Author Archive

NDRG4 – a potential target for cancer therapies

A gene which is overexpressed in malignant brain tumours could provide a solution to controlling the spread of the disease.

NDRG4 meningiomasThe paper, from Rama Kotipatruni and colleagues from St Louis, USA, build on previous work showing that the gene NDRG4 is overexpressed in aggressive meningioma cells. NDRG4 is an intracellular protein which is regulated by the transcription factor n-Myc. Reducing the levels of NDRG4 mRNA or protein in meningioma cell lines increased cell mortality and decreased migration. The group also use a variety of methods, including lentiviral modification of cells and 3D cellular assays to determine the effects of NDRG4 downregulation on a range of phenotypic traits, including angiogenesis and wound healing.

This is an exciting article which could trigger research into potential drugs that could bring NDRG4 expression under control and tame aggressive tumours. It’s free to access* on our site for the next four weeks, so why not download the paper here:

NDRG4, the N-Myc downstream regulated gene, is important for cell survival, tumor invasion and angiogenesis in meningiomas
Rama P. Kotipatruni, Daniel J. Ferraro, Xuan Ren, Robert P. Vanderwaal, Dinesh K. Thotala, Dennis E. Hallahan and Jerry J. Jaboin
DOI: 10.1039/C2IB20168B

*Free access is provided to subscribing institutions or through an RSC Publishing Personal Account. Registration is quick and easy at http://pubs.rsc.org/en/account/register.

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Building proteins brick by brick

In situ click chemistry: from small molecule discovery to synthetic antibodiesScientists have become adept at synthesising novel nucleotide sequences from scratch, but our comparative lack of understanding of how proteins are built has hampered development of new proteins to use in the lab or as a therapy. Novel peptides have to be designed via a screening process rather than de novo synthesis and proteins which are produced in vivo, such as antibodies, can suffer from batch variation.

In this review, Steven Millward and colleagues from California and Singapore explore how the screening technology Iterative Peptide In Situ Click Chemistry (IPISC) could not only allow for greater control over the peptide synthesis process, but also increase the range and complexity of molecules we are able to produce.

The stepwise building method used in IPISC means that amino acids with particular properties, such as increased stability, can to added at the beginning of the process. This method also used target proteins as the scaffold on which to built, ensuring the the synthesised protein can bind effectively with its intended target. IPISC is also relatively easy to scale up from screening to full production when a suitable protein is identified.

This review doesn’t just cover the advantages of IPISC, but also discusses effective ways to analyse the results of a screen and areas where the method could be optimised further. To find out more, download the review here – it’s free for the next four weeks.

In situ click chemistry: from small molecule discovery to synthetic antibodies
Steven W. Millward, Heather D. Agnew, Bert Lai, Su Seong Lee, Jaehong Lim, Arundhati Nag, Suresh Pitram, Rosemary Rohde and James R. Heath
DOI: 10.1039/C2IB20110K

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Cutting off the power of tumours

Cancer develops, progresses and responds to therapies through restricted perturbation of the protein–protein interaction network A new model for analysing the effects of cancer at a systems level has drawn inspiration from an unlikely source – electricity grids.

By using concepts from power networks such as cascading failures, Jordi Serra-Musach and colleagues from both Spain and the UK built a model to show how protein-protein interactions in a cell are affected by oncogenic mutations and changes in protein expression. Far from having random effects, the group show that cancer-causing changes in the interactome show up as specific topological features within the model. The model has also shown itself to be robust when interrogated with data from cancer progression and treatment studies.

This paper is a good example of how integrative approaches are key to understanding more about cancer and how we can tackle it. It’s free for the next four weeks (following a simple registration), so why not take a look at it here:

Cancer develops, progresses and responds to therapies through restricted perturbation of the protein–protein interaction network
Jordi Serra-Musach, Helena Aguilar, Francesco Iorio, Francesc Comellas, Antoni Berenguer, Joan Brunet, Julio Saez-Rodriguez and Miguel Angel Pujana
DOI: 10.1039/C2IB20052J

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Focussing on single islets in type 2 diabetes

Quantitative imaging of electron transfer flavoprotein autofluorescence reveals the dynamics of lipid partitioning in living pancreatic islets A new microscopy technique developed by Alan Lam and colleagues from Toronto could help to reveal more about how pancreatic cells change at the onset of Type 2 diabetes.

It is estimated that around 6 % of the world’s population have Type 2 diabetes, which can be caused by obesity and lack of exercise. β-cells in a diabetic pancreas produce decreased amounts of insulin and are dysfunctional. It is thought that metabolism of glucose and fatty acid could play a role in this dysfunction, but their exact contribution to the pathology is yet to be elucidated.

To start to discover the mechanisms behind this, the authors use microfluidics to isolate single pancreatic islets then use confocal microscopy to look at autofluorescence of the protein flavin as an indication of electron transport chain activity. They then use this setup to characterise redox responses in the islets to fatty acid and glucose metabolism. This work could lead to a deeper understanding of the pathology of diabetes, giving us a better grounding on which to develop more effective treatments and cures.

To find out more about this interesting combination of modern technologies, download the paper here and look out for it in Issue 8!

Quantitative imaging of electron transfer flavoprotein autofluorescence reveals the dynamics of lipid partitioning in living pancreatic islets
Alan K. Lam,  Pamuditha N. Silva,  Svetlana M. Altamentova and Jonathan V. Rocheleau
DOI: 10.1039/C2IB20075A

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Review: Regucalcin in brain calcium signalling and ageing

Incidences of brain illnesses such as Alzheimer’s and Parkinson’s disease are steadily increasing as the population ages. Calcium signalling in the brain is thought to be implicated in the onset of this diseases but the exact relationship between the two remains unknown.

This review by Masayoshi Yamaguchi from the University of Georgia discusses the role of the protein regucalcin, a calcium-binding protein involved in calcium signalling and its expression in the brain, which is known to decrease with age. This could represent part of a possible mechanism of how calcium levels in the brain alter over time. The paper looks at the effects of ageing on calcium signalling and what kind of role regucalcin could play as part of this as well as regucalcin’s role in calcium homeostasis.

Regucalcin has already been implicated in Alzheimer’s and Parkinson’s disease and could also be involved in a number of X-linked mental retardation conditions. This review is a good primer for anyone seeking to learn more about the role of calcium in both healthy and disease brain tissue.

Role of regucalcin in brain calcium signaling: involvement in ageing
Masayoshi Yamaguchi
DOI: 10.1039/C2IB20042B

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Genetically modified tobacco plants resist aphid attack

The issue of genetically modified plants has been widely discussed in the media in the last few months, focussing on experiments on aphid-resistant wheat. Now a group from the Research and Development Center of Plant Resources in Shanghai have produced aphid-resistant tobacco plants by genetic modification.

Guoyin Kai and colleagues inserted an agglutinin cDNA from the creeping vine Monstera deliciosa into the tobacco plant genome. Agglutinins can be toxic, helping to defend the plant from potential attack. After confirming that the transgene was indeed expressed in the plants, the group challenged the plants with peach-potato aphids. The modified plants not only reduced adult aphid numbers over the course of 10 days, they also reduced insect fecundity.

This is the first time that a gene from Monstera deliciosa has been used to produce modified plants. It could be a future source of genes that might help us in our challenge to feed the world’s growing population. To find out more, download the article here – it’s free for the next four weeks.

Expression of Monstera deliciosa agglutinin gene (mda) in tobacco confers resistance to peach-potato aphids
Guoyin Kai,  Qian Ji,  Yang Lu,  Zhongying Qian and Lijie Cui
DOI: 10.1039/C2IB20038D

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An integrative approach to cell binding

Selectin-mediated adhesion in shear flow using micropatterned substrates: multiple-bond interactions govern the critical length for cell bindingCell adhesion has wide-reaching effects on many biological processes and a greater understanding of the molecular mechanisms behind it could lead to the development of therapies to regulate cell binding (e.g. in metastatic tumours). Microfluidic devices are becoming an increasingly popular way to study adhesion at the single-cell level (a previous example about its use in studying chemotaxis can be found here).

ZiQiu Tong and colleagues from Baltimore and Philadelphia have improved upon previous microfluidic set-ups to produce a device that can monitor single cells binding to a substrate under shear stress, mimicking conditions experienced by cells in the blood vessels. The data collected from the microfluidic experiments were then analysed using a mathematical model based on engineering concepts.

They find that a number of different parameters, from the size of the substrate patch and the density of substrate molecules on it, to the number of bonds formed between the cell and its substrate, can alter the time it takes for the cell to bind. These results have implications in areas as diverse as future therapeutics and biosensor design. To take a look at their work, download the article here - as always, access is free for the next four weeks.

Selectin-mediated adhesion in shear flow using micropatterned substrates: multiple-bond interactions govern the critical length for cell binding
ZiQiu Tong, Luthur Siu-Lun Cheung, Kathleen J. Stebe and Konstantinos Konstantopoulos
DOI: 10.1039/C2IB20036H

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Stopping T cells in their tracks

When a pathogen infects your body, the T cells at the site of infection are a vital part of your immune response. However, in order to complete this function the T cells need to stop at the infection site, resisting the blood flow. It’s known that a T cell’s ability to stop in the blood vessels is controlled by diacylglycerol kinases (DGKs). These are known to activate guanine nucleotide exchange factors (GEFs) and Ras proximity 1 (Rap1) molecules, which in turn activate integrin lymphocyte function associated antigen-1 (LFA-1).

Now, Dooyoung Lee and colleagues from the University of Pennsylvania have determined how the level of DKGs regulate T cell arrest in vessels. Using flow chamber assays and in silico models, they show that loss of DGKs actually increases a T cell’s ability to stop in vessels, possibly due to an increase in in LFA-1 binding affinity. Future experiments should deduce the exact effects of DGK deficiency on T cell arrest.

This article is a good example of how well experimental work and computer models can be integrated to solve biological questions. It’s also free* for the next four weeks:

Diacylglycerol kinase zeta negatively regulates CXCR4-stimulated T lymphocyte firm arrest to ICAM-1 under shear flow
Dooyoung Lee, Jiyeon Kim, Michael T. Beste, Gary A. Koretzky and Daniel A. Hammer
DOI: 10.1039/C2IB00002D

* following a simple registration for individual users

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Analysis of high-throughput datasets; is newer always better?

High throughput analysisHigh-throughput experiments have exploded in popularity over the last few years (a few examples from our own archives can found here and here). Scientists all over the world now have online access to a wealth of data, which can be used to create models and help solve important biological questions. One of the most powerful ways to produce such a model is to use Probabilistic Functional Integrated Networks (PFINs), which integrate data by comparing separate datasets to a “Gold Standard” dataset. Integration of this assessed data creates a network, which can then be used to predict the behaviour of a system. But are these models as accurate as they could be?

Katherine James and colleagues from Newcastle University argue that the current mindset among researchers that ‘newer data is better’ needs to change. Focusing on protein interaction data in the yeast Saccharomyces cerevisiae, they analysed the changes in four widely-used online databases (BioGRID, KEGG, GO and SGD) and observed how these changes affect models produced using PFINs. They found that updating the datasets used in a PFIN every month didn’t increase the accuracy on the resulting model and that careful selection of both datasets and Gold Standard is a better guarantee of an accurate model than just using the most recent data available.

To find out more about the team’s analysis, download the paper here – it’s free* for the next four weeks:

Is newer better?—evaluating the effects of data curation on integrated analyses in Saccharomyces cerevisiae
Katherine James, Anil Wipat and Jennifer Hallinan
DOI: 10.1039/C2IB00123C

* following a simple registration for individual users

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Modeling of in vitro cell-free translation

Experiment and mathematical modeling of gene expression dynamics in a cell-free systemIn vitro protein translation is central to synthetic biology and high-throughput screening. Before using cell-free systems, the final yield of synthesised protein has to be calculated.

Tobias Stoegbauer and colleagues from Ludwig-Maximilians University in Munich have devised a minimal mathematical model which can be used, not only to predict final yields, but also to optimise and calibrate experiments. The team uses a simple GFP transcription and translation system to test out their model and found that the model not only predicts how protein yield will be affected by the amount of template DNA put into the system, but also when various reaction components would need to be replaced.

This is an effective model of use to anyone who uses cell-free protein production systems. The article is available for free download here for the next four weeks, so why not take a look:

Experiment and mathematical modeling of gene expression dynamics in a cell-free system
Tobias Stögbauer, Lukas Windhager, Ralf Zimmer and Joachim O. Rädler
DOI: 10.1039/C2IB00102K

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