An agent-based approach to immune modelling

This study focuses on trying to understand why the range of experience with respect to HIV infection is so diverse, especially as regards to the latency period. The challenge is to determine what assumptions can be made about the nature of the experience of antigenic invasion and diversity that can be modelled, tested and argued plausibly. To investigate this, an agent-based approach is used to extract high-level behaviour which cannot be described analytically from the set of interaction rules at the cellular level. A prototype model encompasses local variation in baseline properties contributing to the individual disease experience and is included in a network which mimics the chain of lymphatic nodes. Dealing with massively multi-agent systems requires major computational efforts. However, parallelisation methods are a natural consequence and advantage of the multi-agent approach. These are implemented using the MPI library.

Visualization of complex biological systems: An immune response model using OpenGL

In this paper we present an update on our novel visualization technologies based on cellular immune interaction from both large-scale spatial and temporal perspectives. We do so with a primary motive: to present a visually and behaviourally realistic environment to the community of experimental biologists and physicians such that their knowledge and expertise may be more readily integrated into the model creation and calibration process. Visualization aids understanding as we rely on visual perception to make crucial decisions. For example, with our initial model, we can visualize the dynamics of an idealized lymphatic compartment, with antigen presenting cells (APC) and cytotoxic T lymphocyte (CTL) cells. The visualization technology presented here offers the researcher the ability to start, pause, zoom-in, zoom-out and navigate in 3-dimensions through an idealised lymphatic compartment.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.

Association between single-nucleotide polymorphisms in growth factor genes and quality of life in men with prostate cancer and the general population

Purpose Improved survival for men with prostate cancer has led to increased attention to factors influencing quality of life (QOL). As protein levels of vascular endothelial growth factor (VEGF) and insulin-like growth factor 1 (IGF-1) have been reported to be associated with QOL in people with cancer, we sought to identify whether single-nucleotide polymorphisms (SNPs) of these genes were associated with QOL in men with prostate cancer. Methods Multiple linear regression of two data sets (including approximately 750 men newly diagnosed with prostate cancer and 550 men from the general population) was used to investigate SNPs of VEGF and IGF-1 (10 SNPs in total) for associations with QOL (measured by the SF-36v2 health survey). Results Men with prostate cancer who carried the minor ‘T’ allele for IGF-1 SNP rs35767 had higher mean Role-Physical scale scores (≥0.3 SD) compared to non-carriers (p < 0.05). While this association was not identified in men from the general population, one IGF-1 SNP rs7965399 was associated with higher mean Bodily Pain scale scores in men from the general population that was not found in men with prostate cancer. Men from the general population who carried the rare ‘C’ allele had higher mean Bodily Pain scale scores (≥0.3 SD) than non-carriers (p < 0.05). Conclusions Through identifying SNPs that are associated with QOL in men with prostate cancer and men from the general population, this study adds to the mapping of complex interrelationships that influence QOL and suggests a role for IGF-I in physical QOL outcomes. Future research may identify biomarkers associated with increased risk of poor QOL that could assist in the provision of pre-emptive support for those identified at risk.

Defining a 3-dimensional (3D) in vitro model to study immune cell and renal cell interactions

This study aimed to develop a 3-Dimensional (D) hydrogel system for the co-culture of autologous human renal and immune cells. Previous studies have shown that human renal epithelial cells are able to modulate autologous immune cell responses. However, these studies were undertaken in a standard 2D culture system. The 3D model was developed to re-capitulate these observations within a more physiological relevant in vivo like environment.

An evaluation of potential candidate genes involved in salinity tolerance in striped catfish (Pangasianodon hypopthalmus) using an RNA-SEQ approach

The project investigated the molecular response of Tra catfish (Pangasianodon hypophthalmus) to elevated salinity conditions. We employed Next generation sequencing platform to evaluate differential gene expression profiles of key genes under two salinity conditions. Results of the current project can form the basis for further studies to confirm the functional roles of specific genes that influence salinity tolerance in the target species and more broadly in other freshwater teleost fishes. Ultimately, the approach can contribute to developing superior culture stocks of the target species.

Genetic effects on the cerebellar role in working memory: Same brain, different genes?

Over the past several years, evidence has accumulated showing that the cerebellum plays a significant role in cognitive function. Here we show, in a large genetically informative twin sample (n= 430; aged 16-30. years), that the cerebellum is strongly, and reliably (n=30 rescans), activated during an n-back working memory task, particularly lobules I-IV, VIIa Crus I and II, IX and the vermis. Monozygotic twin correlations for cerebellar activation were generally much larger than dizygotic twin correlations, consistent with genetic influences. Structural equation models showed that up to 65% of the variance in cerebellar activation during working memory is genetic (averaging 34% across significant voxels), most prominently in the lobules VI, and VIIa Crus I, with the remaining variance explained by unique/unshared environmental factors. Heritability estimates for brain activation in the cerebellum agree with those found for working memory activation in the cerebral cortex, even though cerebellar cyto-architecture differs substantially. Phenotypic correlations between BOLD percent signal change in cerebrum and cerebellum were low, and bivariate modeling indicated that genetic influences on the cerebellum are at least partly specific to the cerebellum. Activation on the voxel-level correlated very weakly with cerebellar gray matter volume, suggesting specific genetic influences on the BOLD signal. Heritable signals identified here should facilitate discovery of genetic polymorphisms influencing cerebellar function through genome-wide association studies, to elucidate the genetic liability to brain disorders affecting the cerebellum.

Discovery of genes that affect human brain connectivity: A genome-wide analysis of the connectome

Human brain connectivity is disrupted in a wide range of disorders from Alzheimer's disease to autism but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain regions. We scanned a large twin cohort (N=366) with 4-Tesla high angular resolution diffusion imaging (105-gradient HARDI). Using whole brain HARDI tractography, we extracted a relatively sparse 70×70 matrix representing fiber density between all pairs of cortical regions automatically labeled in co-registered anatomical scans. Additive genetic factors accounted for 1-58% of the variance in connectivity between 90 (of 122) tested nodes. We discovered genome-wide significant associations between variants and connectivity. GWAS permutations at various levels of heritability, and split-sample replication, validated our genetic findings. The resulting genes may offer new leads for mechanisms influencing aberrant connectivity and neurodegeneration. © 2012 IEEE.

The contribution of genes to cortical thickness and volume

We analyzed brain MRI data from 372 young adult twins toidentify cortical regions in which gray matter thickness and volume are influenced by genetics. This was achieved using an A/C/E structural equation model that divides the variance of these traits, at each point on the cortex, into additive genetic (A), shared (C), and unique environmental (E) components. A strong genetic influencewas found in frontal and parietal regions. Inaddition, we correlated cortical thickness with full-scale intelligence quotient for comparison with the A/C/E maps, and several regions where cortical structure was correlated with intelligence quotient are under genetic control. These cortical measures may be useful phenotypes to narrow the searchfor quantitative trait lociinfluencing brain structure.

Expression and characterization of digestive enzyme genes from hepatopancreatic transcripts from redclaw crayfish (Cherax quadricarinatus)

Redclaw crayfish, Cherax quadricarinatus, possess a number of biological and commercial attributes that make them ideal for commercial aquaculture. While some studies have investigated digestive enzyme activity and nutritional requirements of this species, little information exists about the expression of digestive enzyme genes and their role in regulating digestive capacity. The current study therefore sequenced and annotated a RNASeq library constructed from a redclaw hepatopancreas to identify genes involved in digestive enzyme production. We observed that most of the transcripts that were annotated as digestive enzyme genes are associated with carbohydrate metabolism, thus confirming that redclaw have an innate capacity to digest a range of carbohydrate substrates. While endoglucanases were the most abundant group of digestive enzymes found, a number of novel transcripts were also detected. Here, we provide the first report for the presence and expression of endo-b-mannanase in freshwater crayfish. This novel gene showed significant alignment with a GH5 family protein from marine Limnoriids, wood borers that do not possess symbiotic microbes in their gut system. Overall, the data generated here provide an important resource to better understand the suite of digestive enzymes in redclaw that are very useful to fully utilize the species’ digestive capacity and will assist development of specific artificial feeds.

Analysis, characterisation and expression of gill-expressed carbonic anhydrase genes in the freshwater crayfish Cherax quadricarinatus

Changes in water quality parameters such as pH and salinity can have a significant effect on productivity of aquaculture species. Similarly, relative osmotic pressure influences various physiological processes and regulates expression of a number of osmoregulatory genes. Among those, carbonic anhydrase (CA) plays a key role in systemic acid–base balance and ion regulation. Redclaw crayfish (Cherax quadricarinatus) are unique in their ability to thrive in environments with naturally varied pH levels, suggesting unique adaptation to pH stress. To date, however, no studies have focused on identification and characterisation of CA or other osmoregulatory genes in C. quadricarinatus. Here, we analysed the redclaw gill transcriptome and characterized CA genes along with a number of other key osmoregulatory genes that were identified in the transcriptome. We also examined patterns of gene expression of these CA genes when exposed to three pH treatments. In total, 72,382,710 paired end Illumina reads were assembled into 36,128 contigs with an average length of 800 bp. Approximately 37% of contigs received significant BLAST hits and 22% were assigned gene ontology terms. Three full length CA isoforms; cytoplasmic CA (ChqCAc), glycosyl-phosphatidylinositol-linked CA (ChqCAg), and β-CA (ChqCA-beta) as well as two partial CA gene sequences were identified. Both partial CA genes showed high similarity to ChqCAg and appeared to be duplicated from the ChqCAg. Full length coding sequences of Na+/K+-ATPase, V-type H+-ATPase, sarcoplasmic Ca+-ATPase, arginine kinase, calreticulin and Cl− channel protein 2 were also identified. Only the ChqCAc gene showed significant differences in expression across the three pH treatments. These data provide valuable information on the gill expressed CA genes and their expression patterns in freshwater crayfish. Overall our data suggest an important role for the ChqCAc gene in response to changes in pH and in systemic acid–base balance in freshwater crayfish.