Multiple types of data are required to identify the mechanisms influencing the spatial expansion of melanoma cell colonies

Background The expansion of cell colonies is driven by a delicate balance of several mechanisms including cell motility, cell-to-cell adhesion and cell proliferation. New approaches that can be used to independently identify and quantify the role of each mechanism will help us understand how each mechanism contributes to the expansion process. Standard mathematical modelling approaches to describe such cell colony expansion typically neglect cell-to-cell adhesion, despite the fact that cell-to-cell adhesion is thought to play an important role. Results We use a combined experimental and mathematical modelling approach to determine the cell diffusivity, D, cell-to-cell adhesion strength, q, and cell proliferation rate, ?, in an expanding colony of MM127 melanoma cells. Using a circular barrier assay, we extract several types of experimental data and use a mathematical model to independently estimate D, q and ?. In our first set of experiments, we suppress cell proliferation and analyse three different types of data to estimate D and q. We find that standard types of data, such as the area enclosed by the leading edge of the expanding colony and more detailed cell density profiles throughout the expanding colony, does not provide sufficient information to uniquely identify D and q. We find that additional data relating to the degree of cell-to-cell clustering is required to provide independent estimates of q, and in turn D. In our second set of experiments, where proliferation is not suppressed, we use data describing temporal changes in cell density to determine the cell proliferation rate. In summary, we find that our experiments are best described using the range D = 161 - 243 ?m2 hour-1, q = 0.3 - 0.5 (low to moderate strength) and ? = 0.0305 - 0.0398 hour-1, and with these parameters we can accurately predict the temporal variations in the spatial extent and cell density profile throughout the expanding melanoma cell colony. Conclusions Our systematic approach to identify the cell diffusivity, cell-to-cell adhesion strength and cell proliferation rate highlights the importance of integrating multiple types of data to accurately quantify the factors influencing the spatial expansion of melanoma cell colonies.

Data requirements of hedonic models in determining the impact of infrastructure charges on new housing costs

The use of hedonic models to estimate the effects of various factors on house prices is well established. This paper examines a number of international hedonic house price models that seek to quantify the effect of infrastructure charges on new house prices. This work is an important factor in the housing affordability debate, with many governments in high growth areas having user-pays infrastructure charging policies operating in tandem with housing affordability objectives, with no empirical evidence on the impact of one on the other. This research finds there is little consistency between existing models and the data sets utilised. Specification appears dependent upon data availability rather than sound theoretical grounding. This may lead to a lack of external validity with model specification dependent upon data availability rather than sound theoretical grounding.

Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

A data mining approach to improve the automated quality of data

This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

The Arabidopsis thaliana double-stranded RNA binding protein DRB1 directs guide strand selection from microRNA duplexes

In Arabidopsis thaliana (Arabidopsis), DICER-LIKE1 (DCL1) functions together with the double-stranded RNA binding protein (dsRBP), DRB1, to process microRNAs (miRNAs) from their precursor transcripts prior to their transfer to the RNA-induced silencing complex (RISC). miRNA-loaded RISC directs RNA silencing of cognate mRNAs via ARGONAUTE1 (AGO1)-catalyzed cleavage. Short interefering RNAs (siRNAs) are processed from viral-derived or transgene-encoded molecules of doublestranded RNA (dsRNA) by the DCL/dsRBP partnership, DCL4/DRB4, and are also loaded to AGO1-catalyzed RISC for cleavage of complementary mRNAs. Here, we use an artificial miRNA (amiRNA) technology, transiently expressed in Nicotiana benthamiana, to produce a series of amiRNA duplexes with differing intermolecular thermostabilities at the 5′ end of duplex strands. Analyses of amiRNA duplex strand accumulation and target transcript expression revealed that strand selection (amiRNA and amiRNA*) is directed by asymmetric thermostability of the duplex termini. The duplex strand possessing a lower 59 thermostability was preferentially retained by RISC to guide mRNA cleavage of the corresponding target transgene. In addition, analysis of endogenous miRNA duplex strand accumulation in Arabidopsis drb1 and drb2345 mutant plants revealed that DRB1 dictates strand selection, presumably by directional loading of the miRNA duplex onto RISC for passenger strand degradation. Bioinformatic and Northern blot analyses of DCL4/DRB4-dependent small RNAs (miRNAs and siRNAs) revealed that small RNAs produced by this DCL/dsRBP combination do not conform to the same terminal thermostability rules as those governing DCL1/DRB1-processed miRNAs. This suggests that small RNA processing in the DCL1/DRB1-directed miRNA and DCL4/DRB4-directed sRNA biogenesis pathways operates via different mechanisms.

Hairpin RNAs derived from RNA polymerase II and polymerase III promoter-directed transgenes are processed differently in plants

RNA polymerase III (Pol III) as well as Pol II (35S) promoters are able to drive hairpin RNA (hpRNA) expression and induce target gene silencing in plants. siRNAs of 21 nt are the predominant species in a 35S Pol II line, whereas 24- and/or 22-nucleotide (nt) siRNAs are produced by a Pol III line. The 35S line accumulated the loop of the hpRNA, in contrast to full-length hpRNA in the Pol III line. These suggest that Pol II and Pol III-transcribed hpRNAs are processed by different pathways. One Pol III transgene produced only 24-nt siRNAs but silenced the target gene efficiently, indicating that the 24-nt siRNAs can direct mRNA degradation; specific cleavage was confirmed by 59 rapid amplification of cDNA ends (RACE). Both Pol II- and Pol III-directed hpRNA transgenes induced cytosine methylation in the target DNA. The extent of methylation is not correlated with the level of 21-nt siRNAs, suggesting that they are not effective inducers of DNA methylation. The promoter of a U6 transgene was significantly methylated, whereas the promoter of the endogenous U6 gene was almost free of cytosine methylation, suggesting that endogenous sequences are more resistant to de novo DNA methylation than are transgene constructs. Published by Cold Spring Harbor Laboratory Press. Copyright © 2008 RNA Society.

RNA interference-inducing hairpin RNAs in plants act through the viral defence pathway

RNA interference (RNAi) is widely used to silence genes in plants and animals. It operates through the degradation of target mRNA by endonuclease complexes guided by approximately 21 nucleotide (nt) short interfering RNAs (siRNAs). A similar process regulates the expression of some developmental genes through approximately 21 nt microRNAs. Plants have four types of Dicer-like (DCL) enzyme, each producing small RNAs with different functions. Here, we show that DCL2, DCL3 and DCL4 in Arabidopsis process both replicating viral RNAs and RNAi-inducing hairpin RNAs (hpRNAs) into 22-, 24- and 21 nt siRNAs, respectively, and that loss of both DCL2 and DCL4 activities is required to negate RNAi and to release the plant's repression of viral replication. We also show that hpRNAs, similar to viral infection, can engender long-distance silencing signals and that hpRNA-induced silencing is suppressed by the expression of a virus-derived suppressor protein. These findings indicate that hpRNA-mediated RNAi in plants operates through the viral defence pathway.

RNA silencing in plants: Yesterday, today, and tomorrow

RNA silencing has become a major focus of molecular biology and biomedical research around the world. This is highlighted by a simple PubMed search for “RNA silencing,” which retrieves almost 9,000 articles. Interest in gene silencing-related mechanisms stemmed from the early 1990s, when this phenomenon was first noted as a surprise observation by plant scientists during the course of plant transformation experiments, in which the introduction of a transgene into the genome led to the silencing of both the transgene and homologous endogenes. From these initial studies, plant biologists have continued to generate a wealth of information into not only gene silencing mechanisms but also the complexity of these biological pathways as well as revealing their multilevel interactions with one another. The plant biology community has also made significant advancements in exploiting RNA silencing as a powerful tool for gene function studies and crop improvements. In this article, we (1) review the rich history of gene silencing research and the knowledge it has generated into our understanding of this fundamental mechanism of gene regulation in plants; (2) describe examples of the current applications of RNA silencing in crop plants; and (3) discuss improvements in RNA silencing technology and its potential application in plant science.

The RNA world in plants: Post-transcriptional control III

Post-transcriptional control of gene expression has gone from a curiosity involving a few special genes to a highly diverse and widespread set of processes that is truly pervasive in plant gene expression. Thus, Plant Cell readers interested in almost any aspect of plant gene expression in response to any environmental influence, or in development, are advised to read on. In May 2001, what has become the de facto third biennial Symposium on Post-Transcriptional Control of Gene Expression in Plants was held in Ames, Iowa. The meeting was hosted by the new Plant Sciences Institute of Iowa State University with additional funding from the National Science Foundation and the United States Department of Agriculture. In 1997, the annual University of California-Riverside Plant Physiology Symposium was devoted to this topic. This provided a wake-up call to the plant world, summarized in this journal (Gallie and Bailey-Serres, 1997), that not all gene expression is controlled at the level of transcription. This was expanded upon at a European Molecular Biology Organization Workshop in Leysin, Switzerland, in 1999 (Bailey-Serres et al., 1999). The 3-day meeting in Ames brought together a strong and diverse contingent of plant biologists from four continents. The participants represented an unusually heterogeneous group of disciplines ranging from virology to stress response to computational biology. The research approaches and techniques represented were similarly diverse. Here we discuss a sample of the many fascinating aspects of post-transcriptional control that were presented at this meeting; we apologize to those whose work is not described here.

Exploring plant genomes by RNA-induced gene silencing

The nucleotide sequences of several animal, plant and bacterial genomes are now known, but the functions of many of the proteins that they are predicted to encode remain unclear. RNA interference is a gene-silencing technology that is being used successfully to investigate gene function in several organisms - for example, Caenorhabditis elegans. We discuss here that RNA-induced gene silencing approaches are also likely to be effective for investigating plant gene function in a high-throughput, genome-wide manner.

Small RNA viruses of insects : expression in plants and RNA silencing

Interest in insect small RNA viruses (SRVs) has grown slowly but steadily. A number of new viruses have been analyzed at the sequence level, adding to our knowledge of their diversity at the level of both individual virus species and families. In particular, a number of possible new virus families have emerged. This research has largely been driven by interest in their potential for pest control, as well as in their importance as the causal agents of disease in beneficial arthropods. At the same time, research into known viruses has made valuable contributions to our understanding of an emerging new field of central importance to molecular biology-the existence of RNA-based gene silencing, developmental control, and adaptive immune systems in eukaryotes. Subject to RNA-based adaptive immune responses in their hosts, viruses have evolved a variety of genes encoding proteins capable of suppressing the immune response. Such genes were first identified in plant viruses, but the first examples known from animal viruses were identified in insect RNA viruses. This chapter will address the diversity of insect SRVs, and attempts to harness their simplicity in the engineering of transgenic plants expressing viruses for resistance to insect pests. We also describe RNA interference and antiviral pathways identified in plants and animals, how they have led viruses to evolve genes capable of suppressing such adaptive immunity, and the problems presented by these pathways for the strategy of expressing viruses in transgenic plants. Approaches for countering these problems are also discussed. © 2006 Elsevier Inc. All rights reserved.

Constructs and methods for hairpin RNA-mediated gene silencing in plants

Double-stranded RNA (dsRNA) induces an endogenous sequence-specific RNA degradation mechanism in most eukaryotic cells. The mechanism can be harnessed to silence genes in plants by expressing self-complementary single-stranded (hairpin) RNA in which the duplexed region has the same sequence as part of the target gene's mRNA. We describe a number of plasmid vectors for generating hairpin RNAs, including those designed for high-throughput cloning, and provide protocols for their use.