Precision genetic cellular models identify therapies protective against ER stress.

Rare monogenic disorders often share molecular etiologies involved in the pathogenesis of common diseases. Congenital disorders of glycosylation (CDG) and deglycosylation (CDDG) are rare pediatric disorders with symptoms that range from mild to life threatening. A biological mechanism shared among CDG and CDDG as well as more common neurodegenerative diseases such as Alzheimer's disease and amyotrophic lateral sclerosis, is endoplasmic reticulum (ER) stress. We developed isogenic human cellular models of two types of CDG and the only known CDDG to discover drugs that can alleviate ER stress. Systematic phenotyping confirmed ER stress and identified elevated autophagy among other phenotypes in each model. We screened 1049 compounds and scored their ability to correct aberrant morphology in each model using an agnostic cell-painting assay based on >300 cellular features. This primary screen identified multiple compounds able to correct morphological phenotypes. Independent validation shows they also correct cellular phenotypes and alleviate each of the ER stress markers identified in each model. Many of the active compounds are associated with microtubule dynamics, which points to new therapeutic opportunities for both rare and more common disorders presenting with ER stress, such as Alzheimer's disease and amyotrophic lateral sclerosis.

Homology-based hydrogen bond information improves crystallographic structures in the PDB.

The Protein Data Bank (PDB) is the global archive for structural information on macromolecules, and a popular resource for researchers, teachers, and students, amassing more than one million unique users each year. Crystallographic structure models in the PDB (more than 100,000 entries) are optimized against the crystal diffraction data and geometrical restraints. This process of crystallographic refinement typically ignored hydrogen bond (H-bond) distances as a source of information. However, H-bond restraints can improve structures at low resolution where diffraction data are limited. To improve low-resolution structure refinement, we present methods for deriving H-bond information either globally from well-refined high-resolution structures from the PDB-REDO databank, or specifically from on-the-fly constructed sets of homologous high-resolution structures. Refinement incorporating HOmology DErived Restraints (HODER), improves geometrical quality and the fit to the diffraction data for many low-resolution structures. To make these improvements readily available to the general public, we applied our new algorithms to all crystallographic structures in the PDB: using massively parallel computing, we constructed a new instance of the PDB-REDO databank (https://pdb-redo.eu). This resource is useful for researchers to gain insight on individual structures, on specific protein families (as we demonstrate with examples), and on general features of protein structure using data mining approaches on a uniformly treated dataset.

Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies.

MOTIVATION: Next-generation sequencing (NGS) technologies have become much more efficient, allowing whole human genomes to be sequenced faster and cheaper than ever before. However, processing the raw sequence reads associated with NGS technologies requires care and sophistication in order to draw compelling inferences about phenotypic consequences of variation in human genomes. It has been shown that different approaches to variant calling from NGS data can lead to different conclusions. Ensuring appropriate accuracy and quality in variant calling can come at a computational cost. RESULTS: We describe our experience implementing and evaluating a group-based approach to calling variants on large numbers of whole human genomes. We explore the influence of many factors that may impact the accuracy and efficiency of group-based variant calling, including group size, the biogeographical backgrounds of the individuals who have been sequenced, and the computing environment used. We make efficient use of the Gordon supercomputer cluster at the San Diego Supercomputer Center by incorporating job-packing and parallelization considerations into our workflow while calling variants on 437 whole human genomes generated as part of large association study. CONCLUSIONS: We ultimately find that our workflow resulted in high-quality variant calls in a computationally efficient manner. We argue that studies like ours should motivate further investigations combining hardware-oriented advances in computing systems with algorithmic developments to tackle emerging 'big data' problems in biomedical research brought on by the expansion of NGS technologies.

Whole-genome sequencing analysis of phenotypic heterogeneity and anticipation in Li-Fraumeni cancer predisposition syndrome.

The Li-Fraumeni syndrome (LFS) and its variant form (LFL) is a familial predisposition to multiple forms of childhood, adolescent, and adult cancers associated with germ-line mutation in the TP53 tumor suppressor gene. Individual disparities in tumor patterns are compounded by acceleration of cancer onset with successive generations. It has been suggested that this apparent anticipation pattern may result from germ-line genomic instability in TP53 mutation carriers, causing increased DNA copy-number variations (CNVs) with successive generations. To address the genetic basis of phenotypic disparities of LFS/LFL, we performed whole-genome sequencing (WGS) of 13 subjects from two generations of an LFS kindred. Neither de novo CNV nor significant difference in total CNV was detected in relation with successive generations or with age at cancer onset. These observations were consistent with an experimental mouse model system showing that trp53 deficiency in the germ line of father or mother did not increase CNV occurrence in the offspring. On the other hand, individual records on 1,771 TP53 mutation carriers from 294 pedigrees were compiled to assess genetic anticipation patterns (International Agency for Research on Cancer TP53 database). No strictly defined anticipation pattern was observed. Rather, in multigeneration families, cancer onset was delayed in older compared with recent generations. These observations support an alternative model for apparent anticipation in which rare variants from noncarrier parents may attenuate constitutive resistance to tumorigenesis in the offspring of TP53 mutation carriers with late cancer onset.

Identifying microRNA/mRNA dysregulations in ovarian cancer.

BACKGROUND: MicroRNAs are a class of noncoding RNA molecules that co-regulate the expression of multiple genes via mRNA transcript degradation or translation inhibition. Since they often target entire pathways, they may be better drug targets than genes or proteins. MicroRNAs are known to be dysregulated in many tumours and associated with aggressive or poor prognosis phenotypes. Since they regulate mRNA in a tissue specific manner, their functional mRNA targets are poorly understood. In previous work, we developed a method to identify direct mRNA targets of microRNA using patient matched microRNA/mRNA expression data using an anti-correlation signature. This method, applied to clear cell Renal Cell Carcinoma (ccRCC), revealed many new regulatory pathways compromised in ccRCC. In the present paper, we apply this method to identify dysregulated microRNA/mRNA mechanisms in ovarian cancer using data from The Cancer Genome Atlas (TCGA). METHODS: TCGA Microarray data was normalized and samples whose class labels (tumour or normal) were ambiguous with respect to consensus ensemble K-Means clustering were removed. Significantly anti-correlated and correlated genes/microRNA differentially expressed between tumour and normal samples were identified. TargetScan was used to identify gene targets of microRNA. RESULTS: We identified novel microRNA/mRNA mechanisms in ovarian cancer. For example, the expression level of RAD51AP1 was found to be strongly anti-correlated with the expression of hsa-miR-140-3p, which was significantly down-regulated in the tumour samples. The anti-correlation signature was present separately in the tumour and normal samples, suggesting a direct causal dysregulation of RAD51AP1 by hsa-miR-140-3p in the ovary. Other pairs of potentially biological relevance include: hsa-miR-145/E2F3, hsa-miR-139-5p/TOP2A, and hsa-miR-133a/GCLC. We also identified sets of positively correlated microRNA/mRNA pairs that are most likely result from indirect regulatory mechanisms. CONCLUSIONS: Our findings identify novel microRNA/mRNA relationships that can be verified experimentally. We identify both generic microRNA/mRNA regulation mechanisms in the ovary as well as specific microRNA/mRNA controls which are turned on or off in ovarian tumours. Our results suggest that the disease process uses specific mechanisms which may be significant for their utility as early detection biomarkers or in the development of microRNA therapies in treating ovarian cancers. The positively correlated microRNA/mRNA pairs suggest the existence of novel regulatory mechanisms that proceed via intermediate states (indirect regulation) in ovarian tumorigenesis.

Negative feedback governs gonadotrope frequency-decoding of gonadotropin releasing hormone pulse-frequency.

The synthesis of the gonadotropin subunits is directed by pulsatile gonadotropin-releasing hormone (GnRH) from the hypothalamus, with the frequency of GnRH pulses governing the differential expression of the common alpha-subunit, luteinizing hormone beta-subunit (LHbeta) and follicle-stimulating hormone beta-subunit (FSHbeta). Three mitogen-activated protein kinases, (MAPKs), ERK1/2, JNK and p38, contribute uniquely and combinatorially to the expression of each of these subunit genes. In this study, using both experimental and computational methods, we found that dual specificity phosphatase regulation of the activity of the three MAPKs through negative feedback is required, and forms the basis for decoding the frequency of pulsatile GnRH. A fourth MAPK, ERK5, was shown also to be activated by GnRH. ERK5 was found to stimulate FSHbeta promoter activity and to increase FSHbeta mRNA levels, as well as enhancing its preference for low GnRH pulse frequencies. The latter is achieved through boosting the ultrasensitive behavior of FSHbeta gene expression by increasing the number of MAPK dependencies, and through modulating the feedforward effects of JNK activation on the GnRH receptor (GnRH-R). Our findings contribute to understanding the role of changing GnRH pulse-frequency in controlling transcription of the pituitary gonadotropins, which comprises a crucial aspect in regulating reproduction. Pulsatile stimuli and oscillating signals are integral to many biological processes, and elucidation of the mechanisms through which the pulsatility is decoded explains how the same stimulant can lead to various outcomes in a single cell.

3D meshless prostate segmentation and registration in image guided radiotherapy.

Image Guided Radiation Therapy (IGRT) improves radiation therapy for prostate cancer by facilitating precise radiation dose coverage of the object of interest, and minimizing dose to adjacent normal organs. In an effort to optimize IGRT, we developed a fast segmentation-registration-segmentation framework to accurately and efficiently delineate the clinically critical objects in Cone Beam CT images obtained during radiation treatment. The proposed framework started with deformable models automatically segmenting the prostate, bladder, and rectum in planning CT images. All models were built around seed points and involved in the CT image under the influence of image features using the level set formulation. The deformable models were then converted into meshless point sets and underwent a 3D non rigid registration from the planning CT to the treatment CBCT. The motion of deformable models during the registration was constrained by the global shape prior on the target surface during the deformation. The meshless formulation provided a convenient interface between deformable models and the image feature based registration method. The final registered deformable models in the CBCT domain were further refined using the interaction between objects and other available image features. The segmentation results for 15 data sets has been included in the validation study, compared with manual segmentations by a radiation oncologist. The automatic segmentation results achieved a satisfactory convergence with manual segmentations and met the speed requirement for on line IGRT.

The tumor suppressor p53: cancer and aging.

Aging, like many other biological processes, is subject to regulation by genes that reside in pathways that have been conserved during evolution. The insulin/ IGF-1 pathway, mTOR pathway and p53 pathway are among those conserved pathways that impact upon longevity and aging-related diseases such as cancer. Most cancers arise in the last quarter of life span with the frequency increasing exponentially with time, and mutation accumulation in critical genes (e.g., p53) in individual cells over a lifetime is thought to be the reason. Recently, we found that the efficiency of the p53 response to stress declines significantly with age in mice, and the time of onset of this decreased p53 response correlates with the life span of mice. Given the crucial role of the p53 in tumor prevention, this decline in p53 activity at older ages in animals could contribute to the observed dramatic increases in cancer frequency, and provides a plausible explanation for the correlation between tumorigenesis and aging in addition to the accumulation of DNA mutations over lifetime. We discuss here the coordination and communication between the p53 pathway and the IGF-1-mTOR pathways, and their possible impact on cancer and longevity.

Candidate List of yoUr Biomarker (CLUB): A Web-based Platform to Aid Cancer Biomarker Research.

CLUB ("Candidate List of yoUr Biomarkers") is a freely available, web-based resource designed to support Cancer biomarker research. It is targeted to provide a comprehensive list of candidate biomarkers for various cancers that have been reported by the research community. CLUB provides tools for comparison of marker candidates from different experimental platforms, with the ability to filter, search, query and explore, molecular interaction networks associated with cancer biomarkers from the published literature and from data uploaded by the community. This complex and ambitious project is implemented in phases. As a first step, we have compiled from the literature an initial set of differentially expressed human candidate cancer biomarkers. Each candidate is annotated with information from publicly available databases such as Gene Ontology, Swiss-Prot database, National Center for Biotechnology Information's reference sequences, Biomolecular Interaction Network Database and IntAct interaction. The user has the option to maintain private lists of biomarker candidates or share and export these for use by the community. Furthermore, users may customize and combine commonly used sets of selection procedures and apply them as a stored workflow using selected candidate lists. To enable an assessment by the user before taking a candidate biomarker to the experimental validation stage, the platform contains the functionality to identify pathways associated with cancer risk, staging, prognosis, outcome in cancer and other clinically associated phenotypes. The system is available at http://club.bii.a-star.edu.sg.

Molecular force spectroscopy of homophilic nectin-1 interactions.

Nectins are Ca2+ independent cell adhesion molecules localizing at the cadherin based adherens junctions. In this study, we have used atomic force microscopy to study interaction of a chimera of extra cellular fragment of nectin-1 and Fc of human IgG (nef-1) with wild type L-fibroblasts that express endogenous nectin-1 to elucidate the biophysical characteristics of homophilic nectin-1 trans-interactions at the level of single molecule. Bond strength distribution revealed three distinct bound states (or configurations) of trans-interactions between paired nectins, where each bound state has a unique unstressed off-rate and reactive compliance. Kinetic analysis of force-dependent off-rate of the bound state involving trans-interacting V-V domains between paired nectin-1 (unstressed off-rate approximately 1.465+/-0.779 s(-1), reactive compliance approximately 0.143+/-0.072 nm) was found to be closest to E-cadherin, indicating that V-V domain trans-interactions are probably necessary to initiate and promote adhesions of E-cadherin at adherens junctions (AJs).

Oscillations in intracellular signaling cascades.

In this paper, we study the oscillatory dynamics of intracellular signaling cascades. We derive a reaction-diffusion model of the mitogen-activated protein kinase cascade, and use it to show how oscillations of the protein kinase concentrations can occur as a function of the depth of the cascade. We find that only cascades with depths of three or more layers undergo oscillatory instabilities. In addition, the oscillatory instability is spatially uniform. Thus, the oscillations synchronize the protein kinase concentrations and result in them being uniformly distributed in the cytosol, despite the presence of protein kinase diffusion. Finally, we show how the oscillations are perturbed when parallel cascades "crosstalk." We find that the protein kinases in the downstream layers of the cascade are less perturbed than those in the upstream layers. In particular, cascades of three layers are able to maintain the total power of the protein kinase activities at approximately the unperturbed level. Taken together, our results suggest that only cascades of at least three layers can synchronize the oscillations of protein kinases in the cytosol and operate in parallel in the presence of crosstalk without loss of signaling fidelity.

Gastric Cancer (Biomarkers) Knowledgebase (GCBKB): A Curated and Fully Integrated Knowledgebase of Putative Biomarkers Related to Gastric Cancer.

The Gastric Cancer (Biomarkers) Knowledgebase (GCBKB) (http://biomarkers.bii.a-star.edu.sg/background/gastricCancerBiomarkersKb.php) is a curated and fully integrated knowledgebase that provides data relating to putative biomarkers that may be used in the diagnosis and prognosis of gastric cancer. It is freely available to all users. The data contained in the knowledgebase was derived from a large literature source and the putative biomarkers therein have been annotated with data from the public domain. The knowledgebase is maintained by a curation team who update the data from a defined source. As well as mining data from the literature, the knowledgebase will also be populated with unpublished experimental data from investigators working in the gastric cancer biomarker discovery field. Users can perform searches to identify potential markers defined by experiment type, tissue type and disease state. Search results may be saved, manipulated and retrieved at a later date. As far as the authors are aware this is the first open access database dedicated to the discovery and investigation of gastric cancer biomarkers.

iHAP--integrated haplotype analysis pipeline for characterizing the haplotype structure of genes.

BACKGROUND: The advent of genotype data from large-scale efforts that catalog the genetic variants of different populations have given rise to new avenues for multifactorial disease association studies. Recent work shows that genotype data from the International HapMap Project have a high degree of transferability to the wider population. This implies that the design of genotyping studies on local populations may be facilitated through inferences drawn from information contained in HapMap populations. RESULTS: To facilitate analysis of HapMap data for characterizing the haplotype structure of genes or any chromosomal regions, we have developed an integrated web-based resource, iHAP. In addition to incorporating genotype and haplotype data from the International HapMap Project and gene information from the UCSC Genome Browser Database, iHAP also provides capabilities for inferring haplotype blocks and selecting tag SNPs that are representative of haplotype patterns. These include block partitioning algorithms, block definitions, tag SNP definitions, as well as SNPs to be "force included" as tags. Based on the parameters defined at the input stage, iHAP performs on-the-fly analysis and displays the result graphically as a webpage. To facilitate analysis, intermediate and final result files can be downloaded. CONCLUSION: The iHAP resource, available at http://ihap.bii.a-star.edu.sg, provides a convenient yet flexible approach for the user community to analyze HapMap data and identify candidate targets for genotyping studies.

Hybrid simulations of stochastic reaction-diffusion processes for modeling intracellular signaling pathways.

In the intracellular environment, signaling takes place in a nonideal environment that is spatially heterogeneous and that is noisy, with the noise arising from the low copy numbers of the signaling molecules involved. In this paper, we model intracellular signaling pathways as stochastic reaction-diffusion processes and adapt techniques commonly used by physicists to solve for the spatiotemporal evolution of the signaling pathways. We then apply it to study two problems of relevance to the modeling of intracellular signaling pathways. First, we show that, in the limit of small protein diffusion which is typically the case for proteins in the cytosol crowded by other macromolecules, the extent of diffusion control, in the transient regime, on reactions is greater than previous predictions. Second, we show that the presence of scaffold proteins can modify the phosphorylation activity of a mitogen-activated protein kinase cascade, and explain how this activity is modulated by the scaffold protein concentration.

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running.

BACKGROUND: Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. METHODS: We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. RESULTS: We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. CONCLUSIONS: Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described.