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1.  Homing of Neural Stem Cells From the Venous Compartment Into a Brain Infarct Does Not Involve Conventional Interactions With Vascular Endothelium 
Human neural stem cells (hNSCs) hold great potential for treatment of a wide variety of neurodegenerative and neurotraumatic conditions. However, the findings of this study suggest that the behavior of hNSCs in circulation is different from that observed with other cell types and suggests that, at least for stroke, intravenous administration is a suboptimal route even when the in vitro rolling ability of hNSCs is optimized by enforced fucosylation.
Human neural stem cells (hNSCs) hold great potential for treatment of a wide variety of neurodegenerative and neurotraumatic conditions. Heretofore, administration has been through intracranial injection or implantation of cells. Because neural stem cells are capable of migrating to the injured brain from the intravascular space, it seemed feasible to administer them intravenously if their ability to circumvent the blood-brain barrier was enhanced. In the present studies, we found that interactions of hNSCs in vitro on the luminal surface of human umbilical vein endothelial cells was enhanced following enforced expression of cutaneous lymphocyte antigen on cell surface moieties by incubation of hNSCs with fucosyltransferase VI and GDP-fucose (fhNSCs). Interestingly, ex vivo fucosylation of hNSCs not only did not improve the cells homing into the brain injured by stroke following intravenous administration but also increased mortality of rats compared with the nonfucosylated hNSC group. Efforts to explain these unexpected findings using a three-dimensional flow chamber device revealed that transmigration of fhNSCs (under conditions of physiological shear stress) mediated by stromal cell-derived factor 1α was significantly decreased compared with controls. Further analysis revealed that hNSCs poorly withstand physiological shear stress, and their ability is further decreased following fucosylation. In addition, fhNSCs demonstrated a higher frequency of cellular aggregate formation as well as a tendency for removal of fucose from the cell surface. In summary, our findings suggest that the behavior of hNSCs in circulation is different from that observed with other cell types and that, at least for stroke, intravenous administration is a suboptimal route, even when the in vitro rolling ability of hNSCs is optimized by enforced fucosylation.
PMCID: PMC3925049  PMID: 24396034
Neural stem cells; Stroke; Cell migration/homing; Fucosylation; Endothelial cells; Shear stress
2.  Functional Knowledge Transfer for High-accuracy Prediction of Under-studied Biological Processes 
PLoS Computational Biology  2013;9(3):e1002957.
A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning) that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST) have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction.
We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT) dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics techniques and will help biologists systematically integrate prior knowledge from diverse systems to direct targeted experiments in their organism of study.
Author Summary
Due to technical and ethical challenges many human diseases or biological processes are studied in model organisms. Discoveries in these organisms are then transferred back to human or other model organisms. Traditional methods for transferring novel gene function annotations have relied on finding genes with high sequence similarity believed to share evolutionary ancestry. However, sequence similarity does not guarantee a shared functional role in molecular pathways. In this study, we show that functional genomics can complement traditional sequence similarity measures to improve the transfer of gene annotations between organisms. We coupled our knowledge transfer method with current state-of-the-art machine learning algorithms and predicted gene function for 11,000 biological processes across six organisms. We experimentally validated our prediction of wnt5b's involvement in the determination of left-right heart asymmetry in zebrafish. Our results show that functional knowledge transfer can improve the coverage and accuracy of machine learning methods used for gene function prediction in a diverse set of organisms. Such an approach can be applied to additional organisms, and will be especially beneficial in organisms that have high-throughput genomic data with sparse annotations.
PMCID: PMC3597527  PMID: 23516347
3.  Tissue-Specific Functional Networks for Prioritizing Phenotype and Disease Genes 
PLoS Computational Biology  2012;8(9):e1002694.
Integrated analyses of functional genomics data have enormous potential for identifying phenotype-associated genes. Tissue-specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. Accounting for tissue specificity in global integration of functional genomics data is challenging, as “functionality” and “functional relationships” are often not resolved for specific tissue types. We address this challenge by generating tissue-specific functional networks, which can effectively represent the diversity of protein function for more accurate identification of phenotype-associated genes in the laboratory mouse. Specifically, we created 107 tissue-specific functional relationship networks through integration of genomic data utilizing knowledge of tissue-specific gene expression patterns. Cross-network comparison revealed significantly changed genes enriched for functions related to specific tissue development. We then utilized these tissue-specific networks to predict genes associated with different phenotypes. Our results demonstrate that prediction performance is significantly improved through using the tissue-specific networks as compared to the global functional network. We used a testis-specific functional relationship network to predict genes associated with male fertility and spermatogenesis phenotypes, and experimentally confirmed one top prediction, Mbyl1. We then focused on a less-common genetic disease, ataxia, and identified candidates uniquely predicted by the cerebellum network, which are supported by both literature and experimental evidence. Our systems-level, tissue-specific scheme advances over traditional global integration and analyses and establishes a prototype to address the tissue-specific effects of genetic perturbations, diseases and drugs.
Author Summary
Tissue specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. We propose an effective strategy to model tissue-specific functional relationship networks in the laboratory mouse. We integrated large scale genomics datasets as well as low-throughput tissue-specific expression profiles to estimate the probability that two proteins are co-functioning in the tissue under study. These networks can accurately reflect the diversity of protein functions across different organs and tissue compartments. By computationally exploring the tissue-specific networks, we can accurately predict novel phenotype-related gene candidates. We experimentally confirmed a top candidate gene, Mybl1, to affect several male fertility phenotypes, predicted based on male-reproductive system-specific networks and we predicted candidates related to a rare genetic disease ataxia, which are supported by experimental and literature evidence. The above results demonstrate the power of modeling tissue-specific dynamics of co-functionality through computational approaches.
PMCID: PMC3459891  PMID: 23028291
4.  IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks 
Nucleic Acids Research  2012;40(Web Server issue):W484-W490.
Integrative multi-species prediction (IMP) is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides a framework for biologists to analyze their candidate gene sets in the context of functional networks, as they expand or focus these sets by mining functional relationships predicted from integrated high-throughput data. IMP integrates prior knowledge and data collections from multiple organisms in its analyses. Through flexible and interactive visualizations, researchers can compare functional contexts and interpret the behavior of their gene sets across organisms. Additionally, IMP identifies homologs with conserved functional roles for knowledge transfer, allowing for accurate function predictions even for biological processes that have very few experimental annotations in a given organism. IMP currently supports seven organisms (Homo sapiens, Mus musculus, Rattus novegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans and Saccharomyces cerevisiae), does not require any registration or installation and is freely available for use at
PMCID: PMC3394282  PMID: 22684505
5.  An ADAMTSL2 Founder Mutation Causes Musladin-Lueke Syndrome, a Heritable Disorder of Beagle Dogs, Featuring Stiff Skin and Joint Contractures 
PLoS ONE  2010;5(9):e12817.
Musladin-Lueke Syndrome (MLS) is a hereditary disorder affecting Beagle dogs that manifests with extensive fibrosis of the skin and joints. In this respect, it resembles human stiff skin syndrome and the Tight skin mouse, each of which is caused by gene defects affecting fibrillin-1, a major component of tissue microfibrils. The objective of this work was to determine the genetic basis of MLS and the molecular consequence of the identified mutation.
Methodology and Principal Findings
We mapped the locus for MLS by genome-wide association to a 3.05 Mb haplotype on canine chromosome 9 (CFA9 (50.11–54.26; praw <10−7)), which was homozygous and identical-by-descent among all affected dogs, consistent with recessive inheritance of a founder mutation. Sequence analysis of a candidate gene at this locus, ADAMTSL2, which is responsible for the human TGFβ dysregulation syndrome, Geleophysic Dysplasia (GD), uncovered a mutation in exon 7 (c.660C>T; p.R221C) perfectly associated with MLS (p-value = 10−12). Murine ADAMTSL2 containing the p.R221C mutation formed anomalous disulfide-bonded dimers when transiently expressed in COS-1, HEK293F and CHO cells, and was present in the medium of these cells at lower levels than wild-type ADAMTSL2 expressed in parallel.
The genetic basis of MLS is a founder mutation in ADAMTSL2, previously shown to interact with latent TGF-β binding protein, which binds fibrillin-1. The molecular effect of the founder mutation on ADAMTSL2 is formation of disulfide-bonded dimers. Although caused by a distinct mutation, and having a milder phenotype than human GD, MLS nevertheless offers a new animal model for study of GD, and for prospective insights on mechanisms and pathways of skin fibrosis and joint contractures.
PMCID: PMC2941456  PMID: 20862248
6.  AMP-activated protein kinase pathway: a potential therapeutic target in cardiometabolic disease 
AMPK (AMP-activated protein kinase) is a heterotrimetric enzyme that is expressed in many tissues, including the heart and vasculature, and plays a central role in the regulation of energy homoeostasis. It is activated in response to stresses that lead to an increase in the cellular AMP/ATP ratio caused either by inhibition of ATP production (i.e. anoxia or ischaemia) or by accelerating ATP consumption (i.e. muscle contraction or fasting). In the heart, AMPK activity increases during ischaemia and functions to sustain ATP, cardiac function and myocardial viability. There is increasing evidence that AMPK is implicated in the pathophysiology of cardiovascular and metabolic diseases. A principle mode of AMPK activation is phosphorylation by upstream kinases [e.g. LKB1 and CaMK (Ca2+/calmodulin-dependent protein kinase], which leads to direct effects on tissues and phosphorylation of various downstream kinases [e.g. eEF2 (eukaryotic elongation factor 2) kinase and p70 S6 kinase]. These upstream and downstream kinases of AMPK have fundamental roles in glucose metabolism, fatty acid oxidation, protein synthesis and tumour suppression; consequently, they have been implicated in cardiac ischaemia, arrhythmias and hypertrophy. Recent mechanistic studies have shown that AMPK has an important role in the mechanism of action of MF (metformin), TDZs (thiazolinediones) and statins. Increased understanding of the beneficial effects of AMPK activation provides the rationale for targeting AMPK in the development of new therapeutic strategies for cardiometabolic disease.
PMCID: PMC2762688  PMID: 19275766
5-amino-4-imidazolecarboxamide riboside-1-β-D-ribofuranoside (AICAR); AMP-activated protein kinase (AMPK); cardiovascular disease; insulin resistance; metformin; obesity; ACC, acetyl-CoA carboxylase; AICAR, 5-amino-4-imidazolecarboxamide riboside-1-β-D-ribofuranoside; AMPK, AMP-activated protein kinase; CaMK, Ca2+/calmodulin-dependent protein kinase; CPT-1, carnitine palmitoyltransferase-1; CVD, cardiovascular disease; eEF2, eukaryotic elongation factor 2; eNOS, endothelial NO synthase; GLUT-4, glucose transporter-4; HF, heart failure; CHF, chronic HF; HMG-CoA, 3-hydroxy-3-methyl-CoA; IL-6, interleukin-6; LV, left ventricular; MF, metformin; MI, myocardial infarction; MO25, mouse protein 25; mTOR, mammalian target of rapamycin; NEFA, non-esterified fatty acid (‘free fatty acid’); p70RSK, p70 ribosomal protein S6 kinase; PDH, pyruvate dehydrogenase; PFK-2, phosphofructokinase-2; PPAR-γ, peroxisome-proliferator-activated receptor-γ; PROactive, PROspective pioglitAzone Clinical Trial In macroVascular Events; STRAD, Ste20-related adaptor; TNF-α, tumour necrosis factor-α; TZD, thiazolinedione

Results 1-6 (6)