Influence of the Internalization Pathway on the Efficacy of siRNA Delivery by Cationic Fluorescent Nanodiamonds in the Ewing Sarcoma Cell Model

Small interfering RNAs (siRNAs) are powerful tools commonly used for the specific inhibition of gene expression. However, vectorization is required to facilitate cell penetration and to prevent siRNA degradation by nucleases. We have shown that diamond nanocrystals coated with cationic polymer can be used to carry siRNAs into Ewing sarcoma cells, in which they remain traceable over long periods, due to their intrinsic stable fluorescence. We tested two cationic polymers, polyallylamine and polyethylenimine. The release of siRNA, accompanied by Ewing sarcoma EWS-Fli1 oncogene silencing, was observed only with polyethylenimine. We investigated cell penetration and found that the underlying mechanisms accounted for these differences in behavior. Using drugs selectively inhibiting particular pathways and a combination of fluorescence and electronic microscopy, we showed that siRNA gene silencing occurred only if the siRNA:cationic nanodiamond complex followed the macropinocytosis route. These results have potential implications for the design of efficient drug-delivery vectors.     

Toward reprogramming bacteria with small molecules and RNA

A major goal of synthetic biology is to reprogram bacteria to carry out complex tasks, such as synthesizing and delivering drugs, and seeking and destroying environmental pollutants. Advances in molecular biology and bacterial genetics have made it straightforward to modify, insert, or delete genes in many bacterial strains, and advances in gene synthesis have opened the door to replacing entire genomes. However, rewriting the underlying genetic code is only part of the challenge of reprogramming cellular behavior. A remaining challenge is to control how and when the modified genes are expressed. Several recent studies have highlighted how synthetic riboswitches, which are RNA sequences that undergo a ligand-induced conformational change to alter gene expression, can be used to reprogram how bacteria respond to small molecules.     

Transient Knockdown of Tyrosine Hydroxylase during Development Has Persistent Effects on Behaviour in Adult Zebrafish (Danio rerio)

Abnormal dopamine (DA) signaling is often suggested as causative in schizophrenia. The other prominent hypothesis for this disorder, largely driven by epidemiological data, is that certain adverse events during the early stages of brain development increase an individual''s risk of developing schizophrenia later in life. However, the clinical and preclinical literature consistently implicates behavioural, cognitive, and pharmacological abnormalities, implying that DA signaling is abnormal in the adult brain. How can we reconcile these two major hypotheses underlying much of the clinical and basic research into schizophrenia? In this study we have transiently knocked down tyrosine hydroxylase (TH, the rate limiting enzyme in DA synthesis) gene expression in the early stages of brain development in zebrafish using morpholinos. We show that by adulthood, TH and DA levels have returned to normal and basic DA-mediated behaviours, such as locomotion, are also normal. However, when they were exposed to a novel environment the levels of freezing and immediate positioning in deeper zones were significantly reduced in these adult fish. The neurochemistry underlying these behaviours is complex, and the exact mechanisms for these abnormal behaviours remains unknown. This study demonstrates that early transient alterations in DA ontogeny can produce persistent alterations in adult brain function and suggests that the zebrafish may be a promising model animal for future studies directed at clarifying the basic neurodevelopmental mechanisms behind complex psychiatric disease.     

Dissecting High-Dimensional Phenotypes with Bayesian Sparse Factor Analysis of Genetic Covariance Matrices

Quantitative genetic studies that model complex, multivariate phenotypes are important for both evolutionary prediction and artificial selection. For example, changes in gene expression can provide insight into developmental and physiological mechanisms that link genotype and phenotype. However, classical analytical techniques are poorly suited to quantitative genetic studies of gene expression where the number of traits assayed per individual can reach many thousand. Here, we derive a Bayesian genetic sparse factor model for estimating the genetic covariance matrix (G-matrix) of high-dimensional traits, such as gene expression, in a mixed-effects model. The key idea of our model is that we need consider only G-matrices that are biologically plausible. An organism’s entire phenotype is the result of processes that are modular and have limited complexity. This implies that the G-matrix will be highly structured. In particular, we assume that a limited number of intermediate traits (or factors, e.g., variations in development or physiology) control the variation in the high-dimensional phenotype, and that each of these intermediate traits is sparse – affecting only a few observed traits. The advantages of this approach are twofold. First, sparse factors are interpretable and provide biological insight into mechanisms underlying the genetic architecture. Second, enforcing sparsity helps prevent sampling errors from swamping out the true signal in high-dimensional data. We demonstrate the advantages of our model on simulated data and in an analysis of a published Drosophila melanogaster gene expression data set.     

Protein complexity, gene duplicability and gene dispensability in the yeast genome

Using functional genomic and protein structural data we studied the effects of protein complexity (here defined as the number of subunit types in a protein) on gene dispensability and gene duplicability. We found that in terms of gene duplicability the major distinction in protein complexity is between hetero-complexes, each of which includes at least two different types of subunits (polypeptides), and homo-complexes, which include monomers and complexes that consist of only subunits of one polypeptide type. However, gene dispensability decreases only gradually as the number of subunit types in a protein complex increases. These observations suggest that the dosage balance hypothesis can explain well gene duplicability of complex proteins, but cannot completely explain the difference in dispensabilities between hetero-complex subunits. It is likely that knocking out a gene coding for a hetero-complex subunit would disrupt the function of the whole complex, so that the deletion effect on fitness would increase with protein complexity. We also found that multi-domain polypeptide genes are less dispensable but more duplicable than single-domain polypeptide genes. Duplicate genes derived from the whole genome duplication event in yeast are more dispensable (except for ribosomal protein genes) than other duplicate genes. Further, we found that subunits of the same protein complex tend to have similar expression levels and similar effects of gene deletion on fitness. Finally, we estimated that in yeast the contribution of duplicate genes to genetic robustness against null mutation is approximately 9%, smaller than previously estimated. In yeast, protein complexity may serve as a better indicator of gene dispensability than do duplicate genes.     

Single-stranded oligonucleotide-mediated gene repair in mammalian cells has a mechanism distinct from homologous recombination repair

Single-stranded DNA oligonucleotide (SSO)-mediated gene repair has great potentials for gene therapy and functional genomic studies. However, its underlying mechanism remains unclear. Previous studies from other groups have suggested that DNA damage response via the ATM/ATR pathway may be involved in this process. In this study, we measured the effect of two ATM/ATR inhibitors caffeine and pentoxifylline on the correction efficiency in SSO-mediated gene repair. We also checked their effect on double-stranded break (DSB)-induced homologous recombination repair (HRR) as a control, which is well known to be dependent on the ATM/ATR pathway. We found these inhibitors could completely inhibit DSB-induced HRR, but could only partially inhibit SSO-mediated process, indicating SSO-mediated gene repair is not dependent on the ATM/ATR pathway. Furthermore, we found that thymidine treatment promotes SSO-mediated gene repair, but inhibits DSB-induced HRR. Collectively, our results demonstrate that SSO-mediated and DSB-induced gene repairs have distinct mechanisms.     

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation.     

Gap junctional regulation of signal transduction in bone cells

The role of gap junctions, particularly that of connexin43 (Cx43), has become an area of increasing interest in bone physiology. An abundance of studies have shown that Cx43 influences the function of osteoblasts and osteocytes, which ultimately impacts bone mass acquisition and skeletal homeostasis. However, the molecular details underlying how Cx43 regulates bone are only coming into focus and have proven to be more complex than originally thought. In this review, we focus on the diverse molecular mechanisms by which Cx43 gap junctions and hemichannels regulate cell signaling pathways, gene expression, mechanotransduction and cell survival in bone cells. This review will highlight key signaling factors that have been identified as downstream effectors of Cx43 and the impact of these pathways on distinct osteoblast and osteocyte functions.     

Joint learning of gene functions--a Bayesian network model approach

In this paper, we develop a machine learning system for determining gene functions from heterogeneous data sources using a Weighted Naive Bayesian network (WNB). The knowledge of gene functions is crucial for understanding many fundamental biological mechanisms such as regulatory pathways, cell cycles and diseases. Our major goal is to accurately infer functions of putative genes or Open Reading Frames (ORFs) from existing databases using computational methods. However, this task is intrinsically difficult since the underlying biological processes represent complex interactions of multiple entities. Therefore, many functional links would be missing when only one or two sources of data are used in the prediction. Our hypothesis is that integrating evidence from multiple and complementary sources could significantly improve the prediction accuracy. In this paper, our experimental results not only suggest that the above hypothesis is valid, but also provide guidelines for using the WNB system for data collection, training and predictions. The combined training data sets contain information from gene annotations, gene expressions, clustering outputs, keyword annotations, and sequence homology from public databases. The current system is trained and tested on the genes of budding yeast Saccharomyces cerevisiae. Our WNB model can also be used to analyze the contribution of each source of information toward the prediction performance through the weight training process. The contribution analysis could potentially lead to significant scientific discovery by facilitating the interpretation and understanding of the complex relationships between biological entities.     

mNUDC is required for plus‐end‐directed transport of cytoplasmic dynein and dynactins by kinesin‐1

Lissencephaly is a devastating neurological disorder caused by defective neuronal migration. The LIS1 (or PAFAH1B1) gene was identified as the gene mutated in lissencephaly patients, and was found to regulate cytoplasmic dynein function and localization. In particular, LIS1 is essential for anterograde transport of cytoplasmic dynein as a part of the cytoplasmic dynein–LIS1–microtubule complex in a kinesin‐1‐dependent manner. However, the underlying mechanism by which a cytoplasmic dynein–LIS1–microtubule complex binds kinesin‐1 is unknown. Here, we report that mNUDC (mammalian NUDC) interacts with kinesin‐1 and is required for the anterograde transport of a cytoplasmic dynein complex by kinesin‐1. mNUDC is also required for anterograde transport of a dynactin‐containing complex. Inhibition of mNUDC severely suppressed anterograde transport of distinct cytoplasmic dynein and dynactin complexes, whereas motility of kinesin‐1 remained intact. Reconstruction experiments clearly demonstrated that mNUDC mediates the interaction of the dynein or dynactin complex with kinesin‐1 and supports their transport by kinesin‐1. Our findings have uncovered an essential role of mNUDC for anterograde transport of dynein and dynactin by kinesin‐1.     

Molecular dynamics simulations of Gly-12-->Val mutant of p21(ras): dynamic inhibition mechanism.

The mutant p21(ras) protein is a G protein produced by the point-mutated H-ras gene, and this mutant protein has been shown to cause carcinogenesis due to a reduction in its GTPase activity. However, the mechanism underlying this strange phenomenon has still not been elucidated. In our previous study, we have clarified the mechanism of the GTP-->GDP hydrolysis reaction in the wild-type p21(ras) at the atomic level and concluded that GTPase-activating protein plays a significant role in the supply of H2O molecules for the hydrolysis. The structure of the active site in the mutant is the same as that in the wild type. However, by performing molecular dynamic calculations, we found that the structure of the active site of the enzyme substrate complex in the oncogenic mutant p21(ras) continuously changes, and these continuous changes in the active site would make it difficult for the GTP-->GDP hydrolysis reaction to occur in the mutant. These findings can explain the fact that the GTPase activity in the mutant was only 15% of that in the wild type and the fact that GTPase-activating protein has no reaction-activating effect in the mutant. This is a dynamic inhibition mechanism of a vital reaction that can be explained by considering the molecular dynamics.     

Programs of Gene Expression During the Laying Down of Memory Formation as Revealed by DNA Microarrays

Many experiments in the past have demonstrated the requirement of de novo gene expression during memory formation. In contrast to the initial reductionistic view that genes relevant to learning and memory would be easily found and would provide a simple key to understand this brain function, it is becoming apparent that the genetic contribution to memory is complex. Previous approaches have been focused on individual genes or genetic pathways and failed to address the massively parallel nature of genome activities and collective behavior of the genes that ultimately control the molecular mechanisms underlying brain function. In view of the broad variety of genes and the cross talk of genetic pathways involved in this regulation, only gene expression profiles may reflect the complete behavior of regulatory pathways. In this review we illustrate how DNA microarray-based gene expression profiling may help to dissect and analyze the complex mechanisms involved in gene regulation during the acquisition and storage of memory in the mammalian brain.     

Gene set analysis of genome-wide association studies: methodological issues and perspectives

Recent studies have demonstrated that gene set analysis, which tests disease association with genetic variants in a group of functionally related genes, is a promising approach for analyzing and interpreting genome-wide association studies (GWAS) data. These approaches aim to increase power by combining association signals from multiple genes in the same gene set. In addition, gene set analysis can also shed more light on the biological processes underlying complex diseases. However, current approaches for gene set analysis are still in an early stage of development in that analysis results are often prone to sources of bias, including gene set size and gene length, linkage disequilibrium patterns and the presence of overlapping genes. In this paper, we provide an in-depth review of the gene set analysis procedures, along with parameter choices and the particular methodology challenges at each stage. In addition to providing a survey of recently developed tools, we also classify the analysis methods into larger categories and discuss their strengths and limitations. In the last section, we outline several important areas for improving the analytical strategies in gene set analysis.     

Meta-analysis for microarray studies of the genetics of complex traits

In comparison to other complex disease traits, alcoholism and alcohol abuse are influenced by the combined effects of many genes that alter susceptibility, phenotypic expression and associated morbidity, respectively. Many genetic studies, in both animal models and humans, have identified genetic intervals containing genes that influence alcoholism or behavioral responses to ethanol. Concurrently, a growing number of microarray studies have identified gene expression differences related to ethanol drinking or other ethanol behaviors. However, concerns about the statistical power of these experiments, combined with the complexity of the underlying phenotypes, have greatly hampered the identification of candidate genes underlying ethanol behaviors. Meta-analysis approaches using recent compilations of large datasets of microarray, behavioral and genetic data promise improved statistical power for detecting the genes or gene networks affecting ethanol behaviors and other complex traits.     

Mechanism of activation of methyltransferases involved in translation by the Trm112 'hub' protein

Methylation is a common modification encountered in DNA, RNA and proteins. It plays a central role in gene expression, protein function and mRNA translation. Prokaryotic and eukaryotic class I translation termination factors are methylated on the glutamine of the essential and universally conserved GGQ motif, in line with an important cellular role. In eukaryotes, this modification is performed by the Mtq2-Trm112 holoenzyme. Trm112 activates not only the Mtq2 catalytic subunit but also two other tRNA methyltransferases (Trm9 and Trm11). To understand the molecular mechanisms underlying methyltransferase activation by Trm112, we have determined the 3D structure of the Mtq2-Trm112 complex and mapped its active site. Using site-directed mutagenesis and in vivo functional experiments, we show that this structure can also serve as a model for the Trm9-Trm112 complex, supporting our hypothesis that Trm112 uses a common strategy to activate these three methyltransferases.