A genome wide analysis of ubiquitin ligases in APP processing identifies a novel regulator of BACE1 mRNA levels

Defining a standard and weighted mathematical index for maturation of dendritic cells

The concept of dendritic cell (DC) maturation generally refers to the changes in morphology and function of DCs. Conventionally, DC maturity is based on three criteria: loss of endocytic ability, gain of high-level capacity to present antigens and induce proliferation of T cells, and mobility of DCs toward high concentrations of CCL19. Impairment of DC maturation has been suggested as the main reason for infectivity or chronicity of several infectious agents. In the case of hepatitis C virus, this has been a matter of controversy for the last two decades. However, insufficient attention has been paid to the method of ex vivo maturation as the possible source of such controversies. We previously reported striking differences between DCs matured with different methods, so we propose the use of a standard quantitative index to determine the level of maturity in DCs as an approach to compare results from different studies. We designed and formulated a mathematically calculated index to numerically define the level of maturity based on experimental data from ex vivo assays. This introduces a standard maturation index (SMI) and weighted maturation index (WMI) based on strictly standardized mean differences between different methods of generating mature DCs. By calculating an SMI and a WMI, numerical values were assigned to the level of maturity achieved by DCs matured with different methods. SMI and WMI could be used as a standard tool to compare diversely generated mature DCs and so better interpret outcomes of ex vivo and in vivo studies with mature DCs.

A New Method with Flexible and Balanced Control of False Negatives and False Positives for Hit Selection in RNA Interference High-Throughput Screening Assays

The z-score method and its variants for testing mean difference are commonly used for hit selection in high-throughput screening (HTS) assays. Strictly standardized mean difference (SSMD) offers a way to measure and classify the short interfering RNA (siRNA) effects. In this article, based on SSMD, the authors propose a new testing method for hit selection in RNA interference (RNAi) HTS assays. This SSMD-based method allows the differentiation between siRNAs with large and small effects on the assay output and maintains flexible and balanced control of both the false-negative rate, in which the siRNAs with strong effects are not selected as hits, and the restricted false-positive rate, in which the siRNAs with weak or no effects are selected as hits. This method directly addresses the size of siRNA effects represented by the strength of difference between an siRNA and a negative reference, whereas the classic z-score method and t-test of testing no mean difference address whether the mean of an siRNA is exactly the same as the mean of a negative reference. This method can readily control the false-negative rate, whereas it is nontrivial for the classic z-score method and t-test to control the false-negative rate. Therefore, theoretically, the SSMD-based method offers better control of the sizes of siRNA effects and the associated false-positive and false-negative rates than the commonly used z-score method and t-test for hit selection in HTS assays. The SSMD-based method should generally be applicable to any assay in which the end point is a difference in signal compared to a reference sample, including those for RNAi, receptor, enzyme, and cellular function. (Journal of Biomolecular Screening 2007:645-655)

Roles of Prolyl Isomerases in RNA-Mediated Gene Expression

The peptidyl-prolyl cis-trans isomerases (PPIases) that include immunophilins (cyclophilins and FKBPs) and parvulins (Pin1, Par14, Par17) participate in cell signaling, transcription, pre-mRNA processing and mRNA decay. The human genome encodes 19 cyclophilins, 18 FKBPs and three parvulins. Immunophilins are receptors for the immunosuppressive drugs cyclosporin A, FK506, and rapamycin that are used in organ transplantation. Pin1 has also been targeted in the treatment of Alzheimer’s disease, asthma, and a number of cancers. While these PPIases are characterized as molecular chaperones, they also act in a nonchaperone manner to promote protein-protein interactions using surfaces outside their active sites. The immunosuppressive drugs act by a gain-of-function mechanism by promoting protein-protein interactions in vivo. Several immunophilins have been identified as components of the spliceosome and are essential for alternative splicing. Pin1 plays roles in transcription and RNA processing by catalyzing conformational changes in the RNA Pol II C-terminal domain. Pin1 also binds several RNA binding proteins such as AUF1, KSRP, HuR, and SLBP that regulate mRNA decay by remodeling mRNP complexes. The functions of ribonucleoprotein associated PPIases are largely unknown. This review highlights PPIases that play roles in RNA-mediated gene expression, providing insight into their structures, functions and mechanisms of action in mRNP remodeling in vivo.

The emerging role of peptidyl-prolyl isomerase chaperones in tau oligomerization, amyloid processing, and Alzheimer's disease

Peptidyl-prolyl cis/trans isomerases (PPIases), a unique family of molecular chaperones, regulate protein folding at proline residues. These residues are abundant within intrinsically disordered proteins, like the microtubule-associated protein tau. Tau has been shown to become hyperphosphorylated and accumulate as one of the two main pathological hallmarks in Alzheimer's disease, the other being amyloid beta (Ab). PPIases, including Pin1, FK506-binding protein (FKBP) 52, FKBP51, and FKBP12, have been shown to interact with and regulate tau biology. This interaction is particularly important given the numerous proline-directed phosphorylation sites found on tau and the role phosphorylation has been found to play in pathogenesis. This regulation then affects downstream aggregation and oligomerization of tau. However, many PPIases have yet to be explored for their effects on tau biology, despite the high likelihood of interaction based on proline content. Moreover, Pin1, FKBP12, FKBP52, cyclophilin (Cyp) A, CypB, and CypD have been shown to also regulate Ab production or the toxicity associated with Ab pathology. Therefore, PPIases directly and indirectly regulate pathogenic protein multimerization in Alzheimer's disease and represent a family rich in targets for modulating the accumulation and toxicity.

Multidomain Peptidyl Prolyl cis/trans Isomerases

BACKGROUND

Peptidyl prolyl cis/trans isomerases (PPIases) assist the folding and restructuring of client proteins by catalysis of the slow rotational motion of peptide bonds preceding a proline residue. Catalysis is performed by relatively small, distinct protein domains of 10 to 18kDa for all PPIase families. PPIases are involved in a wide variety of physiological and pathophysiological processes like signal transduction, cell differentiation, apoptosis as well as viral, bacterial and parasitic infection.

SCOPE OF REVIEW

There are multidomain PPIases consisting of one to up to four catalytic domains of the respective PPIase family supplemented by N- or C-terminal extensions. This review examines the biochemical and functional properties of the members of the PPIase class of enzymes which contain additional protein domains with defined biochemical functions.

MAJOR CONCLUSIONS

The versatile domain architecture of multidomain PPIases is important for the control of enzyme specificity and organelle-specific targeting, the establishment of molecular connections and hence the coordination of PPIase functions across the cellular network.

GENERAL SIGNIFICANCE

Accessory domains covalently linked to a PPIase domain supply an additional layer of control to the catalysis of prolyl isomerization in specific client proteins. Understanding these control mechanisms will provide new insights into the physiological mode of action of the multidomain PPIases and their ability to form therapeutic targets. This article is part of a Special Issue entitled Proline-directed Foldases: Cell Signaling Catalysts and Drug Targets.

RVG-peptide-linked trimethylated chitosan for delivery of siRNA to the brain

In this work, a peptide derived from the rabies virus glycoprotein (RVG) was linked to siRNA/trimethylated chitosan (TMC) complexes through bifunctional PEG for efficient brain-targeted delivery of siRNA. The physiochemical properties of the complexes, such as siRNA complexing ability, size and ζ potential, morphology, serum stability, and cytotoxicity, were investigated prior to studying the cellular uptake, in vitro gene silencing efficiency, and in vivo biodistribution. The RVG-peptide-linked siRNA/TMC-PEG complexes showed increased serum stability, negligible cytotoxicity, and higher cellular uptake than the unmodified siRNA/TMC-mPEG complexes in acetylcholine receptor positive Neuro2a cells. The potent knockdown of BACE1, a therapeutic target in Alzheimer's disease, demonstrated the gene silencing efficiency. In vivo imaging analysis showed significant accumulation of Cy5-siRNA in the isolated brain of mice injected with RVG-peptide-linked complexes. Therefore, the RVG-peptide-linked TMC-PEG developed in this study can be used as a potential carrier for delivery of siRNA to the brain.

Viable mouse gene ablations that robustly alter brain Aβ levels are rare

BACKGROUND

Accumulation of amyloid-β (Aβ) peptide in the brain is thought to play a key pathological role in Alzheimer's disease. Many pharmacological targets have therefore been proposed based upon the biochemistry of Aβ, but not all are equally tractable for drug discovery.

RESULTS

To search for novel targets that affect brain Aβ without causing toxicity, we screened mouse brain samples from 1930 novel gene knock-out (KO) strains, representing 1926 genes, using Aβ ELISA assays. Although robust Aβ lowering was readily apparent in brains from a BACE1 KO strain, none of the novel strains exhibited robust decreases in brain Aβ, including a GPR3 KO strain, which had previously been proposed as an Aβ target. However, significantly increased Aβ was observed in brain samples from two KO strains, corresponding to genes encoding the glycosylphosphatidylinositol mannosyl transferase PIGZ and quinolinate phosphoribosyltransferase (QPRT).

CONCLUSIONS

Thus, gene ablations that are permissive for mouse survival and that also have a robust effect on Aβ levels in the brain are rare.

Ancient origin of animal U-box ubiquitin ligases

Background

The patterns of emergence and diversification of the families of ubiquitin ligases provide insights about the evolution of the eukaryotic ubiquitination system. U-box ubiquitin ligases (UULs) are proteins characterized by containing a peculiar protein domain known as U box. In this study, the origin of the animal UUL genes is described.

Results

Phylogenetic and structural data indicate that six of the seven main UUL-encoding genes found in humans (UBE4A, UBE4B, UIP5, PRP19, CHIP and CYC4) were already present in the ancestor of all current metazoans and the seventh (WDSUB1) is found in placozoans, cnidarians and bilaterians. The fact that only 4 - 5 genes orthologous to the human ones are present in the choanoflagellate Monosiga brevicollis suggests that several animal-specific cooptions of the U box to generate new genes occurred. Significantly, Monosiga contains five additional UUL genes that are not present in animals. One of them is also present in distantly-related protozoans. Along animal evolution, losses of UUL-encoding genes are rare, except in nematodes, which lack three of them. These general patterns are highly congruent with those found for other two families (RBR, HECT) of ubiquitin ligases.

Conclusions

Finding that the patterns of emergence, diversification and loss of three unrelated families of ubiquitin ligases (RBR, HECT and U-box) are parallel indicates that there are underlying, linage-specific evolutionary forces shaping the complexity of the animal ubiquitin system.

The use of SSMD-based false discovery and false nondiscovery rates in genome-scale RNAi screens

In genome-scale RNA interference (RNAi) screens, it is critical to control false positives and false negatives statistically. Traditional statistical methods for controlling false discovery and false nondiscovery rates are inappropriate for hit selection in RNAi screens because the major goal in RNAi screens is to control both the proportion of short interfering RNAs (siRNAs) with a small effect among selected hits and the proportion of siRNAs with a large effect among declared nonhits. An effective method based on strictly standardized mean difference (SSMD) has been proposed for statistically controlling false discovery rate (FDR) and false nondiscovery rate (FNDR) appropriate for RNAi screens. In this article, the authors explore the utility of the SSMD-based method for hit selection in RNAi screens. As demonstrated in 2 genome-scale RNAi screens, the SSMD-based method addresses the unmet need of controlling for the proportion of siRNAs with a small effect among selected hits, as well as controlling for the proportion of siRNAs with a large effect among declared nonhits. Furthermore, the SSMD-based method results in reasonably low FDR and FNDR for selecting inhibition or activation hits. This method works effectively and should have a broad utility for hit selection in RNAi screens with replicates.

High-throughput screening using siRNA (RNAi) libraries

RNA interference (RNAi) has become one of the most important research tools in functional genomics analysis ever since the discovery of the phenomenon. The robustness of the method has enabled construction of RNAi libraries in the forms of long double-stranded RNA or short-interfering RNA that can cover the whole or significant parts of the genomes of different organisms. Over the last few years, such libraries have been used in different high-throughput formats to establish functional links between genes and phenotypes. In this review, available RNAi library resources and application of these strategic tools will be discussed.

Novel analytic criteria and effective plate designs for quality control in genome-scale RNAi screens

One of the most fundamental challenges in genome-wide RNA interference (RNAi) screens is to glean biological significance from mounds of data, which relies on the development and adoption of appropriate analytic methods and designs for quality control (QC) and hit selection. Currently, a Z-factor-based QC criterion is widely used to evaluate data quality. However, this criterion cannot take into account the fact that different positive controls may have different effect sizes and leads to inconsistent QC results in experiments with 2 or more positive controls with different effect sizes. In this study, based on a recently proposed parameter, strictly standardized mean difference (SSMD), novel QC criteria are constructed for evaluating data quality in genome-wide RNAi screens. Two good features of these novel criteria are: (1) SSMD has both clear original and probability meanings for evaluating the differentiation between positive and negative controls and hence the SSMD-based QC criteria have a solid probabilistic and statistical basis, and (2) these QC criteria obtain consistent QC results for multiple positive controls with different effect sizes. In addition, I propose multiple plate designs and the guidelines for using them in genome-wide RNAi screens. Finally, I provide strategies for using the SSMD-based QC criteria and effective plate design together to improve data quality. The novel SSMD-based QC criteria, effective plate designs, and related guidelines and strategies may greatly help to obtain high quality of data in genome-wide RNAi screens.

Hit selection with false discovery rate control in genome-scale RNAi screens

RNA interference (RNAi) is a modality in which small double-stranded RNA molecules (siRNAs) designed to lead to the degradation of specific mRNAs are introduced into cells or organisms. siRNA libraries have been developed in which siRNAs targeting virtually every gene in the human genome are designed, synthesized and are presented for introduction into cells by transfection in a microtiter plate array. These siRNAs can then be transfected into cells using high-throughput screening (HTS) methodologies. The goal of RNAi HTS is to identify a set of siRNAs that inhibit or activate defined cellular phenotypes. The commonly used analysis methods including median +/- kMAD have issues about error rates in multiple hypothesis testing and plate-wise versus experiment-wise analysis. We propose a methodology based on a Bayesian framework to address these issues. Our approach allows for sharing of information across plates in a plate-wise analysis, which obviates the need for choosing either a plate-wise or experimental-wise analysis. The proposed approach incorporates information from reliable controls to achieve a higher power and a balance between the contribution from the samples and control wells. Our approach provides false discovery rate (FDR) control to address multiple testing issues and it is robust to outliers.

Genome-wide screens for effective siRNAs through assessing the size of siRNA effects

Background

RNA interference (RNAi) has been seen as a revolution in functional genomics and system biology. Genome-wide RNAi research relies on the development of RNAi high-throughput screening (HTS) assays. One of the most fundamental challenges in RNAi HTS is to glean biological significance from mounds of data, which relies on the development of effective analytic methods for selecting effective small interfering RNAs (siRNAs).

Findings

Based on a recently proposed parameter, strictly standardized mean difference (SSMD), I propose an analytic method for genome-wide screens of effective siRNAs through assessing and testing the size of siRNA effects. Central to this method is the capability of SSMD in quantifying siRNA effects. This method has relied on normal approximation, which works only in the primary screens but not in the confirmatory screens. In this paper, I explore the non-central t-distribution property of SSMD estimates and use this property to extend the SSMD-based method so that it works effectively in either primary or confirmatory screens as well as in any HTS screens with or without replicates. The SSMD-based method maintains a balanced control of false positives and false negatives.

Conclusion

The central interest in genome-wide RNAi research is the selection of effective siRNAs which relies on the development of analytic methods to measure the size of siRNA effects. The new analytic method for hit selection provided in this paper offers a good analytic tool for selecting effective siRNAs, better than current analytic methods, and thus may have broad utility in genome-wide RNAi research.

Integrating experimental and analytic approaches to improve data quality in genome-wide RNAi screens

RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research.

The use of strictly standardized mean difference for hit selection in primary RNA interference high-throughput screening experiments

RNA interference (RNAi) high-throughput screening (HTS) has been hailed as the 2nd genomics wave following the 1st genomics wave of gene expression microarrays and single-nucleotide polymorphism discovery platforms. Following an RNAi HTS, the authors are interested in identifying short interfering RNA (siRNA) hits with large inhibition/activation effects. For hit selection, the z-score method and its variants are commonly used in primary RNAi HTS experiments. Recently, strictly standardized mean difference (SSMD) has been proposed to measure the siRNA effect represented by the magnitude of difference between an siRNA and a negative reference group. The links between SSMD and d+-probability offer a clear interpretation of siRNA effects from a probability perspective. Hence, SSMD can be used as a ranking metric for hit selection. In this article, the authors investigated both the SSMD-based testing process and the use of SSMD as a ranking metric for hit selection in 2 primary siRNA HTS experiments. The analysis results showed that, as a ranking metric, SSMD was more stable and reliable than percentage inhibition and led to more robust hit selection results. Using the SSMD -based testing method, the false-negative rate can more readily be obtained. More important, the use of the SSMD-based method can result in a reduction in both the false-negative and false-positive rates. The applications presented in this article demonstrate that the SSMD method addresses scientific questions and fills scientific needs better than both percentage inhibition and the commonly used z-score method for hit selection.