A meshfree model for plant tissue deformations during drying

Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.

Role of intratumoural heterogeneity in cancer drug resistance : molecular and clinical perspectives

Drug resistance continues to be a major barrier to the delivery of curative therapies in cancer. Historically, drug resistance has been associated with over-expression of drug transporters, changes in drug kinetics or amplification of drug targets. However, the emergence of resistance in patients treated with new-targeted therapies has provided new insight into the complexities underlying cancer drug resistance. Recent data now implicate intratumoural heterogeneity as a major driver of drug resistance. Single cell sequencing studies that identified multiple genetically distinct variants within human tumours clearly demonstrate the heterogeneous nature of human tumours. The major contributors to intratumoural heterogeneity are (i) genetic variation, (ii) stochastic processes, (iii) the microenvironment and (iv) cell and tissue plasticity. Each of these factors impacts on drug sensitivity. To deliver curative therapies to patients, modification of current therapeutic strategies to include methods that estimate intratumoural heterogeneity and plasticity will be essential.

Reduced excision repair cross-complementing 1 expression associates with enhanced papilloma formation and fibroblast transformation after genetic disruption of secreted protein acidic and rich in cysteine

SPARC (secreted protein acidic and rich in cysteine)/ osteonectin/BM-40 is a matricellular protein implicated in development, cell transformation and tumorigenesis. We have examined the role of SPARC in cell transformation induced chemically with 7,12-dimethylbenz[a]anthracene (DMBA) and 12- tetradecanoylphorbol-13-acetate (TPA) in embryonic fibroblasts and in the skin of mice. Embryonic fibroblasts from SPARCnull mice showed increases in cell proliferation, enhanced sensitivity to DMBA and a higher number of DMBA/TPA-induced transformation foci. The number of DMBA-DNA adducts was 9 times higher in SPARCnull fibroblasts and their stability was lower than wild-type fibroblasts, consistent with a reduction in excision repair cross-complementing 1 the nucleotide excision repair enzyme in these cells. The SPARCnull mice showed an increase in both the speed and number of papillomas forming after topical administration of DMBA/TPA to the skin. These papillomas showed reduced growth and reduced progression to a more malignant phenotype, indicating that the effect of SPARC on tumorigenesis depends upon the transformation stage and/or tissue context. These data reinforce a growing number of observations in which SPARC has shown opposite effects on different tumor types/stages.

Herbivores and nutrients control grassland plant diversity via light limitation

Human alterations to nutrient cycles1, 2 and herbivore communities3, 4, 5, 6, 7 are affecting global biodiversity dramatically2. Ecological theory predicts these changes should be strongly counteractive: nutrient addition drives plant species loss through intensified competition for light, whereas herbivores prevent competitive exclusion by increasing ground-level light, particularly in productive systems8, 9. Here we use experimental data spanning a globally relevant range of conditions to test the hypothesis that herbaceous plant species losses caused by eutrophication may be offset by increased light availability due to herbivory. This experiment, replicated in 40 grasslands on 6 continents, demonstrates that nutrients and herbivores can serve as counteracting forces to control local plant diversity through light limitation, independent of site productivity, soil nitrogen, herbivore type and climate. Nutrient addition consistently reduced local diversity through light limitation, and herbivory rescued diversity at sites where it alleviated light limitation. Thus, species loss from anthropogenic eutrophication can be ameliorated in grasslands where herbivory increases ground-level light.

ST7-mediated suppression of tumorigenicity of prostate cancer cells is characterized by remodeling of the extracellular matrix

Multiple lines of evidence have provided compelling evidence for the existence of a tumor suppressor gene (TSG) on chromosome 7q31.1. ST7 may be the target of this genetic instability but its designation as a TSG is controversial. In this study, we show that, functionally, ST7 behaves as a tumor suppressor in human cancer. ST7 suppressed growth of PC-3 prostate cancer cells inoculated subcutaneously into severe combined immunodeficient mice, and increased the latency of tumor detection from 13 days in control tumors to 23 days. Re-expression of ST7 was also associated with suppression of colony formation under anchorage-independent conditions in MDA-MB-231 breast cancer cells and ST7 mRNA expression was downregulated in 44% of primary breast cancers. Expression profiling of PC-3 cells revealed that ST7 predominantly induces changes in genes involved in re-modeling the extracellular matrix such as SPARC, IGFBP5 and several matrix metalloproteinases. These data indicate that ST7 may mediate tumor suppression through modification of the tumor microenvironment.

When supply does not meet demand-ER stress and plant programmed cell death

The endoplasmic reticulum (ER) is the central organelle in the eukaryotic secretory pathway. The ER functions in protein synthesis and maturation and is crucial for proper maintenance of cellular homeostasis and adaptation to adverse environments. Acting as a cellular sentinel, the ER is exquisitely sensitive to changing environments principally via the ER quality control machinery. When perturbed, ER-stress triggers a tightly regulated and highly conserved, signal transduction pathway known as the unfolded protein response (UPR) that prevents the dangerous accumulation of unfolded/misfolded proteins. In situations where excessive UPR activity surpasses threshold levels, cells deteriorate and eventually trigger programmed cell death (PCD) as a way for the organism to cope with dysfunctional or toxic signals. The programmed cell death that results from excessive ER stress in mammalian systems contributes to several important diseases including hypoxia, neurodegeneration, and diabetes. Importantly, hallmark features and markers of cell death that are associated with ER stress in mammals are also found in plants. In particular, there is a common, conserved set of chaperones that modulate ER cell death signaling. Here we review the elements of plant cell death responses to ER stress and note that an increasing number of plant-pathogen interactions are being identified in which the host ER is targeted by plant pathogens to establish compatibility.

Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis

For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

The analysis of large scale data taken from the world groundnut (Arachis hypogaea L.) germplasm collection. II. Two-way data with mixed data types

As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.

Patterns of diversity in fatty acid composition in the Australian groundnut germplasm collection

Knowledge of the amounts and types of fatty acids in groundnut oil is beneficial, particularly from a nutritional standpoint. Germplasm evaluation data for fatty acid composition on 819 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for eight quantitative fatty acid descriptors have been documented. Statistical assessment, via methods of pattern analysis, summarised and described the patterns of variation in fatty acid composition of the groundnut accessions in the Australian germplasm collection. Presentation of the results from principal components analysis and hierarchical cluster analysis using a biplot was shown to be a very useful interpretative tool. Such a biplot enables a simultaneous examination of the relationships among all the accessions and the fatty acids. Unlike that information available via database searches, the results from contribution analysis together with the biplot provide a global picture of the diversity available for use in plant breeding programs. The use of standardised data for eight fatty acids, compared to using three specific fatty acids, provided a better description of the total diversity available because it remains relevant with possible changes in the nutritional preferences for fatty acids. Fatty acid composition was found to vary in relation to the branching pattern of the accessions. This pattern is generally indicative of the botanical types of groundnuts; Virginia (alternate) compared to Spanish and Valencia (sequential) botanical types.

Mixed data types and the use of pattern analysis on the Australian groundnut germplasm data

Data in germplasm collections contain a mixture of data types; binary, multistate and quantitative. Given the multivariate nature of these data, the pattern analysis methods of classification and ordination have been identified as suitable techniques for statistically evaluating the available diversity. The proximity (or resemblance) measure, which is in part the basis of the complementary nature of classification and ordination techniques, is often specific to particular data types. The use of a combined resemblance matrix has an advantage over data type specific proximity measures. This measure accommodates the different data types without manipulating them to be of a specific type. Descriptors are partitioned into their data types and an appropriate proximity measure is used on each. The separate proximity matrices, after range standardisation, are added as a weighted average and the combined resemblance matrix is then used for classification and ordination. Germplasm evaluation data for 831 accessions of groundnut (Arachis hypogaea L.) from the Australian Tropical Field Crops Genetic Resource Centre, Biloela, Queensland were examined. Data for four binary, five ordered multistate and seven quantitative descriptors have been documented. The interpretative value of different weightings - equal and unequal weighting of data types to obtain a combined resemblance matrix - was investigated by using principal co-ordinate analysis (ordination) and hierarchical cluster analysis. Equal weighting of data types was found to be more valuable for these data as the results provided a greater insight into the patterns of variability available in the Australian groundnut germplasm collection. The complementary nature of pattern analysis techniques enables plant breeders to identify relevant accessions in relation to the descriptors which distinguish amongst them. This additional information may provide plant breeders with a more defined entry point into the germplasm collection for identifying sources of variability for their plant improvement program, thus improving the utilisation of germplasm resources.

Managed livestock grazing is compatible with the maintenance of plant diversity in semidesert grasslands

Even when no baseline data are available, the impacts of 150 years of livestock grazing on natural grasslands can be assessed using a combined approach of grazing manipulation and regional-scale assessment of the flora. Here, we demonstrate the efficacy of this method across 18 sites in the semidesert Mitchell grasslands of northeastern Australia. Fifteen-year-old exclosures (ungrazed and macropod grazed) revealed that the dominant perennial grasses in the genus Astrebla do not respond negatively to grazing disturbance typical of commercial pastoralism. Neutral, positive, intermediate, and negative responses to grazing disturbance were recorded amongst plant species with no single life-form group associated with any response type. Only one exotic species, Cenchrus ciliaris, was recorded at low frequency. The strongest negative response was from a native annual grass, Chionachne hubbardiana, an example of a species that is highly sensitive to grazing disturbance. Herbarium records revealed only scant evidence that species with a negative response to grazing have declined through the period of commercial pastoralism. A regional analysis identified 14 from a total of 433 plant species in the regional flora that may be rare and potentially threatened by grazing disturbance. However, a targeted survey precluded grazing as a cause of decline for seven of these based on low palatability and positive responses to grazing and other disturbance. Our findings suggest that livestock grazing of semidesert grasslands with a short evolutionary history of ungulate grazing has altered plant composition, but has not caused declines in the dominant perennial grasses or in species richness as predicted by the preceding literature. The biggest impact of commercial pastoralism is the spread of woody leguminous trees that can transform grassland to thorny shrubland. The conservation of plant biodiversity is largely compatible with commercial pastoralism provided these woody weeds are controlled, but reserves strategically positioned within water remote areas are necessary to protect grazing-sensitive species. This study demonstrates that a combination of experimental studies and regional surveys can be used to understand anthropogenic impacts on natural ecosystems where reference habitat is not available.

Nucleic acid hybridizations as radioactive tool for rapid detection of banana bunchy top virus

Banana bunchy top disease (BBTD) caused by banana bunchy top virus (BBTV) was radioactively detected by nucleic acid hybridization techniques. Results showed that, 32P-labelled insert of pBT338 was hybridized with nucleic acid extracts from BBTV-infected plants from Egypt and Australia but not with those from CMV-infected plants from Egypt. Results revealed that BBTV was greatly detected in midrib, roots, meristem, corm, leaves and pseudostem respectively. BBTV was also detected in symptomless young plants prepared from diseased plant materials grown under tissue culture conditions but was not present in those performed from healthy plant materials. The sensitivity of dot blot and Southern blot hybridizations for the detection of BBTV was also performed for the detection of BBTV.

Mapping eQTLs in the Norfolk Island genetic isolate identifies candidate genes for CVD risk traits

Cardiovascular disease (CVD) affects millions of people worldwide and is influenced by numerous factors, including lifestyle and genetics. Expression quantitative trait loci (eQTLs) influence gene expression and are good candidates for CVD risk. Founder-effect pedigrees can provide additional power to map genes associated with disease risk. Therefore, we identified eQTLs in the genetic isolate of Norfolk Island (NI) and tested for associations between these and CVD risk factors. We measured genome-wide transcript levels of blood lymphocytes in 330 individuals and used pedigree-based heritability analysis to identify heritable transcripts. eQTLs were identified by genome-wide association testing of these transcripts. Testing for association between CVD risk factors (i.e., blood lipids, blood pressure, and body fat indices) and eQTLs revealed 1,712 heritable transcripts (p < 0.05) with heritability values ranging from 0.18 to 0.84. From these, we identified 200 cis-acting and 70 trans-acting eQTLs (p < 1.84 × 10(-7)) An eQTL-centric analysis of CVD risk traits revealed multiple associations, including 12 previously associated with CVD-related traits. Trait versus eQTL regression modeling identified four CVD risk candidates (NAAA, PAPSS1, NME1, and PRDX1), all of which have known biological roles in disease. In addition, we implicated several genes previously associated with CVD risk traits, including MTHFR and FN3KRP. We have successfully identified a panel of eQTLs in the NI pedigree and used this to implicate several genes in CVD risk. Future studies are required for further assessing the functional importance of these eQTLs and whether the findings here also relate to outbred populations.

Enhancing itaconic acid production by Aspergillus terreus

Aspergillus terreus is successfully used for industrial production of itaconic acid. The acid is formed from cis-aconitate, an intermediate of the tricarboxylic (TCA) cycle, by catalytic action of cis-aconitate decarboxylase. It could be assumed that strong anaplerotic reactions that replenish the pool of the TCA cycle intermediates would enhance the synthesis and excretion rate of itaconic acid. In the phylogenetic close relative Aspergillus niger, upregulated metabolic flux through glycolysis has been described that acted as a strong anaplerotic reaction. Deregulated glycolytic flux was caused by posttranslational modification of 6-phosphofructo-1-kinase (PFK1) that resulted in formation of a highly active, citrate inhibition-resistant shorter form of the enzyme. In order to avoid complex posttranslational modification, the native A. niger pfkA gene has been modified to encode for an active shorter PFK1 fragment. By the insertion of the modified A. niger pfkA genes into the A. terreus strain, increased specific productivities of itaconic acid and final yields were documented by transformants in respect to the parental strain. On the other hand, growth rate of all transformants remained suppressed which is due to the low initial pH value of the medium, one of the prerequisites for the accumulation of itaconic acid by A. terreus mycelium. © 2010 Springer-Verlag.

A particle based model to simulate microscale morphological changes of plant tissues during drying

Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.