interaction. TFPI is a potent inhibitor of thrombin generation by prothrombinase assembled with C6PS, while TFPI-160 and K1K2C are not. Conversely, TFPI does not inhibit prothrombin activation by prothrombinase assembled on a two-dimensional lipid bilayer. Together, the data indicate that the region between Gly-160 and the end of the third Kunitz domain contributes to TFPI function by orienting the second Kunitz domain so that it can bind the active site of phospholipid-associated factor Xa prior to prothrombinase assembly and/or by slowing formation of the prothrombinase complex.     

Stereochemistry of the enolization of scytalone by scytalone dehydratase

In D(2)O, scytalone exchanges its two C2 hydrogen atoms for deuterium atoms at different rates. At pD 7.0 and 25 degrees C, half-lives for the exchanges are 0.8 and 10 days for the pro-S and pro-R hydrogens, respectively. The differential exchange rates allow for the preparation of multiple scytalone samples (through incubation of scytalone in D(2)O and then back exchanging with H(2)O) having differential levels of deuterium enrichment at the C2 pro-S and pro-R positions. From these samples, the stereochemical preference for hydrogen abstraction during the dehydration reaction mediated by the enzyme scytalone dehydratase was determined. At pH 7. 0, deuterium at the pro-S position has little effect on enzyme catalysis, whereas deuterium at the pro-R position produces kinetic isotope effects of 2.3 (25 degrees C), 5.1 (25 degrees C), and 6.7 (6.8 degrees C) on k(cat), k(cat)/K(m), and the single-turnover rate, respectively. The results are fully consistent with the enzyme catalyzing a syn elimination through an E1cb-like mechanism. The syn elimination is compatible with the interactions realized between a scytalone boat conformation and key active site residues as modeled from multiple X-ray crystal structures of the enzyme in complexes with inhibitors.     

Small, efficient hammerhead ribozymes

The hammerhead ribozyme is able to cleave RNA in a sequence-specific manner. These ribozymes are usually designed with four basepairs in helix II, and with equal numbers of nucleotides in the 5′ and 3′ hybridizing arms that bind the RNA substrate on either side of the cleavage site. Here guidelines are given for redesigning the ribozyme so that it is small, but retains efficient cleavage activity. First, the ribozyme may be reduced in size by shortening the 5′ arm of the ribozyme to five or six nucleotides; for these ribozymes, cleavage of short substrates is maximal. Second, the internal double-helix of the ribozyme (helix II) may be shortened to one or no basepairs, forming a miniribozyme or minizyme, respectively. The sequence of the shortened helix+loop II greatly affects cleavage rates. With eight or more nucleotides in both the 5′ and the 3′ arms of a miniribozyme containing an optimized sequence for helix+loop II, cleavage rates of short substrates are greater than for analogous ribozymes possessing a longer helix II. Cleavage of genelength RNA substrates may be best achieved by miniribozymes.     

A web server to locate periodicities in a sequence

Summary : FT is a tool written in C++, which implements the Fourier analysis method to locate periodicities in aminoacid or DNA sequences. It is provided for free public use on a WWW server with a Java interface. Availability : The server address is http://o2.db. uoa.gr/FT Contact : shamodr@atlas.uoa.gr      

Blood-Based Protein Biomarker Panel for the Detection of Colorectal Cancer

Background

The majority of colorectal cancer (CRC) cases are preventable by early detection and removal of precancerous polyps. Even though CRC is the second most common internal cancer in Australia, only 30 per cent of the population considered to have risk factors participate in stool-based test screening programs. Evidence indicates a robust, blood-based, diagnostic assay would increase screening compliance. A number of potential diagnostic blood-based protein biomarkers for CRC have been reported, but all lack sensitivity or specificity for use as a stand-alone diagnostic. The aim of this study was to identify and validate a panel of protein-based biomarkers in independent cohorts that could be translated to a reliable, non-invasive blood-based screening test.

Principal Findings

In two independent cohorts (n = 145 and n = 197), we evaluated seven single biomarkers in serum of CRC patients and age/gender matched controls that showed a significant difference between controls and CRC, but individually lack the sensitivity for diagnostic application. Using logistic regression strategies, we identified a panel of three biomarkers that discriminated between controls and CRC with 73% sensitivity at 95% specificity, when applied to either of the two cohorts. This panel comprised of Insulin like growth factor binding protein 2 (IGFBP2), Dickkopf-3 (DKK3), and Pyruvate kinase M2(PKM2).

Conclusions

Due to the heterogeneous nature of CRC, a single biomarker is unlikely to have sufficient sensitivity or specificity for use as a stand-alone diagnostic screening test and a panel of markers may be more effective. We have identified a 3 biomarker panel that has higher sensitivity and specificity for early stage (Stage I and -II) disease than the faecal occult blood test, raising the possibility for its use as a non-invasive blood diagnostic or screening test.     

Automatic and quantitative measurement of protein-protein colocalization in live cells

We introduce a novel statistical approach that quantifies, for the first time, the amount of colocalization of two fluorescent-labeled proteins in an image automatically, removing the bias of visual interpretation. This is done by estimating simultaneously the maximum threshold of intensity for each color below which pixels do not show any statistical correlation. The sensitivity of the method was illustrated on simulated data by statistically confirming the existence of true colocalization in images with as little as 3% colocalization. This method was then tested on a large three-dimensional set of fixed cells cotransfected with CFP/YFP pairs of proteins that either co-compartmentalized, interacted, or were just randomly localized in the nucleolus. In this test, the algorithm successfully distinguished random color overlap from colocalization due to either co-compartmentalization or interaction, and results were verified by fluorescence resonance energy transfer. The accuracy and consistency of our algorithm was further illustrated by measuring, for the first time in live cells, the dissociation rate (k(d)) of the HIV-1 Rev/CRM1 export complex induced by the cytotoxin leptomycin B. Rev/CRM1 colocalization in nucleoli dropped exponentially after addition of leptomycin B at a rate of 1.25 x 10(-3) s(-1). More generally, this algorithm can be used to answer a variety of biological questions involving protein-protein interactions or co-compartmentalization and can be generalized to colocalization of more than two colors.     

Automatic segmentation and supervised learning-based selection of nuclei in cancer tissue images

Analysis of preferential localization of certain genes within the cell nuclei is emerging as a new technique for the diagnosis of breast cancer. Quantitation requires accurate segmentation of 100-200 cell nuclei in each tissue section to draw a statistically significant result. Thus, for large-scale analysis, manual processing is too time consuming and subjective. Fortuitously, acquired images generally contain many more nuclei than are needed for analysis. Therefore, we developed an integrated workflow that selects, following automatic segmentation, a subpopulation of accurately delineated nuclei for positioning of fluorescence in situ hybridization-labeled genes of interest. Segmentation was performed by a multistage watershed-based algorithm and screening by an artificial neural network-based pattern recognition engine. The performance of the workflow was quantified in terms of the fraction of automatically selected nuclei that were visually confirmed as well segmented and by the boundary accuracy of the well-segmented nuclei relative to a 2D dynamic programming-based reference segmentation method. Application of the method was demonstrated for discriminating normal and cancerous breast tissue sections based on the differential positioning of the HES5 gene. Automatic results agreed with manual analysis in 11 out of 14 cancers, all four normal cases, and all five noncancerous breast disease cases, thus showing the accuracy and robustness of the proposed approach. ? Published 2012 Wiley Periodicals, Inc.     

Whole cell segmentation in solid tissue sections.

BACKGROUND: Understanding the cellular and molecular basis of tissue development and function requires analysis of individual cells while in their tissue context. METHODS: We developed software to find the optimum border around each cell (segmentation) from two-dimensional microscopic images of intact tissue. Samples were labeled with a fluorescent cell surface marker so that cell borders were brighter than elsewhere. The optimum border around each cell was defined as the border with an average intensity per unit length greater that any other possible border around that cell, and was calculated using the gray-weighted distance transform. Algorithm initiation requiring the user to mark two points per cell, one approximately in the center and the other on the border, ensured virtually 100% correct segmentation. Thereafter segmentation was automatic. RESULTS: The method was highly robust, because intermittent labeling of the cell borders, diffuse borders, and spurious signals away from the border do not significantly affect the optimum path. Computer-generated cells with increasing levels of added noise showed that the approach was accurate provided the cell could be detected visually. CONCLUSIONS: We have developed a highly robust algorithm for segmenting images of surface-labeled cells, enabling accurate and quantitative analysis of individual cells in tissue.