Volatility in mRNA secondary structure as a design principle for antisense

Post-transcriptional modification of m6A methylase METTL3 regulates ERK-induced androgen-deprived treatment resistance prostate cancer

As the most common modification of RNA, N⁶-methyladenosin (m⁶A) has been confirmed to be involved in the occurrence and development of various cancers. However, the relationship between m⁶A and castration resistance prostate cancer (CRPC), has not been fully studied. By m⁶A-sequencing of patient cancer tissues, we identified that the overall level of m⁶A in CRPC was up-regulated than castration sensitive prostate cancer (CSPC). Based on the analysis of m⁶A-sequencing data, we found m⁶A modification level of HRas proto-oncogene, GTPase (HRAS) and mitogen-activated protein kinase kinase 2 (MEK2 or MAP2K2) were enhanced in CRPC. Specifically, tissue microarray analysis and molecular biology experiments confirmed that METTL3, an m⁶A "writer" up-regulated after castration, activated the ERK pathway to contribute to malignant phenotype including ADT resistance, cell proliferation and invasion. We revealed that METTL3-mediated ERK phosphorylation by stabilizing the transcription of HRAS and positively regulating the translation of MEK2. In the Enzalutamide-resistant (Enz-R) C4-2 and LNCap cell line (C4-2^R, LNCap^R) established in the current study, the ERK pathway was confirmed to be regulated by METTL3. We also found that applying antisense oligonucleotides (ASOs) to target the METTL3/ERK axis can restore Enzalutamide resistance in vitro and in vivo. In conclusion, METTL3 activated the ERK pathway and induced the resistance to Enzalutamide by regulating the m⁶A level of critical gene transcription in the ERK pathway.

Analysis of human total antibody repertoires in TIF1γ autoantibody positive dermatomyositis

We investigate the accumulated microbial and autoantigen antibody repertoire in adult-onset dermatomyositis patients sero-positive for TIF1γ (TRIM33) autoantibodies. We use an untargeted high-throughput approach which combines immunoglobulin disease-specific epitope-enrichment and identification of microbial and human antigens. We observe antibodies recognizing a wider repertoire of microbial antigens in dermatomyositis. Antibodies recognizing viruses and Poxviridae family species are significantly enriched. The identified autoantibodies recognise a large portion of the human proteome, including interferon regulated proteins; these proteins cluster in specific biological processes. In addition to TRIM33, we identify autoantibodies against eleven further TRIM proteins, including TRIM21. Some of these TRIM proteins share epitope homology with specific viral species including poxviruses. Our data suggest antibody accumulation in dermatomyositis against an expanded diversity of microbial and human proteins and evidence of non-random targeting of specific signalling pathways. Our findings indicate that molecular mimicry and epitope spreading events may play a role in dermatomyositis pathogenesis.

Megremis, Walker at al. identify immunogenic epitopes in dermatomyositis patients. They identify antibodies recognizing a wider diversity of microbial antigens including poxviruses, and autoantibodies recognizing a large portion of the human proteome. Shared epitope homology between viral and human proteins suggests that molecular mimicry and epitope spreading events may play a role in dermatomyositis pathogenesis.

Pan-genome analysis and ancestral state reconstruction of class halobacteria: probability of a new super-order

Halobacteria, a class of Euryarchaeota are extremely halophilic archaea that can adapt to a wide range of salt concentration generally from 10% NaCl to saturated salt concentration of 32% NaCl. It consists of the orders: Halobacteriales, Haloferaciales and Natriabales. Pan-genome analysis of class Halobacteria was done to explore the core (300) and variable components (Softcore: 998, Cloud:36531, Shell:11784). The core component revealed genes of replication, transcription, translation and repair, whereas the variable component had a major portion of environmental information processing. The pan-gene matrix was mapped onto the core-gene tree to find the ancestral (44.8%) and derived genes (55.1%) of the Last Common Ancestor of Halobacteria. A High percentage of derived genes along with presence of transformation and conjugation genes indicate the occurrence of horizontal gene transfer during the evolution of Halobacteria. A Core and pan-gene tree were also constructed to infer a phylogeny which implicated on the new super-order comprising of Natrialbales and Halobacteriales.

HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks

The growing prevalence of resistance to antibiotics motivates the search for new antibacterial agents. Antimicrobial peptides are a diverse class of well-studied membrane-active peptides which function as part of the innate host defence system, and form a promising avenue in antibiotic drug research. Some antimicrobial peptides exhibit toxicity against eukaryotic membranes, typically characterised by hemolytic activity assays, but currently, the understanding of what differentiates hemolytic and non-hemolytic peptides is limited. This study leverages advances in machine learning research to produce a novel artificial neural network classifier for the prediction of hemolytic activity from a peptide's primary sequence. The classifier achieves best-in-class performance, with cross-validated accuracy of [Formula: see text] and Matthews correlation coefficient of 0.71. This innovative classifier is available as a web server at https://research.timmons.eu/happenn , allowing the research community to utilise it for in silico screening of peptide drug candidates for high therapeutic efficacies.

Bayesian Confidence Intervals for Multiplexed Proteomics Integrate Ion-statistics with Peptide Quantification Concordance

Multiplexed proteomics has emerged as a powerful tool to measure relative protein expression levels across multiple conditions. The relative protein abundances are inferred by comparing the signals generated by isobaric tags, which encode the samples' origins. Intuitively, the trust associated with a protein measurement depends on the similarity of ratios from the protein's peptides and the signal-strength of these measurements. However, typically the average peptide ratio is reported as the estimate of relative protein abundance, which is only the most likely ratio with a very naive model. Moreover, there is no sense on the confidence in these measurements. Here, we present a mathematically rigorous approach that integrates peptide signal strengths and peptide-measurement agreement into an estimation of the true protein ratio and the associated confidence (BACIQ). The main advantages of BACIQ are: (1) It removes the need to threshold reported peptide signal based on an arbitrary cut-off, thereby reporting more measurements from a given experiment; (2) Confidence can be assigned without replicates; (3) For repeated experiments BACIQ provides confidence intervals for the union, not the intersection, of quantified proteins; (4) For repeated experiments, BACIQ confidence intervals are more predictive than confidence intervals based on protein measurement agreement. To demonstrate the power of BACIQ we reanalyzed previously published data on subcellular protein movement on treatment with an Exportin-1 inhibiting drug. We detect ∼2× more highly significant movers, down to subcellular localization changes of ∼1%. Thus, our method drastically increases the value obtainable from quantitative proteomics experiments, helping researchers to interpret their data and prioritize resources. To make our approach easily accessible we distribute it via a Python/Stan package.

A novel mitochondrial micropeptide MPM enhances mitochondrial respiratory activity and promotes myogenic differentiation

Micropeptides belong to a class of newly identified small molecules with <100 amino acids in length, and their functions remain largely unknown. Here, we identified a novel muscle-enriched micropeptide that was localized to mitochondria (named MPM, micropeptide in mitochondria) and upregulated during in vitro differentiation of C2C12 myoblasts and in vivo early postnatal skeletal muscle development, and muscle regeneration after cardiotoxin (CTX) damage. Downregulation of MPM was observed in the muscular tissues of tibial muscular dystrophy and Duchenne muscular dystrophy patients. Furthermore, MPM silencing inhibited the differentiation of C2C12 myoblasts into myotubes, whereas MPM overexpression stimulated it. MPM^−/− mice exhibited smaller skeletal muscle fibers and worse muscle performance, such as decrease in the maximum grip force of limbs, the latency to fall off rotarod, and the exhausting swimming time. Muscle regeneration was also impaired in MPM^−/− mice, as evidenced by lower expression of Pax7, MyoD, and MyoG after CTX injection and smaller regenerated myofibers, compared with wild-type mice. Mechanistical investigations based on both gain- and loss-of function studies revealed that MPM increased oxygen consumption and ATP production of mitochondria. Moreover, ectopic expression of PGC-1α, which can enhance mitochondrial respiration, attenuated the inhibitory effect of siMPM on myogenic differentiation. These results imply that MPM may promote myogenic differentiation and muscle fiber growth by enhancing mitochondrial respiratory activity, which highlights the importance of micropeptides in the elaborate regulatory network of both myogenesis and mitochondrial activity and implicates MPM as a potential target for muscular dystrophy therapy.

Bacterial Signal Peptidases

Signal peptidases are the membrane bound enzymes that cleave off the amino-terminal signal peptide from secretory preproteins . There are two types of bacterial signal peptidases . Type I signal peptidase utilizes a serine/lysine catalytic dyad mechanism and is the major signal peptidase in most bacteria. Type II signal peptidase is an aspartic protease specific for prolipoproteins. This chapter will review what is known about the structure, function and mechanism of these unique enzymes.

Exploring of the feature space of de novo developed post-transcriptional riboregulators

Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.

To allow reliable forward engineering of microbial cell factories, various metabolic engineering efforts rely on RNA-based technology. As such, programmable riboregulators allow dynamic control over gene expression. However, no clear design principles exist for de novo developed repressing riboregulators, which limits their applicability. Here, various engineering principles are identified and computationally explored. Subsequently, various design criteria are used in an experimental design, which were explored in an in vivo study. This resulted in a regression model that enables a more reliable computational design of repression small RNAs.

Discovery of a new metal and NAD+-dependent formate dehydrogenase from Clostridium ljungdahlii

Over the next decades, with the growing concern of rising atmospheric carbon dioxide (CO₂) levels, the importance of investigating new approaches for its reduction becomes crucial. Reclamation of CO₂ for conversion into biofuels represents an alternative and attractive production method that has been studied in recent years, now with enzymatic methods gaining more attention. Formate dehydrogenases (FDHs) are NAD(P)H-dependent oxidoreductases that catalyze the conversion of formate into CO₂ and have been extensively used for cofactor recycling in chemoenzymatic processes. A new FDH from Clostridium ljungdahlii (ClFDH) has been recently shown to possess activity in the reverse reaction: the mineralization of CO₂ into formate. In this study, we show the successful homologous expression of ClFDH in Escherichia coli. Biochemical and kinetic characterization of the enzyme revealed that this homologue also demonstrates activity toward CO₂ reduction. Structural analysis of the enzyme through homology modeling is also presented.

Updates on resources, software tools, and databases for plant proteomics in 2016-2017

Proteomics data processing, annotation, and analysis can often lead to major hurdles in large-scale high-throughput bottom-up proteomics experiments. Given the recent rise in protein-based big datasets being generated, efforts in in silico tool development occurrences have had an unprecedented increase; so much so, that it has become increasingly difficult to keep track of all the advances in a particular academic year. However, these tools benefit the plant proteomics community in circumventing critical issues in data analysis and visualization, as these continually developing open-source and community-developed tools hold potential in future research efforts. This review will aim to introduce and summarize more than 50 software tools, databases, and resources developed and published during 2016-2017 under the following categories: tools for data pre-processing and analysis, statistical analysis tools, peptide identification tools, databases and spectral libraries, and data visualization and interpretation tools. Intended for a well-informed proteomics community, finally, efforts in data archiving and validation datasets for the community will be discussed as well. Additionally, the author delineates the current and most commonly used proteomics tools in order to introduce novice readers to this -omics discovery platform.

Comparative analysis of Cucurbita pepo metabolism throughout fruit development in acorn squash and oilseed pumpkin

Both the fruit mesocarp and the seeds of winter squash can be used for consumption, although the focus of breeding efforts varies by cultivar. Cultivars bred for fruit consumption are selected for fruit mesocarp quality traits such as carotenoid content, percent dry matter, and percent soluble solids, while these traits are essentially ignored in oilseed pumpkins. To compare fruit development in these two types of squash, we sequenced the fruit transcriptome of two cultivars bred for different purposes: an acorn squash, 'Sweet REBA', and an oilseed pumpkin, 'Lady Godiva'. Putative metabolic pathways were developed for carotenoid, starch, and sucrose synthesis in winter squash fruit and squash homologs were identified for each of the structural genes in the pathways. Gene expression, especially of known rate-limiting and branch point genes, corresponded with metabolite accumulation both across development and between the two cultivars. Thus, developmental regulation of metabolite genes is an important factor in winter squash fruit quality.

Proximal disruptor aided ligation (ProDAL) of kilobase-long RNAs

RNA with site-specific modification is a useful tool for RNA biology studies. However, generating kilobase (kb) -long RNA with internal modification at a site distant from RNA termini remains challenging. Here we report an enhanced splint ligation technique, proximal disruptor aided ligation (ProDAL), which allows adequate efficiency toward this purpose. The key to our approach is using multiple DNA oligonucleotides, 'proximal disruptors', to target the RNA substrate sequence next to the ligation site. The binding of disruptors helps to free the ligation site from intramolecular RNA basepairing, and consequently promotes more efficient formation of the pre-ligation complex and a higher overall ligation yield. We used naturally occurring 1.0 kb renilla and 1.9 kb firefly luciferase mRNA sequences to test the efficacy of our approach. ProDAL yielded 9-14% efficiency for the ligation between two RNA substrates, both of which were between 414 and 1313 nucleotides (nt) long. ProDAL also allowed similarly high efficiency for generating kb-long RNA with site-specific internal modification by a simple three-part ligation between two long RNA substrates and a modification-carrying RNA oligonucleotide. In comparison, classical splint ligation yielded a significantly lower efficiency of 0-2% in all cases. We expect that ProDAL will benefit studies involving kb-long RNAs, including translation, long non-coding RNAs, RNA splicing and modification, and large ribonucleoprotein complexes.

Overall conceptual framework for studying the genetics of autoimmune diseases following vaccination: a regulatory perspective

The US Vaccine Adverse Event Reporting System contains case reports of autoimmune diseases (ADs) occurring following vaccinations. ADs are rare and occur in unvaccinated people, making the potential association between vaccines and ADs challenging to evaluate. Developing mechanistic pathways that link genes, immune mediators, vaccine components and ADs would be helpful for hypothesis generation, enhancing theories of biologic plausibility and grouping rare autoimmune adverse events to increase the ability to detect and evaluate safety signals. Here, we propose a conceptual framework for investigating the genetics of ADs as safety signals following vaccination, potentially contributing to the identification of relevant biomarkers. We also discuss a study design that incorporates genetic information into postmarket clinical evaluation of autoimmune adverse events following vaccination.

Sequence-Specific Peptide Nucleic Acid-Based Antisense Inhibitors of TEM-1 β-Lactamase and Mechanism of Adaptive Resistance

The recent surge of drug-resistant superbugs and shrinking antibiotic pipeline are serious challenges to global health. In particular, the emergence of β-lactamases has caused extensive resistance against the most frequently prescribed class of β-lactam antibiotics. Here, we develop novel synthetic peptide nucleic acid-based antisense inhibitors that target the start codon and ribosomal binding site of the TEM-1 β-lactamase transcript and act via translation inhibition mechanism. We show that these antisense inhibitors are capable of resensitizing drug-resistant Escherichia coli to β-lactam antibiotics exhibiting 10-fold reduction in the minimum inhibitory concentration (MIC). To study the mechanism of resistance, we adapted E. coli at MIC levels of the β-lactam/antisense inhibitor combination and observed a nonmutational, bet-hedging based adaptive antibiotic resistance response as evidenced by phenotypic heterogeneity as well as heterogeneous expression of key stress response genes. Our data show that both the development of new antimicrobials and an understanding of cellular response during the development of tolerance could aid in mitigating the impending antibiotic crisis.

An acorn squash (Cucurbita pepo ssp. ovifera) fruit and seed transcriptome as a resource for the study of fruit traits in Cucurbita

Acorn squash (Cucurbita pepo) is an iconic fall vegetable in the United States, known for its unique fruit shape and also prized for its culinary properties. Little is known about the metabolism that underlies the development of fruit quality attributes such as color, sweetness, texture and nutritional qualities in acorn squash, or any other winter squash grown worldwide. To provide insight into winter squash fruit and seed development and add to the genomic resources in the Cucurbita genus, RNA sequencing was used to generate an acorn squash fruit and seed transcriptome from the cultivar Sweet REBA at critical points throughout fruit development. 141 838 600 high-quality paired-end Illumina reads were assembled into 55 949 unigenes. 85% of unigenes with predicted open reading frames had homology with previously identified genes and over 62% could be functionally annotated. Comparison with the watermelon and cucumber genomes provided confirmation that the unigenes are full-length and comprehensive, covering an average of 90% of the coding sequence of their homologs and 72% of the cucumber and watermelon exomes. Key candidate genes associated with carotenoid and carbohydrate metabolism were identified toward a resource for winter squash fruit quality trait dissection. This transcriptome represents a major advance in C. pepo genomics, providing significant new sequence information and revealing the repertoire of genes expressed throughout winter squash fruit and seed development. Future studies on the genetic basis of fruit quality and future breeding efforts will be enhanced by tools and insights developed from this resource.

Effects of copy number variable regions on local gene expression in white blood cells of Mexican Americans

Only few systematic studies on the contribution of copy number variation to gene expression variation have been published to date. Here we identify effects of copy number variable regions (CNVRs) on nearby gene expression by investigating 909 CNVRs and expression levels of 12059 nearby genes in white blood cells from Mexican-American participants of the San Antonio Family Heart Study. We empirically evaluate our ability to detect the contribution of CNVs to proximal gene expression (presumably in cis) at various window sizes (up to a 10 Mb distance) between the gene and CNV. We found a ~1-Mb window size to be optimal for capturing cis effects of CNVs. Up to 10% of the CNVs in this study were found to be significantly associated with the expression of at least one gene within their vicinity. As expected, we find that CNVs that directly overlap gene sequences have the largest effects on gene expression (compared with non-overlapping CNVRs located nearby), with positive correlation (except for a few exceptions) between estimated genomic dosage and expression level. We find that genes whose expression level is significantly influenced by nearby CNVRs are enriched for immunity and autoimmunity related genes. These findings add to the currently limited catalog of CNVRs that are recognized as expression quantitative trait loci, and have implications for future study designs as well as for prioritizing candidate causal variants in genomic regions associated with disease.

Exploiting open data: a new era in pharmacoinformatics

Within the last decade open data concepts has been gaining increasing interest in the area of drug discovery. With the launch of ChEMBL and PubChem, an enormous amount of bioactivity data was made easily accessible to the public domain. In addition, platforms that semantically integrate those data, such as the Open PHACTS Discovery Platform, permit querying across different domains of open life science data beyond the concept of ligand-target-pharmacology. However, most public databases are compiled from literature sources and are thus heterogeneous in their coverage. In addition, assay descriptions are not uniform and most often lack relevant information in the primary literature and, consequently, in databases. This raises the question how useful large public data sources are for deriving computational models. In this perspective, we highlight selected open-source initiatives and outline the possibilities and also the limitations when exploiting this huge amount of bioactivity data.

Mapping post-translational modifications of mammalian testicular specific histone variant TH2B in tetraploid and haploid germ cells and their implications on the dynamics of nucleosome structure

Histones regulate a variety of chromatin templated events by their post-translational modifications (PTMs). Although there are extensive reports on the PTMs of canonical histones, the information on the histone variants remains very scanty. Here, we report the identification of different PTMs, such as acetylation, methylation, and phosphorylation of a major mammalian histone variant TH2B. Our mass spectrometric analysis has led to the identification of both conserved and unique modifications across tetraploid spermatocytes and haploid spermatids. We have also computationally derived the 3-dimensional model of a TH2B containing nucleosome in order to study the spatial orientation of the PTMs identified and their effect on nucleosome stability and DNA binding potential. From our nucleosome model, it is evident that substitution of specific amino acid residues in TH2B results in both differential histone-DNA and histone-histone contacts. Furthermore, we have also observed that acetylation on the N-terminal tail of TH2B weakens the interactions with the DNA. These results provide direct evidence that, similar to somatic H2B, the testis specific histone TH2B also undergoes multiple PTMs, suggesting the possibility of chromatin regulation by such covalent modifications in mammalian male germ cells.

Prediction of substrates for glutathione transferases by covalent docking

Enzymes in the glutathione transferase (GST) superfamily catalyze the conjugation of glutathione (GSH) to electrophilic substrates. As a consequence they are involved in a number of key biological processes, including protection of cells against chemical damage, steroid and prostaglandin biosynthesis, tyrosine catabolism, and cell apoptosis. Although virtual screening has been used widely to discover substrates by docking potential noncovalent ligands into active site clefts of enzymes, docking has been rarely constrained by a covalent bond between the enzyme and ligand. In this study, we investigate the accuracy of docking poses and substrate discovery in the GST superfamily, by docking 6738 potential ligands from the KEGG and MetaCyc compound libraries into 14 representative GST enzymes with known structures and substrates using the PLOP program [ Jacobson Proteins 2004 , 55 , 351 ]. For X-ray structures as receptors, one of the top 3 ranked models is within 3 Å all-atom root mean square deviation (RMSD) of the native complex in 11 of the 14 cases; the enrichment LogAUC value is better than random in all cases, and better than 25 in 7 of 11 cases. For comparative models as receptors, near-native ligand-enzyme configurations are often sampled but difficult to rank highly. For models based on templates with the highest sequence identity, the enrichment LogAUC is better than 25 in 5 of 11 cases, not significantly different from the crystal structures. In conclusion, we show that covalent docking can be a useful tool for substrate discovery and point out specific challenges for future method improvement.

Optimization of a yeast RNA interference system for controlling gene expression and enabling rapid metabolic engineering

Reduction of endogenous gene expression is a fundamental operation of metabolic engineering, yet current methods for gene knockdown (i.e., genome editing) remain laborious and slow, especially in yeast. In contrast, RNA interference allows facile and tunable gene knockdown via a simple plasmid transformation step, enabling metabolic engineers to rapidly prototype knockdown strategies in multiple strains before expending significant cost to undertake genome editing. Although RNAi is naturally present in a myriad of eukaryotes, it has only been recently implemented in Saccharomyces cerevisiae as a heterologous pathway and so has not yet been optimized as a metabolic engineering tool. In this study, we elucidate a set of design principles for the construction of hairpin RNA expression cassettes in yeast and implement RNA interference to quickly identify routes for improvement of itaconic acid production in this organism. The approach developed here enables rapid prototyping of knockdown strategies and thus accelerates and reduces the cost of the design-build-test cycle in yeast.

Discovery of novel genes and gene isoforms by integrating transcriptomic and proteomic profiling from mouse liver

Comprehensively identifying gene expression in both transcriptomic and proteomic levels of one tissue is a prerequisite for a deeper understanding of its biological functions. Alternative splicing and RNA editing, two main forms of transcriptional processing, play important roles in transcriptome and proteome diversity and result in multiple isoforms for one gene, which are hard to identify by mass spectrometry (MS)-based proteomics approach due to the relative lack of isoform information in standard protein databases. In our study, we employed MS and RNA-Seq in parallel into mouse liver tissue and captured a considerable catalogue of both transcripts and proteins that, respectively, covered 60 and 34% of protein-coding genes in Ensembl. We then developed a bioinformatics workflow for building a customized protein database that for the first time included new splicing-derived peptides and RNA-editing-caused peptide variants, allowing us to more completely identify protein isoforms. Using this experimentally determined database, we totally identified 150 peptides not present in standard biological databases at false discovery rate of <1%, corresponding to 72 novel splicing isoforms, 43 new genetic regions, and 15 RNA-editing sites. Of these, 11 randomly selected novel events passed experimental verification by PCR and Sanger sequencing. New discoveries of gene products with high confidence in two omics levels demonstrated the robustness and effectiveness of our approach and its potential application into improve genome annotation. All the MS data have been deposited to the iProx ( http://ww.iprox.org ) with the identifier IPX00003601.

Structural and kinetic characterization of guinea pig L-asparaginase type III

We investigated whether an uncharacterized protein from guinea pig could be the enzyme behind Kidd's serendipitous discovery, made over 60 years ago, that guinea pig serum has cell killing ability. It has been long known that an enzyme with l-asparaginase activity is responsible for cell killing, although astonishingly, its identity remains unclear. Bacterial asparaginases with similar cell killing properties have since become a mainstay therapy of certain cancers such as acute lymphoblastic leukemia. By hydrolyzing asparagine to aspartate and ammonia, these drugs deplete the asparagine present in the blood, killing cancer cells that rely on extracellular asparagine uptake for survival. However, bacterial asparaginases can elicit an adverse immune response. We propose that replacement of bacterial enzymes with the guinea pig asparaginase responsible for serum activity, by its virtue of being more closely related to human enzymes, will be less immunogenic. To this goal, we investigated whether an uncharacterized protein from guinea pig with putative asparaginase activity, which we call gpASNase3, could be that enzyme. We examined its self-activation process (gpASNase3 requires autocleavage to become active), kinetically characterized it for asparaginase and β-aspartyl dipeptidase activity, and elucidated its crystal structure in both the uncleaved and cleaved states. This work reveals that gpASNase3 is not the enzyme responsible for the antitumor effects of guinea pig serum. It exhibits a low affinity for asparagine as measured by a high Michaelis constant, KM, in the millimolar range, in contrast to the low KM (micromolar range) required for asparaginase to be effective as an anticancer agent.

RNA- and antibody-based profiling of the human proteome with focus on chromosome 19

An important part of the Human Proteome Project is to characterize the protein complement of the genome with antibody-based profiling. Within the framework of this effort, a new version 12 of the Human Protein Atlas ( www.proteinatlas.org ) has been launched, including transcriptomics data for 27 tissues and 44 cell lines to complement the protein expression data from antibody-based profiling. Besides the extensive addition of transcriptomics data, the Human Protein Atlas now contains antibody-based protein profiles for 82% of the 20 329 putative protein-coding genes. The comprehensive data resulting from RNA-seq analysis and antibody-based profiling performed within the Human Protein Atlas as well as information from UniProt were used to generate evidence summary scores for each of the 20 329 genes, of which 94% now have experimental evidence at least at transcript level. The evidence scores for all individual genes are displayed with regards to both RNA- and antibody-based protein profiles, including chromosome-centric visualizations. An analysis of the human chromosome 19 shows that ∼43% of the genes are expressed at the transcript level in all 27 tissues analyzed, suggesting a "house-keeping" function, while 12% of the genes show a more tissue-specific pattern with enriched expression in one of the analyzed tissues only.

Accessibility of microRNA binding sites in metastable RNA secondary structures in the presence of SNPs

MOTIVATION

We study microRNA (miRNA) bindings to metastable RNA secondary structures close to minimum free energy conformations in the context of single nucleotide polymorphisms (SNPs) and messenger RNA (mRNA) concentration levels, i.e. whether features of miRNA bindings to metastable conformations could provide additional information supporting the differences in expression levels of the two sequences defined by a SNP. In our study, the instances [mRNA/3'UTR; SNP; miRNA] were selected based on strong expression level analyses, SNP locations within binding regions and the computationally feasible identification of metastable conformations.

RESULTS

We identified 14 basic cases [mRNA; SNP; miRNA] of 3' UTR-lengths ranging from 124 up to 1078 nt reported in recent literature, and we analyzed the number, structure and miRNA binding to metastable conformations within an energy offset above mfe conformations. For each of the 14 instances, the miRNA binding characteristics are determined by the corresponding STarMir output. Among the different parameters we introduced and analyzed, we found that three of them, related to the average depth and average opening energy of metastable conformations, may provide supporting information for a stronger separation between miRNA bindings to the two alleles defined by a given SNP.

AVAILABILITY AND IMPLEMENTATION

At http://kks.inf.kcl.ac.uk/MSbind.html the MSbind tool is available for calculating features of metastable conformations determined by putative miRNA binding sites.

Antisense oligonucleotides: treating neurodegeneration at the level of RNA

Adequate therapies are lacking for Alzheimer's disease, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis, and other neurodegenerative diseases. The ability to use antisense oligonucleotides (ASOs) to target disease-associated genes by means of RNA may offer a potent approach for the treatment of these, and other, neurodegenerative disorders. In modifying the basic backbone chemistry, chemical groups, and target sequence, ASOs can act through numerous mechanisms to decrease or increase total protein levels, preferentially shift splicing patterns, and inhibit microRNAs, all at the level of the RNA molecule. Here, we discuss many of the more commonly used ASO chemistries, as well as the different mechanisms of action that can result from these specific chemical modifications. When applied to multiple neurodegenerative mouse models, ASOs that specifically target the detrimental transgenes have been shown to rescue disease associated phenotypes in vivo. These supporting mouse model data have moved the ASOs from the bench to the clinic, with two neuro-focused human clinical trials now underway and several more being proposed. Although still early in development, translating ASOs into human patients for neurodegeneration appears promising.

Potent and selective inhibition of A-to-I RNA editing with 2'-O-methyl/locked nucleic acid-containing antisense oligoribonucleotides

ADARs (adenosine deaminases acting on RNA) are RNA editing enzymes that bind double helical RNAs and deaminate select adenosines (A). The product inosine (I) is read during translation as guanosine (G), so such changes can alter codon meaning. ADAR-catalyzed A to I changes occur in coding sequences for several proteins of importance to the nervous system. However, these sites constitute only a very small fraction of known A to I sites in the human transcriptome, and the significance of editing at the vast majority sites is unknown at this time. Site-selective inhibitors of RNA editing are needed to advance our understanding of the function of editing at specific sites. Here we show that 2'-O-methyl/locked nucleic acid (LNA) mixmer antisense oligonucleotides are potent and selective inhibitors of RNA editing on two different target RNAs. These reagents are capable of binding with high affinity to RNA editing substrates and remodeling the secondary structure by a strand-invasion mechanism. The potency observed here for 2'-O-methyl/LNA mixmers suggests this backbone structure is superior to the morpholino backbone structure for inhibition of RNA editing. Finally, we demonstrate antisense inhibition of editing of the mRNA for the DNA repair glycosylase NEIL1 in cultured human cells, providing a new approach to exploring the link between RNA editing and the cellular response to oxidative DNA damage.