Translation initiation region sequence preferences in <Emphasis Type="Italic">Escherichia coli</Emphasis>

Background  

The mRNA translation initiation region (TIR) comprises the initiator codon, Shine-Dalgarno (SD) sequence and translational enhancers. Probably the most abundant class of enhancers contains A/U-rich sequences. We have tested the influence of SD sequence length and the presence of enhancers on the efficiency of translation initiation.     

A computational survey of candidate exonic splicing enhancer motifs in the model plant <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>

Background  

Algorithmic approaches to splice site prediction have relied mainly on the consensus patterns found at the boundaries between protein coding and non-coding regions. However exonic splicing enhancers have been shown to enhance the utilization of nearby splice sites.     

Prediction of regulatory elements in mammalian genomes using chromatin signatures

Background  

Recent genomic scale survey of epigenetic states in the mammalian genomes has shown that promoters and enhancers are correlated with distinct chromatin signatures, providing a pragmatic way for systematic mapping of these regulatory elements in the genome. With rapid accumulation of chromatin modification profiles in the genome of various organisms and cell types, this chromatin based approach promises to uncover many new regulatory elements, but computational methods to effectively extract information from these datasets are still limited.     

Antimalarial activity of the anticancer and proteasome inhibitor bortezomib and its analog ZL<Subscript>3</Subscript>B

Background  

The high rate of mortality due to malaria and the worldwide distribution of parasite resistance to the commonly used antimalarial drugs chloroquine and pyrimethamine emphasize the urgent need for the development of new antimalarial drugs. An alternative approach to the long and uncertain process of designing and developing new compounds is to identify among the armamentarium of drugs already approved for clinical treatment of various human diseases those that may have strong antimalarial activity.     

Enhancement of solubility in <Emphasis Type="Italic">Escherichia coli</Emphasis> and purification of an aminotransferase from <Emphasis Type="Italic">Sphingopyxis</Emphasis> sp. MTA144 for deamination of hydrolyzed fumonisin B<Subscript>1</Subscript>

Background  

Fumonisin B₁ is a cancerogenic mycotoxin produced by Fusarium verticillioides and other fungi. Sphingopyxis sp. MTA144 can degrade fumonisin B₁, and a key enzyme in the catabolic pathway is an aminotransferase which removes the C2-amino group from hydrolyzed fumonisin B₁. In order to study this aminotransferase with respect to a possible future application in enzymatic fumonisin detoxification, we attempted expression of the corresponding fumI gene in E. coli and purification of the enzyme. Since the aminotransferase initially accumulated in inclusion bodies, we compared the effects of induction level, host strain, expression temperature, solubility enhancers and a fusion partner on enzyme solubility and activity.     

<Emphasis Type="Italic">Bacillus pumilus</Emphasis>laccase: a heat stable enzyme with a wide substrate spectrum

Background  

Laccases are multi-copper oxidases that catalyze the one electron oxidation of a broad range of compounds. Laccase substrates include substituted phenols, arylamines and aromatic thiols. Such compounds are activated by the enzyme to the corresponding radicals. Owing to their broad substrate range laccases are considered to be versatile biocatalysts which are capable of oxidizing natural and non-natural industrial compounds, with water as sole by-product.     

Release of volatile organic compounds (VOCs) from the lung cancer cell line CALU-1 <Emphasis Type="Italic">in vitro</Emphasis>

Background  

The aim of this work was to confirm the existence of volatile organic compounds (VOCs) specifically released or consumed by lung cancer cells.     

Sodium butyrate enhances the cytotoxic effect of cisplatin by abrogating the cisplatin imposed cell cycle arrest

Background  

Histone deacetylase inhibitors have been proposed as potential enhancers of the cytotoxic effect of cisplatin and other anticancer drugs. Their application would permit the use of lower therapeutic doses and reduction of the adverse side effects of the drugs. However, the molecular mechanisms by which they sensitize the cells towards anticancer drugs are not known in details, which is an obstacle in developing effective therapeutic protocols.     

Sulphur metabolism and cellulase gene expression are connected processes in the filamentous fungus <Emphasis Type="Italic">Hypocrea jecorina</Emphasis> (anamorph <Emphasis Type="Italic">Trichoderma reesei</Emphasis>)

Background  

Sulphur compounds like cysteine, methionine and S-adenosylmethionine are essential for the viability of most cells. Thus many organisms have developed a complex regulatory circuit that governs the expression of enzymes involved in sulphur assimilation and metabolism. In the filamentous fungus Hypocrea jecorina (anamorph Trichoderma reesei) little is known about the participants in this circuit.     

Predicting enhancers with deep convolutional neural networks

Background

With the rapid development of deep sequencing techniques in the recent years, enhancers have been systematically identified in such projects as FANTOM and ENCODE, forming genome-wide landscapes in a series of human cell lines. Nevertheless, experimental approaches are still costly and time consuming for large scale identification of enhancers across a variety of tissues under different disease status, making computational identification of enhancers indispensable.

Results

To facilitate the identification of enhancers, we propose a computational framework, named DeepEnhancer, to distinguish enhancers from background genomic sequences. Our method purely relies on DNA sequences to predict enhancers in an end-to-end manner by using a deep convolutional neural network (CNN). We train our deep learning model on permissive enhancers and then adopt a transfer learning strategy to fine-tune the model on enhancers specific to a cell line. Results demonstrate the effectiveness and efficiency of our method in the classification of enhancers against random sequences, exhibiting advantages of deep learning over traditional sequence-based classifiers. We then construct a variety of neural networks with different architectures and show the usefulness of such techniques as max-pooling and batch normalization in our method. To gain the interpretability of our approach, we further visualize convolutional kernels as sequence logos and successfully identify similar motifs in the JASPAR database.

Conclusions

DeepEnhancer enables the identification of novel enhancers using only DNA sequences via a highly accurate deep learning model. The proposed computational framework can also be applied to similar problems, thereby prompting the use of machine learning methods in life sciences.

     

Analysis of outer membrane vesicle associated proteins isolated from the plant pathogenic bacterium <Emphasis Type="Italic">Xanthomonas campestris</Emphasis> pv. campestris

Background  

Outer membrane vesicles (OMVs) are released from the outer membrane of many Gram-negative bacteria. These extracellular compartments are known to transport compounds involved in cell-cell signalling as well as virulence associated proteins, e.g. the cytolysine from enterotoxic E. coli.     

Temporal and spatial control of transgene expression using laser induction of the hsp70 promoter

Background  

Precise temporal and spatial regulation of transgene expression is a critical tool to investigate gene function in developing organisms. The most commonly used technique to achieve tight control of transgene expression, however, requires the use of specific DNA enhancers that are difficult to characterize in non-model organisms. Here, we sought to eliminate the need for this type of sequence-based gene regulation and to open the field of functional genetics to a broader range of organisms.     

Can cognitive enhancers reduce the risk of falls in older people with Mild Cognitive Impairment? A protocol for a randomised controlled double blind trial

Background  

Older adults with cognitive problems have a higher risk of falls, at least twice that of cognitively normal older adults. The consequences of falls in this population are very serious: fallers with cognitive problems suffer more injuries due to falls and are approximately five times more likely to be admitted to institutional care. Although the mechanisms of increased fall risk in cognitively impaired people are not completely understood, it is known that impaired cognitive abilities can reduce attentional resource allocation while walking. Since cognitive enhancers, such as cholinesterase inhibitors, improve attention and executive function, we hypothesise that cognitive enhancers may reduce fall risk in elderly people in the early stages of cognitive decline by improving their gait and balance performance due to an enhancement in attention and executive function.     

Genomic features defining exonic variants that modulate splicing

Background  

Single point mutations at both synonymous and non-synonymous positions within exons can have severe effects on gene function through disruption of splicing. Predicting these mutations in silico purely from the genomic sequence is difficult due to an incomplete understanding of the multiple factors that may be responsible. In addition, little is known about which computational prediction approaches, such as those involving exonic splicing enhancers and exonic splicing silencers, are most informative.