New Approach for Interpreting Changes in Circulating Tumour Cells (CTC) for Evaluation of Treatment Effect in Metastatic Breast Cancer

Aim: Attempts have been made to use CTC values for interpretation of treatment response and to guide change of chemotherapy by using a static cut-off of 5 CTC to stratify patients in favourable or unfavourable responders. We propose a new approach to interpret treatment effect using significant changes in CTC values (SCV-limits¹) as grouping parameter for responders and non-responders to chemotherapy among metastatic breast cancer (mBC) patients. Method: CTC were analysed using the CellSearch System in blood from 47 mBC patients before the start of new chemotherapy and before the third cycle of therapy. The new and old approach to interpret changes in CTC values were compared in relation to progression free survival (PFS). Results: The new approach using significant CTC change (P = .032) and the old approach using static cut-off (P > .001) correlated significantly with PFS using a cohort of 47 patients. Conclusion: We propose a new approach to interpret significant changes between baseline and follow-up CTC values as a tool for assessing treatment effect in mBC. Our approach stratified patients in new risk groups that were stratified significantly with respect to PFS. More patients are needed to balance the size of the risk groups for better comparison to the existing approach based on a 5 CTC cut-off.     

Segmented K-mer and its application on similarity analysis of mitochondrial genome sequences

K-mer-based approach has been widely used in similarity analyses so as to discover similarity/dissimilarity among different biological sequences. In this study, we have improved the traditional K-mer method, and introduce a segmented K-mer approach (s-K-mer). After each primary sequence is divided into several segments, we simultaneously transform all these segments into corresponding K-mer-based vectors. In this approach, it is vital how to determine the optimal combination of distance metric with the number of K and the number of segments, i.e., (K^?, s^?, and d^?). Based on the cascaded feature vectors transformed from s^? segmented sequences, we analyze 34 mammalian genome sequences using the proposed s-K-mer approach. Meanwhile, we compare the results of s-K-mer with those of traditional K-mer. The contrastive analysis results demonstrate that s-K-mer approach outperforms the traditionally K-mer method on similarity analysis among different species.     

A novel in silico approach to identify potential therapeutic targets in human bacterial pathogens

In recent years, genome-sequencing projects of pathogens and humans have revolutionized microbial drug target identification. Of the several known genomic strategies, subtractive genomics has been successfully utilized for identifying microbial drug targets. The present work demonstrates a novel genomics approach in which codon adaptation index (CAI), a measure used to predict the translational efficiency of a gene based on synonymous codon usage, is coupled with subtractive genomics approach for mining potential drug targets. The strategy adopted is demonstrated using respiratory pathogens, namely, Streptococcus pneumoniae and Haemophilus influenzae as examples. Our approach identified 8 potent target genes (Streptococcus pneumoniae?C2, H. influenzae?C6), which are functionally significant and also play key role in host-pathogen interactions. This approach facilitates swift identification of potential drug targets, thereby enabling the search for new inhibitors. These results underscore the utility of CAI for enhanced in silico drug target identification.     

A Novel Quantitative Kinase Assay Using Bacterial Surface Display and Flow Cytometry

The inhibition of tyrosine kinases is a successful approach for the treatment of cancers and the discovery of kinase inhibitor drugs is the focus of numerous academic and pharmaceutical laboratories. With this goal in mind, several strategies have been developed to measure kinase activity and to screen novel tyrosine kinase inhibitors. Nevertheless, a general non-radioactive and inexpensive approach, easy to implement and adapt to a range of applications, is still missing. Herein, using Bcr-Abl tyrosine kinase, an oncogenic target and a model protein for cancer studies, we describe a novel cost-effective high-throughput screening kinase assay. In this approach, named the BacKin assay, substrates displayed on a Bacterial cell surface are incubated with Kinase and their phosphorylation is examined and quantified by flow cytometry. This approach has several advantages over existing approaches, as using bacteria (i.e. Escherichia coli) to display peptide substrates provides a self renewing solid support that does not require laborious chemical strategies. Here we show that the BacKin approach can be used for kinetic and mechanistic studies, as well as a platform to characterize and identify small-molecule or peptide-based kinase inhibitors with potential applications in drug development.     

New method for global alignment of 2 DNA sequences by the tree data structure

We introduce a new approach to investigate problem of DNA sequence alignment. The method consists of three parts: (i) simple alignment algorithm, (ii) extension algorithm for largest common substring, (iii) graphical simple alignment tree (GSA tree). The approach firstly obtains a graphical representation of scores of DNA sequences by the scoring equation R₀*R−S₀*S−T₀*(a+bk). Then a GSA tree is constructed to facilitate solving the problem for global alignment of 2 DNA sequences. Finally we give several practical examples to illustrate the utility and practicality of the approach.     

Systematic Analysis of Experimental Phenotype Data Reveals Gene Functions

High-throughput phenotyping projects in model organisms have the potential to improve our understanding of gene functions and their role in living organisms. We have developed a computational, knowledge-based approach to automatically infer gene functions from phenotypic manifestations and applied this approach to yeast (Saccharomyces cerevisiae), nematode worm (Caenorhabditis elegans), zebrafish (Danio rerio), fruitfly (Drosophila melanogaster) and mouse (Mus musculus) phenotypes. Our approach is based on the assumption that, if a mutation in a gene leads to a phenotypic abnormality in a process , then must have been involved in , either directly or indirectly. We systematically analyze recorded phenotypes in animal models using the formal definitions created for phenotype ontologies. We evaluate the validity of the inferred functions manually and by demonstrating a significant improvement in predicting genetic interactions and protein-protein interactions based on functional similarity. Our knowledge-based approach is generally applicable to phenotypes recorded in model organism databases, including phenotypes from large-scale, high throughput community projects whose primary mode of dissemination is direct publication on-line rather than in the literature.     

A universal approach to the synthesis of carbohydrate conjugates of polyhedral boron compounds as potential agents for boron neutron capture therapy

A universal approach to the synthesis of carbohydrate conjugates with polyhedral boron compounds (PBCs) was developed. Oligosaccharide derivatives with amino group in aglycone moiety can be conjugated with PBC carboxy derivatives using N-methyl-N-(4,6-dimethoxy-1,3,5-triazin-2-yl)morpholinium chloride as a condensing agent. Both N-and O-glycosides differing in the conformation mobility around the glycoside bond were shown to be useful as oligosaccharides with a functional group in the aglycone moiety. This allows the application of this approach to the synthesis of PBC conjugates with a wide range of oligosaccharides isolated from natural sources can be transformed into N-glycosides with a functional group in aglycone. The approach was tested by conjugation of the carboxy derivatives of ortho-carborane and dodecaborate anion with lactose as a model oligosaccharide. Lactose, an easily available disaccharide, is a ligand of lectins expressed on the surface of melanoma cells. The approach suggested is the first example of the synthesis of such conjugates that does not require protective groups for the carbohydrate residue. It is especially important for obtaining dodecaborate-carbohydrate conjugates for which the removal of protective groups is often a non-trivial task.     

Relationship of three measures of behavior to milk production

Nine commerical herds were observed on three separate occasion for flight distance, i.e., how close a human can come before a stationary cow moves away, and approach distance, i.e., how close a cow will come to a stationary human. Herdsmen from each herd scored their cows on parlor behavior using a scoring system that ranged from 1 (the most docile) to 5 (the most aggressive). These three behavior factors were compared with milk production. Both mean flight distance and mean approach distance were 1.6 m. Mean parlor score was 2.2 and mean production was 9153 kg. These were significant inter-herd correlations between flight distance and approach distance (r=0.30), flight distance and parlor score (r=0.20), and parlor score and milk production (r=0.08); however, only flight distance and approach distance (r=0.18), and flight distance and parlor score (r=0.12) were significantly correlated within herds. There was no significant intraherd correlation between milk production and any of the behavioral factors considered. These findings indicate that while parlor score is associated with milk production across herds, flight distance and approach distance are not useful indicators of milk production.     

Diagnostic Probes Targeting the Major Sperm Protein Gene That May Be Useful in the Molecular Identification of Nematodes

Discrimination of closely related nematode species is typically problematic when traditional identification characteristics are prone to intraspecific variation. In this study, a molecular approach that can distinguish Pratylenchus penetrans and P. scribneri is described. The approach uses universal primers in conjunction with polymerase chain reaction (PCR) to amplify equivalent fragments of the major sperm protein (msp) gene from any nematode. This gene fragment typically includes an intron of variable sequence. The presence of this highly variable segment in an otherwise conserved gene sequence allows P. penetrans and P. scribneri to be distinguished by either a species-specific amplification or by dot-blot hybridization. The approach is potentially of general utility in species-specific identification of nematodes.     

Immunisation against a serine protease inhibitor reduces intensity of Plasmodium berghei infection in mosquitoes

The mosquito innate immune response is able to clear the majority of Plasmodium parasites. This immune clearance is controlled by a number of regulatory molecules including serine protease inhibitors (serpins). To determine whether such molecules could represent a novel target for a malaria transmission-blocking vaccine, we vaccinated mice with Anopheles gambiae serpin-2. Antibodies against Anopheles gambiae serpin-2 significantly reduced the infection of a heterologous Anopheles species (Anopheles stephensi) by Plasmodium berghei, however this effect was not observed with Plasmodium falciparum. Therefore, this approach of targeting regulatory molecules of the mosquito immune system may represent a novel approach to transmission-blocking malaria vaccines.     

PeanutDB: an integrated bioinformatics web portal for Arachis hypogaea transcriptomics

Background

Doubled haploid production is a key technology in triticale research and breeding. A critical component of this method depends on chromosome doubling, which is traditionally achieved by in vivo treatment of seedlings with colchicine.

Results

In this study we investigated the applicability of an in vitro approach for chromosome doubling based on microspore culture. Our results show a pronounced increase in the proportion of doubled haploid triticale plants compared to the spontaneous doubling rate, but also compared to the doubling obtained by the standard in vivo approach. In addition, the frequency of plants surviving from culture medium to maturity is also much higher for the in vitro approach. Colchicine concentrations of 1?mM for 24?h or 0.3?mM applied for 48 or 72?h during the first hours of microspore culture performed best.

Conclusions

Our results suggest that for triticale, in vitro chromosome doubling is a promising alternative to the in vivo approach.     

The Mouse MC13 Mutant Is a Novel ENU Mutation in Collagen Type II,Alpha 1

Phenotype-driven mutagenesis experiments are a powerful approach to identifying novel alleles in a variety of contexts. The traditional disadvantage of this approach has been the subsequent task of identifying the affected locus in the mutants of interest. Recent advances in bioinformatics and sequencing have reduced the burden of cloning these ENU mutants. Here we report our experience with an ENU mutagenesis experiment and the rapid identification of a mutation in a previously known gene. A combination of mapping the mutation with a high-density SNP panel and a candidate gene approach has identified a mutation in collagen type II, alpha I (Col2a1). Col2a1 has previously been studied in the mouse and our mutant phenotype closely resembles mutations made in the Col2a1 locus.     

Assessing Genome-Wide Statistical Significance for Large p Small n Problems

Assessing genome-wide statistical significance is an important issue in genetic studies. We describe a new resampling approach for determining the appropriate thresholds for statistical significance. Our simulation results demonstrate that the proposed approach accurately controls the genome-wide type I error rate even under the large p small n situations.     

A single anti-microRNA antisense oligodeoxyribonucleotide (AMO) targeting multiple microRNAs offers an improved approach for microRNA interference

Anti-miRNA antisense inhibitors (AMOs) have demonstrated their utility in miRNA research and potential in miRNA therapy. Here we report a modified AMO approach in which multiple antisense units are engineered into a single unit that is able to simultaneously silence multiple-target miRNAs, the multiple-target AMO or MTg-AMO. We validated the technique with two separate MTg-AMOs: anti-miR-21/anti-miR-155/anti-miR-17-5p and anti-miR-1/anti-miR-133. We first verified the ability of the MTg-AMOs to antagonize the repressive actions of their target miRNAs using luciferase reporter activity assays and to specifically knock down the levels of their target miRNAs using real-time RT-PCR methods. We then used the MTg-AMO approach to identify several tumor suppressors—TGFBI, APC and BCL2L11 as the target genes for oncogenic miR-21, miR-155 and miR-17-5p, respectively, and two cardiac ion channel genes HCN2 (encoding a subunit of cardiac pacemaker channel) and CACNA1C (encoding the α-subunit of cardiac L-type Ca²⁺ channel) for the muscle-specific miR-1 and miR-133. We further demonstrated that the MTg-AMO targeting miR-21, miR-155 and miR-17-5p produced a greater inhibitory effect on cancer cell growth, compared with the regular single-target AMOs. Moreover, while using the regular single-target AMOs excluded HCN2 as a target gene for either miR-1 or miR-133, the MTg-AMO approach is able to reveal HCN2 as the target for both miR-1 and miR-133. Our findings suggest the MTg-AMO as an improved approach for miRNA target finding and for studying function of miRNAs. This approach may find its broad application for exploring biological processes involving multiple miRNAs and multiple genes.     

Plotting receiver operating characteristic and precision–recall curves from presence and background data

1. The receiver operating characteristic (ROC) and precision–recall (PR) plots have been widely used to evaluate the performance of species distribution models. Plotting the ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting the ROC/PR curves from presence‐only data while treating background data as pseudo absence data (namely PO approach) may provide misleading results.
2. In this study, we propose a new approach to calibrate the ROC/PR curves from presence and background data with user‐provided information on a constant c, namely PB approach. Here, c defines the probability that species occurrence is detected (labeled), and an estimate of c can also be derived from the PB‐based ROC/PR plots given that a model with good ability of discrimination is available. We used five virtual species and a real aerial photography to test the effectiveness of the proposed PB‐based ROC/PR plots. Different models (or classifiers) were trained from presence and background data with various sample sizes. The ROC/PR curves plotted by PA approach were used to benchmark the curves plotted by PO and PB approaches.
3. Experimental results show that the curves and areas under curves by PB approach are more similar to that by PA approach as compared with PO approach. The PB‐based ROC/PR plots also provide highly accurate estimations of c in our experiment.
4. We conclude that the proposed PB‐based ROC/PR plots can provide valuable complements to the existing model assessment methods, and they also provide an additional way to estimate the constant c (or species prevalence) from presence and background data.

     

An Approach to Heterologous Expression of Membrane Proteins. The Case of Bacteriorhodopsin

Heterologous overexpression of functional membrane proteins is a major bottleneck of structural biology. Bacteriorhodopsin from Halobium salinarum (bR) is a striking example of the difficulties in membrane protein overexpression. We suggest a general approach with a finite number of steps which allows one to localize the underlying problem of poor expression of a membrane protein using bR as an example. Our approach is based on constructing chimeric proteins comprising parts of a protein of interest and complementary parts of a homologous protein demonstrating advantageous expression. This complementary protein approach allowed us to increase bR expression by two orders of magnitude through the introduction of two silent mutations into bR coding DNA. For the first time the high quality crystals of bR expressed in E. Coli were obtained using the produced protein. The crystals obtained with in meso nanovolume crystallization diffracted to 1.67 Å.     

Combining natural language processing and metabarcoding to reveal pathogen-environment associations

Cryptococcus neoformans is responsible for life-threatening infections that primarily affect immunocompromised individuals and has an estimated worldwide burden of 220,000 new cases each year—with 180,000 resulting deaths—mostly in sub-Saharan Africa. Surprisingly, little is known about the ecological niches occupied by C. neoformans in nature. To expand our understanding of the distribution and ecological associations of this pathogen we implement a Natural Language Processing approach to better describe the niche of C. neoformans. We use a Latent Dirichlet Allocation model to de novo topic model sets of metagenetic research articles written about varied subjects which either explicitly mention, inadvertently find, or fail to find C. neoformans. These articles are all linked to NCBI Sequence Read Archive datasets of 18S ribosomal RNA and/or Internal Transcribed Spacer gene-regions. The number of topics was determined based on the model coherence score, and articles were assigned to the created topics via a Machine Learning approach with a Random Forest algorithm. Our analysis provides support for a previously suggested linkage between C. neoformans and soils associated with decomposing wood. Our approach, using a search of single-locus metagenetic data, gathering papers connected to the datasets, de novo determination of topics, the number of topics, and assignment of articles to the topics, illustrates how such an analysis pipeline can harness large-scale datasets that are published/available but not necessarily fully analyzed, or whose metadata is not harmonized with other studies. Our approach can be applied to a variety of systems to assert potential evidence of environmental associations.     

Analyzing Multi-locus Plant Barcoding Datasets with a Composition Vector Method Based on Adjustable Weighted Distance

Background

The composition vector (CV) method has been proved to be a reliable and fast alignment-free method to analyze large COI barcoding data. In this study, we modify this method for analyzing multi-gene datasets for plant DNA barcoding. The modified method includes an adjustable-weighted algorithm for the vector distance according to the ratio in sequence length of the candidate genes for each pair of taxa.

Methodology/Principal Findings

Three datasets, matK+rbcL dataset with 2,083 sequences, matK+rbcL dataset with 397 sequences and matK+rbcL+trnH-psbA dataset with 397 sequences, were tested. We showed that the success rates of grouping sequences at the genus/species level based on this modified CV approach are always higher than those based on the traditional K2P/NJ method. For the matK+rbcL datasets, the modified CV approach outperformed the K2P-NJ approach by 7.9% in both the 2,083-sequence and 397-sequence datasets, and for the matK+rbcL+trnH-psbA dataset, the CV approach outperformed the traditional approach by 16.7%.

Conclusions

We conclude that the modified CV approach is an efficient method for analyzing large multi-gene datasets for plant DNA barcoding. Source code, implemented in C++ and supported on MS Windows, is freely available for download at http://math.xtu.edu.cn/myphp/math/research/source/Barcode_source_codes.zip.