Rapid identification of improved protein ligands using peptoid microarrays

A rapid array-based protocol is presented by which a modest affinity protein-binding small molecule can be appended to a library of peptoids via click chemistry. The array can then be screened for improved ligands that exhibit a higher affinity for the protein target.     

Profiling microRNA expression with microarrays

The discovery of several types of small RNAs (sRNAs) has led to a steady increase in available RNA databases. Many of these sRNAs remain to be validated and functionally characterized. Recent advances in microRNA (miRNA)-expression profiling of different tissues, stages of development and physiological or pathological states are beginning to be explored using several technological approaches. In this review, these recent advances in miRNA microarray technology and their applications, particularly in basic research and clinical diagnosis, will be summarized and discussed. The methods for miRNA enrichment and probe design and labeling will also be discussed with an emphasis on evaluation of predicted miRNA sequences, analysis of miRNA expression and exploration of the potential roles of miRNA sequences in the regulation of stem cell differentiation and tissue- and time-specific profiling patterns of their target genes.     

A precursor microRNA in a cancer cell nucleus

In line with their broad-based effects, microRNAs (miRNAs), small non-coding RNA molecules ~22 nucleotides long that silence target mRNAs, are thought to act as oncogenes or tumor suppressor genes based on their inhibition of tumor-suppressive and oncogenic mRNAs, respectively. We and others previously showed that global downregulation of miRNAs, a common feature of human tumors, is functionally relevant to oncogenesis as impairment of miRNA biogenesis enhanced transformation in both cancer cells and a K-Ras-driven model of lung cancer. The dysregulation of miRNA biosynthesis in cancer emerges as a cancer-specific mechanism that enhances its tumorigenic capacity. These observations are further supported by the fact that frameshift mutations of TARBP2 occur in sporadic and hereditary carcinomas with microsatellite instability and that DICER1 mutations are associated with familial pleuropulmonary blastoma. Accordingly, it was reported that reduced expression of miRNA-processing factors is associated with poor prognosis in lung cancer and ovarian cancer. Recently we have also demonstrated the presence of Exportin 5 (XPO5) inactivating mutations in tumors with microsatellite instability. This observed genetic defect is responsible for nuclear retention of pre-miRNAs, thereby reducing miRNA processing. The characterized mutant form of the XPO5 protein lacks a C-terminal region that contributes to the formation of the pre-miRNA/XPO5/Ran-GTP ternary complex and the protein itself, as well as pre-miRNAs accumulating in the nucleus of cancer cells. Most importantly, the restoration of XPO5 function reverses the impaired export of pre-miRNAs and has tumor suppressor features. Our data suggest a cancer-specific mechanism to guide the subcellular distribution of miRNA precursors and prevent them from being processed to the active mature miRNA. The control of the miRNA biosynthesis pathway is emerging as an important mechanism in defining the spatiotemporal pattern of miRNA expression in cancer cells.     

Discovering novel ligands for macromolecules using X-ray crystallographic screening

The need to decrease the time scale for clinical compound discovery has led to innovations at several stages in the process, including genomics/proteomics for target identification, ultrahigh-throughput screening for lead identification, and structure-based drug design and combinatorial chemistry for lead optimization. A critical juncture in the process is the identification of a proper lead compound, because a poor choice may generate costly difficulties at later stages. Lead compounds are commonly identified from high-throughput screens of large compound libraries, derived from known substrates/inhibitors, or identified in computational prescreeusing X-ray crystal structures. Structural information is often consulted to efficiently optimize leads, but under the current paradigm, such data require preidentification and confirmation of compound binding. Here, we describe a new X-ray crystallography-driven screening technique that combines the steps of lead identification, structural assessment, and optimization. The method is rapid, efficient, and high-throughput, and it results in detailed crystallographic structure information. The utility of the method is demonstrated in the discovery and optimization of a new orally available class of urokinase inhibitors for the treatment of cancer.     

Discovering peptide ligands using epitope libraries.

Epitope libraries are large collections of peptides. Each peptide is displayed on the surface of a bacteriophage particle and is encoded by a randomly mutated region of the phage genome, thus associating each unique peptide with the DNA molecule encoding it. Antibodies and other binding proteins are used to select specifically for rare, phage-bearing peptide ligands; sequencing of the corresponding viral DNA will reveal their amino acid sequences. Relatively high-affinity peptides for a variety of peptide- and non-peptide-binding ligates have been affinity-isolated from epitope libraries. This technology has been used to map epitopes on proteins and to find peptide mimics for non-peptide-binding ligates. The current challenge lies in developing epitope library technology so that tight-binding peptide ligands can be detected for a wider variety of ligates, including those that recognize folded proteins. Should this be accomplished, many powerful applications can be envisioned in the areas of drug design and the development of diagnostic markers and vaccines.     

Purification of animal immunoglobulin G (IgG) using peptoid affinity ligands

The availability of highly pure animal antibodies is critical in the production of diagnostic tools and biosensors. The peptoid PL16, previously isolated from an ensemble of peptoid variants of the IgG-binding peptide HWRGWV, was utilized in this work as affinity ligand on WorkBeads resin for the purification of immunoglobulin G (IgG) from a variety of mammalian sources and chicken immunoglobulin Y (IgY). The chromatographic protocol initially optimized for murine serum and ascites was subsequently employed for processing rabbit, goat and sheep, donkey, llama, and chicken sera. The PL16-WorkBeads resin proved able to recover all antibody targets with values of yield between 50 and 90%, and purity consistently above 90%. Notably, PL16 not only binds a broader spectrum of animal immunoglobulins than the reference ligands Protein A and G, but it also binds equally well with all their subclasses. Unlike the protein ligands, in fact, PL16 afforded excellent values of yield and purity of mammalian polyclonal IgG, namely murine (47 and 94%), rabbit (66.5 and 91.7%), caprine IgG (63 and 91–95%), donkey, and llama (93 and 97%), as well as chicken IgY (42 and 92%). Of notice, it is also the ability of PL16 to target monomeric IgG without binding aggregated IgG; when challenged with a mixture of monomeric and aggregated murine IgG, PL16 eluted <3% of fed aggregates, against 11–13% eluted by Protein A and G. Collectively, these results prove the potential of the proposed peptoid ligand for large-scale purification of animal immunoglobulins.     

The Phaseolus vulgaris miR159a precursor encodes a second differentially expressed microRNA

Plant microRNAs originate from a stem-loop structured single-stranded RNA precursor. Each stem-loop is processed to generate a mature microRNA that is recruited to an ARGONAUTE-containing multi-protein complex to direct silencing of its target mRNA. Here we report that the conserved plant miR159a precursor produces a second 21-nt long RNA with the properties of a microRNA. Its presence in different plant species is supported by its conservation in the stem-loop position and expression as determined by northern blot analysis. We show that successive processing by DCL1 produces this novel microRNA from the same precursor as miR159a. In contrast to the low levels observed in other plant models for the equivalent of miR159.2, in P. vulgaris, the accumulation of miR159.2 is easily detectable and when compared to miR159a, their expression patterns are distinct in different organs and growth conditions. Further evidence of the functionality of miR159.2 comes from its association with silencing complexes as demonstrated by co-immunoprecipitation experiments using an AGO1-specific antibody and processing of an artificial GFP reporter construct containing a complementary target sequence. These results indicate that the second small RNA corresponds to a microRNA, at least partially independent of miR159 activity, and that in plants a miRNA precursor may encode multiple regulatory small RNAs.     

MCPIP1 ribonuclease antagonizes dicer and terminates microRNA biogenesis through precursor microRNA degradation

MicroRNAs (miRNAs) are versatile regulators of gene expression and undergo complex maturation processes. However, the mechanism(s) stabilizing or reducing these small RNAs remains poorly understood. Here we identify mammalian immune regulator MCPIP1 (Zc3h12a) ribonuclease as a broad suppressor of miRNA activity and biogenesis, which counteracts Dicer, a central ribonuclease in miRNA processing. MCPIP1 suppresses miRNA biosynthesis via cleavage of the terminal loops of precursor miRNAs (pre-miRNAs). MCPIP1 also carries a vertebrate-specific oligomerization domain important for pre-miRNA recognition, indicating its recent evolution. Furthermore, we observed potential antagonism between MCPIP1 and Dicer function in human cancer and found a regulatory role of MCPIP1 in the signaling axis comprising miR-155 and its target c-Maf. These results collectively suggest that the balance between processing and destroying ribonucleases modulates miRNA biogenesis and potentially affects pathological miRNA dysregulation. The presence of this abortive processing machinery and diversity of MCPIP1-related genes may imply a dynamic evolutional transition of the RNA silencing system.     

A combinatorial peptoid library for the identification of novel MSH and GRP/bombesin receptor ligands

A tripeptoid library was synthesized using 69 different primary amines in initially 69 individual reactions by the mix and split approach. The resulting library consisted of 328,509 (69(3)) single compounds, divided in 69 subpools each containing 4,761 entities. The 69 subpools were tested in two binding assays, one for alpha-MSH (alpha-melanotropin) and one for GRP (gastrin-releasing peptide)/bombesin. The sublibraries with the highest affinity to the MSH receptor (i.e. melanocortin type 1 or MC1 receptor) and, respectively, the GRP-preferring bombesin receptor were identified by an iterative process. Individual tripeptoids with good binding activity were resynthesized, analyzed and their dissociation constants and biological activity determined. The KD of the most potent MC1 receptor ligand was 1.58 mumol/l and that of the GRP-preferring bombesin receptor 3.40 mumol/l. Extension of this latter tripeptoid structure whose KD value increased to 280 nmol/l. A similar increase in activity was not observed with the most potent MSH tripeptoid ligand when extended by one residue, but a compound suitable for radioiodination and lacking the N-terminal amino group had a slightly higher binding activity than the tripeptoids (KD approximately 850 nmol/l). These results demonstrate that testing a peptoid library containing 328,509 single compounds led to the successful identification of new ligands for both the MC1 receptor as well as the GRP-preferring bombesin receptor.     

Real-time PCR quantification of precursor and mature microRNA

microRNAs (miRNAs) are challenging molecules to amplify by PCR because the miRNA precursor consists of a stable hairpin and the mature miRNA is roughly the size of a standard PCR primer. Despite these difficulties, successful real-time RT-PCR technologies have been developed to amplify and quantify both the precursor and mature microRNA. An overview of real-time PCR technologies developed by us to detect precursor and mature microRNAs is presented here. Protocols describe presentation of the data using relative (comparative C(T)) and absolute (standard curve) quantification. Real-time PCR assays were used to measure the time course of precursor and mature miR-155 expression in monocytes stimulated by lipopolysaccharide. Protocols are provided to configure the assays as low density PCR arrays for high throughput gene expression profiling. By profiling over 200 precursor and mature miRNAs in HL60 cells induced to differentiate with 12-O-tetradecanoylphorbol-13-acetate, it was possible to identify miRNAs who's processing is regulated during differentiation. Real-time PCR has become the gold standard of nucleic acid quantification due to the specificity and sensitivity of the PCR. Technological advancements have allowed for quantification of miRNA that is of comparable quality to more traditional RNAs.     

TRBP alters human precursor microRNA processing in vitro

MicroRNAs play central roles in controlling gene expression in human cells. Sequencing data show that many miRNAs are produced at different levels and as multiple isoforms that can vary in length at their 5′ or 3′ ends, but the biogenesis and functional significance of these RNAs are largely unknown. We show here that the human trans-activation response (TAR) RNA binding protein (TRBP), a known molecular partner of the miRNA processing enzyme Dicer, changes the rates of pre-miRNA cleavage in an RNA-structure-specific manner. Furthermore, TRBP can trigger the generation of iso-miRNAs (isomiRs) that are longer than the canonical sequence by one nucleotide. We show that this change in miRNA processing site can alter guide strand selection, resulting in preferential silencing of a different mRNA target. These results implicate TRBP as a key regulator of miRNA processing and targeting in humans.     

Stripping custom microRNA microarrays and the lessons learned about probe-slide interactions

Microarrays have been used extensively in gene expression profiling and genotyping studies. To reduce the high cost and enhance the consistency of microarray experiments, it is often desirable to strip and reuse microarray slides. Our genome-wide analysis of microRNA expression involves the hybridization of fluorescently labeled nucleic acids to custom-made, spotted DNA microarrays based on GAPSII-coated slides. We describe here a simple and effective method to regenerate such custom microarrays that uses a very low-salt buffer to remove labeled nucleic acids from microarrays. Slides can be stripped and reused multiple times without significantly compromising data quality. Moreover, our analyses of the performance of regenerated slides identifies parameters that influence the attachment of oligonucleotide probes to GAPSII slides, shedding light on the interactions between DNA and the microarray surface and suggesting ways in which to improve the design of oligonucleotide probes.     

Computational identification of microRNA gene loci and precursor microRNA sequences in CHO cell lines

MicroRNAs (miRNAs) have recently entered Chinese hamster ovary (CHO) cell culture technology, due to their severe impact on the regulation of cellular phenotypes. Applications of miRNAs that are envisioned range from biomarkers of favorable phenotypes to cell engineering targets. These applications, however, require a profound knowledge of miRNA sequences and their genomic organization, which exceeds the currently available information of ~400 conserved mature CHO miRNA sequences. Based on these recently published sequences and two independent CHO-K1 genome assemblies, this publication describes the computational identification of CHO miRNA genomic loci. Using BLAST alignment, 415 previously reported CHO miRNAs were mapped to the reference genomes, and subsequently assigned to a distinct genomic miRNA locus. Sequences of the respective precursor-miRNAs were extracted from both reference genomes, folded in silico to verify correct structures and cross-compared. In the end, 212 genomic loci and pre-miRNA sequences representing 319 expressed mature miRNAs (approximately 50% of miRNAs represented matching pairs of 5' and 3' miRNAs) were submitted to the miRBase miRNA repository. As a proof-of-principle for the usability of the published genomic loci, four likely polycistronic miRNA cluster were chosen for PCR amplification using CHO-K1 and DHFR (-) genomic DNA. Overall, these data on the genomic context of miRNA expression in CHO will simplify the development of tools employing stable overexpression or deletion of miRNAs, allow the identification of miRNA promoters and improve detection methods such as microarrays.     

MiRANN: a reliable approach for improved classification of precursor microRNA using Artificial Neural Network model

MicroRNA (miRNA) is a special class of short noncoding RNA that serves pivotal function of regulating gene expression. The computational prediction of new miRNA candidates involves various methods such as learning methods and methods using expression data. This article has proposed a reliable model - miRANN which is a supervised machine learning approach. MiRANN used known pre-miRNAs as positive set and a novel negative set from human CDS regions. The number of known miRNAs is now huge and diversified that could cover almost all characteristics of unknown miRNAs which increases the quality of the result (99.9% accuracy, 99.8% sensitivity, 100% specificity) and provides a more reliable prediction. MiRANN performs better than other state-of-the-art approaches and declares to be the most potential tool to predict novel miRNAs. We have also tested our result using a previous negative set. MiRANN, opens new ground using ANN for predicting pre-miRNAs with a promise of better performance.