Novel C. elegans models of Lewy body disease reveal pathological protein interactions and widespread miRNA dysregulation.

Lewy body diseases (LBD) comprise a group of complex neurodegenerative conditions originating from accumulation of misfolded alpha-synuclein (α-syn) in the form of Lewy bodies. LBD pathologies are characterized by α-syn deposition in association with other proteins such as Amyloid ß (Aß), Tau, and TAR-DNA-binding protein. To investigate the complex interactions of these proteins, we constructed 2 novel transgenic overexpressing (OE) C. elegans strains (α-synA53T;Taupro-agg (OE) and α-synA53T;Aß1-42;Taupro-agg (OE)) and compared them with previously established Parkinson's, Alzheimer's, and Lewy Body Dementia disease models. The LBD models presented here demonstrate impairments including uncoordinated movement, egg-laying deficits, altered serotonergic and cholinergic signaling, memory and posture deficits, as well as dopaminergic neuron damage and loss. Expression levels of total and prone to aggregation α-syn protein were increased in α-synA53T;Aß1-42 but decreased in α-synA53T;Taupro-agg animals when compared to α-synA53T animals suggesting protein interactions. These alterations were also observed at the mRNA level suggesting a pre-transcriptional mechanism. miRNA-seq revealed that cel-miR-1018 was upregulated in LBD models α-synA53T, α-synA53T;Aß1-42, and α-synA53T;Taupro-agg compared with WT. cel-miR-58c was upregulated in α-synA53T;Taupro-agg but downregulated in α-synA53T and α-synA53T;Aß1-42 compared with WT. cel-miR-41-3p and cel-miR-355-5p were significantly downregulated in 3 LBD models. Our results obtained in a model organism provide evidence of interactions between different pathological proteins and alterations in specific miRNAs that may further exacerbate or ameliorate LBD pathology.

PIWI-interacting RNAs in human diseases: databases and computational models.

PIWI-interacting RNAs (piRNAs) are short 21-35 nucleotide molecules that comprise the largest class of non-coding RNAs and found in a large diversity of species including yeast, worms, flies, plants and mammals including humans. The most well-understood function of piRNAs is to monitor and protect the genome from transposons particularly in germline cells. Recent data suggest that piRNAs may have additional functions in somatic cells although they are expressed there in far lower abundance. Compared with microRNAs (miRNAs), piRNAs have more limited bioinformatics resources available. This review collates 39 piRNA specific and non-specific databases and bioinformatics resources, describes and compares their utility and attributes and provides an overview of their place in the field. In addition, we review 33 computational models based upon function: piRNA prediction, transposon element and mRNA-related piRNA prediction, cluster prediction, signature detection, target prediction and disease association. Based on the collection of databases and computational models, we identify trends and potential gaps in tool development. We further analyze the breadth and depth of piRNA data available in public sources, their contribution to specific human diseases, particularly in cancer and neurodegenerative conditions, and highlight a few specific piRNAs that appear to be associated with these diseases. This briefing presents the most recent and comprehensive mapping of piRNA bioinformatics resources including databases, models and tools for disease associations to date. Such a mapping should facilitate and stimulate further research on piRNAs.

Drug-Target Interaction Prediction Based on an Interactive Inference Network.

Drug-target interactions underlie the actions of chemical substances in medicine. Moreover, drug repurposing can expand use profiles while reducing costs and development time by exploiting potential multi-functional pharmacological properties based upon additional target interactions. Nonetheless, drug repurposing relies on the accurate identification and validation of drug-target interactions (DTIs). In this study, a novel drug-target interaction prediction model was developed. The model, based on an interactive inference network, contains embedding, encoding, interaction, feature extraction, and output layers. In addition, this study used Morgan and PubChem molecular fingerprints as additional information for drug encoding. The interaction layer in our model simulates the drug-target interaction process, which assists in understanding the interaction by representing the interaction space. Our method achieves high levels of predictive performance, as well as interpretability of drug-target interactions. Additionally, we predicted and validated 22 Alzheimer's disease-related targets, suggesting our model is robust and effective and thus may be beneficial for drug repurposing.

The bioinformatics toolbox for circRNA discovery and analysis.

Circular RNAs (circRNAs) are a unique class of RNA molecule identified more than 40 years ago which are produced by a covalent linkage via back-splicing of linear RNA. Recent advances in sequencing technologies and bioinformatics tools have led directly to an ever-expanding field of types and biological functions of circRNAs. In parallel with technological developments, practical applications of circRNAs have arisen including their utilization as biomarkers of human disease. Currently, circRNA-associated bioinformatics tools can support projects including circRNA annotation, circRNA identification and network analysis of competing endogenous RNA (ceRNA). In this review, we collected about 100 circRNA-associated bioinformatics tools and summarized their current attributes and capabilities. We also performed network analysis and text mining on circRNA tool publications in order to reveal trends in their ongoing development.

Dysregulation of Human Somatic piRNA Expression in Parkinson's Disease Subtypes and Stages.

Piwi interacting RNAs (piRNAs) are small non-coding single-stranded RNA species 20-31 nucleotides in size generated from distinct loci. In germline tissues, piRNAs are amplified via a "ping-pong cycle" to produce secondary piRNAs, which act in transposon silencing. In contrast, the role of somatic-derived piRNAs remains obscure. Here, we investigated the identity and distribution of piRNAs in human somatic tissues to determine their function and potential role in Parkinson's disease (PD). Human datasets were curated from the Gene Expression Omnibus (GEO) database and a workflow was developed to identify piRNAs, which revealed 902 somatic piRNAs of which 527 were expressed in the brain. These were mainly derived from chromosomes 1, 11, and 19 compared to the germline tissues, which were from 15 and 19. Approximately 20% of somatic piRNAs mapped to transposon 3' untranslated regions (UTRs), but a large proportion were sensed to the transcript in contrast to germline piRNAs. Gene set enrichment analysis suggested that somatic piRNAs function in neurodegenerative disease. piRNAs undergo dysregulation in different PD subtypes (PD and Parkinson's disease dementia (PDD)) and stages (premotor and motor). piR-has-92056, piR-hsa-150797, piR-hsa-347751, piR-hsa-1909905, piR-hsa-2476630, and piR-hsa-2834636 from blood small extracellular vesicles were identified as novel biomarkers for PD diagnosis using a sparse partial least square discriminant analysis (sPLS-DA) (accuracy: 92%, AUC = 0.89). This study highlights a role for piRNAs in PD and provides tools for novel biomarker development.

Trends in the development of miRNA bioinformatics tools.

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression via recognition of cognate sequences and interference of transcriptional, translational or epigenetic processes. Bioinformatics tools developed for miRNA study include those for miRNA prediction and discovery, structure, analysis and target prediction. We manually curated 95 review papers and ∼1000 miRNA bioinformatics tools published since 2003. We classified and ranked them based on citation number or PageRank score, and then performed network analysis and text mining (TM) to study the miRNA tools development trends. Five key trends were observed: (1) miRNA identification and target prediction have been hot spots in the past decade; (2) manual curation and TM are the main methods for collecting miRNA knowledge from literature; (3) most early tools are well maintained and widely used; (4) classic machine learning methods retain their utility; however, novel ones have begun to emerge; (5) disease-associated miRNA tools are emerging. Our analysis yields significant insight into the past development and future directions of miRNA tools.

JMJD-1.2/PHF8 controls axon guidance by regulating Hedgehog-like signaling.

Components of the KDM7 family of histone demethylases are implicated in neuronal development and one member, PHF8, is often found to be mutated in cases of X-linked mental retardation. However, how PHF8 regulates neurodevelopmental processes and contributes to the disease is still largely unknown. Here, we show that the catalytic activity of a PHF8 homolog in Caenorhabditis elegans, JMJD-1.2, is required non-cell-autonomously for proper axon guidance. Loss of JMJD-1.2 dysregulates transcription of the Hedgehog-related genes wrt-8 and grl-16, the overexpression of which is sufficient to induce the axonal defects. Deficiency of either wrt-8 or grl-16, or reduced expression of homologs of genes promoting Hedgehog signaling, restores correct axon guidance in jmjd-1.2 mutants. Genetic and overexpression data indicate that Hedgehog-related genes act on axon guidance through actin remodelers. Thus, our study highlights a novel function of jmjd-1.2 in axon guidance that might be relevant for the onset of X-linked mental retardation and provides compelling evidence of a conserved function of the Hedgehog pathway in C. elegans axon migration.

Impaired removal of H3K4 methylation affects cell fate determination and gene transcription.

Methylation of histone 3 lysine 4 (H3K4) is largely associated with promoters and enhancers of actively transcribed genes and is finely regulated during development by the action of histone methyltransferases and demethylases. H3K4me3 demethylases of the KDM5 family have been previously implicated in development, but how the regulation of H3K4me3 level controls developmental processes is not fully established. Here, we show that the H3K4 demethylase RBR-2, the unique member of the KDM5 family in C. elegans, acts cell-autonomously and in a catalytic-dependent manner to control vulva precursor cells fate acquisition, by promoting the LIN-12/Notch pathway. Using genome-wide approaches, we show that RBR-2 reduces the H3K4me3 level at transcription start sites (TSSs) and in regions upstream of the TSSs, and acts both as a transcription repressor and activator. Analysis of the lin-11 genetic locus, a direct RBR-2 target gene required for vulva precursor cell fate acquisition, shows that RBR-2 controls the epigenetic signature of the lin-11 vulva-specific enhancer and lin-11 expression, providing in vivo evidence that RBR-2 can positively regulate transcription and cell fate acquisition by controlling enhancer activity.

Human amyloid ß peptide and tau co-expression impairs behavior and causes specific gene expression changes in Caenorhabditis elegans.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the presence of extracellular amyloid plaques consisting of Amyloid-ß peptide (Aß) aggregates and neurofibrillary tangles formed by aggregation of hyperphosphorylated microtubule-associated protein tau. We generated a novel invertebrate model of AD by crossing Aß1-42 (strain CL2355) with either pro-aggregating tau (strain BR5270) or anti-aggregating tau (strain BR5271) pan-neuronal expressing transgenic Caenorhabditis elegans. The lifespan and progeny viability of the double transgenic strains were significantly decreased compared with wild type N2 (P<0.0001). In addition, co-expression of these transgenes interfered with neurotransmitter signaling pathways, caused deficits in chemotaxis associative learning, increased protein aggregation visualized by Congo red staining, and increased neuronal loss. Global transcriptomic RNA-seq analysis revealed 248 up- and 805 down-regulated genes in N2 wild type versus Aß1-42+pro-aggregating tau animals, compared to 293 up- and 295 down-regulated genes in N2 wild type versus Aß1-42+anti-aggregating tau animals. Gene set enrichment analysis of Aß1-42+pro-aggregating tau animals uncovered up-regulated annotation clusters UDP-glucuronosyltransferase (5 genes, P<4.2E-4), protein phosphorylation (5 genes, P<2.60E-02), and aging (5 genes, P<8.1E-2) while the down-regulated clusters included nematode cuticle collagen (36 genes, P<1.5E-21). RNA interference of 13 available top up-regulated genes in Aß1-42+pro-aggregating tau animals revealed that F-box family genes and nep-4 could enhance life span deficits and chemotaxis deficits while Y39G8C.2 (TTBK2) could suppress these behaviors. Comparing the list of regulated genes from C. elegans to the top 60 genes related to human AD confirmed an overlap of 8 genes: patched homolog 1, PTCH1 (ptc-3), the Rab GTPase activating protein, TBC1D16 (tbc-16), the WD repeat and FYVE domain-containing protein 3, WDFY3 (wdfy-3), ADP-ribosylation factor guanine nucleotide exchange factor 2, ARFGEF2 (agef-1), Early B-cell Factor, EBF1 (unc-3), d-amino-acid oxidase, DAO (daao-1), glutamate receptor, metabotropic 1, GRM1 (mgl-2), prolyl 4-hydroxylase subunit alpha 2, P4HA2 (dpy-18 and phy-2). Taken together, our C. elegans double transgenic model provides insight on the fundamental neurobiologic processes underlying human AD and recapitulates selected transcriptomic changes observed in human AD brains.

RNA-Seq Reveals Acute Manganese Exposure Increases Endoplasmic Reticulum Related and Lipocalin mRNAs in Caenorhabditis elegans.

Manganese (Mn) is an essential nutrient; nonetheless, excessive amounts can accumulate in brain tissues causing manganism, a severe neurological condition. Previous studies have suggested oxidative stress, mitochondria dysfunction, and impaired metabolism pathways as routes for Mn toxicity. Here, we used the nematode Caenorhabditis elegans to analyze gene expression changes after acute Mn exposure using RNA-Seq. L1 stage animals were exposed to 50 mM MnCl2 for 30 min and analyzed at L4. We identified 746 up- and 1828 downregulated genes (FDR corrected p < 0.05; two-fold change) that included endoplasmic reticulum related abu and fkb family genes, as well as six of seven lipocalin-related (lpr) family members. These were also verified by qRT-PCR. RNA interference of lpr-5 showed a dramatic increase in whole body vulnerability to Mn exposure. Our studies demonstrate that Mn exposure alters gene transcriptional levels in different cell stress pathways that may ultimately contribute to its toxic effects.

Chronic ethanol exposure increases cytochrome P-450 and decreases activated in blocked unfolded protein response gene family transcripts in caenorhabditis elegans.

Ethanol is a widely consumed and rapidly absorbed toxin. While the physiological effects of ethanol consumption are well known, the underlying biochemical and molecular changes at the gene expression level in whole animals remain obscure. We exposed the model organism Caenorhabditis elegans to 0.2 M ethanol from the embryo to L4 larva stage and assayed gene expression changes in whole animals using RNA-Seq and quantitative real-time PCR. We observed gene expression changes in 1122 genes (411 up, 711 down). Cytochrome P-450 (CYP) gene family members (12 of 78) were upregulated, whereas activated in blocked unfolded protein response (ABU) (7 of 15) were downregulated. Other detoxification gene family members were also regulated including four glutathione-S-transferases and three flavin monooxygenases. The results presented show specific gene expression changes following chronic ethanol exposure in C. elegans that indicate both persistent upregulation of detoxification response genes and downregulation of endoplasmic reticulum stress pathway genes.

Nomogram for Early Prediction of Parkinson's Disease Based on microRNA Profiles and Clinical Variables.

BACKGROUND: Few efficient and simple models for the early prediction of Parkinson's disease (PD) exists. OBJECTIVE: To develop and validate a novel nomogram for early identification of PD by incorporating microRNA (miRNA) expression profiles and clinical indicators. METHODS: Expression levels of blood-based miRNAs and clinical variables from 1,284 individuals were downloaded from the Parkinson's Progression Marker Initiative database on June 1, 2022. Initially, the generalized estimating equation was used to screen candidate biomarkers of PD progression in the discovery phase. Then, the elastic net model was utilized for variable selection and a logistics regression model was constructed to establish a nomogram. Additionally, the receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and calibration curves were utilized to evaluate the performance of the nomogram. RESULTS: An accurate and externally validated nomogram was constructed for predicting prodromal and early PD. The nomogram is easy to utilize in a clinical setting since it consists of age, gender, education level, and transcriptional score (calculated by 10 miRNA profiles). Compared with the independent clinical model or 10 miRNA panel separately, the nomogram was reliable and satisfactory because the area under the ROC curve achieved 0.72 (95% confidence interval, 0.68-0.77) and obtained a superior clinical net benefit in DCA based on external datasets. Moreover, calibration curves also revealed its excellent prediction power. CONCLUSION: The constructed nomogram has potential for large-scale early screening of PD based upon its utility and precision.

PIWI-interacting RNA expression regulates pathogenesis in a Caenorhabditis elegans model of Lewy body disease.

PIWI-interacting RNAs (piRNAs) are small noncoding RNAs that regulate gene expression, yet their molecular functions in neurobiology are unclear. While investigating neurodegeneration mechanisms using human α-syn(A53T)Tg and AßTg;α-syn(A53T)Tg pan-neuronal overexpressing strains, we unexpectedly observed dysregulation of piRNAs. RNAi screening revealed that knock down of piRNA biogenesis genes improved thrashing behavior; further, a tofu-1 gene deletion ameliorated phenotypic deficits in α-syn(A53T)Tg and AßTg;α-syn(A53T)Tg transgenic strains. piRNA expression was extensively downregulated and H3K9me3 marks were decreased after tofu-1 deletion in α-syn(A53T)Tg and AßTg;α-syn(A53T)Tg strains. Dysregulated piRNAs targeted protein degradation genes suggesting that a decrease of piRNA expression leads to an increase of degradation ability in C. elegans. Finally, we interrogated piRNA expression in brain samples from PD patients. piRNAs were observed to be widely overexpressed at late motor stage. In this work, our results provide evidence that piRNAs are mediators in pathogenesis of Lewy body diseases and suggest a molecular mechanism for neurodegeneration in these and related disorders.

Prediction of microRNA targets in Caenorhabditis elegans using a self-organizing map.

MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that regulate transcriptional processes via binding to the target gene mRNA. In animals, this binding is imperfect, which makes the computational prediction of animal miRNA targets a challenging task. The accuracy of miRNA target prediction can be improved with the use of machine learning methods. Previous work has described methods using supervised learning, but they suffer from the lack of adequate training examples, a common problem in miRNA target identification, which often leads to deficient generalization ability. RESULTS: In this work, we introduce mirSOM, a miRNA target prediction tool based on clustering of short 3(')-untranslated region (3(')-UTR) substrings with self-organizing map (SOM). As our method uses unsupervised learning and a large set of verified Caenorhabditis elegans 3(')-UTRs, we did not need to resort to training using a known set of targets. Our method outperforms seven other methods in predicting the experimentally verified C.elegans true and false miRNA targets. AVAILABILITY: mirSOM miRNA target predictions are available at http://kokki.uku.fi/bioinformatics/mirsom.

Radiation-induced genomic instability in Caenorhabditis elegans.

Radiation-induced genomic instability has been well documented, particularly in vitro. However, the understanding of its mechanisms and their consequences in vivo is still limited. In this study, Caenorhabditis elegans (C. elegans; strain CB665) nematodes were exposed to X-rays at doses of 0.1, 1, 3 or 10Gy. The endpoints were measured several generations after exposure and included mutations in the movement-related gene unc-58, alterations in gene expression analysed with oligoarrays containing the entire C. elegans genome, and micro-satellite mutations measured by capillary electrophoresis. The progeny of the irradiated nematodes showed an increased mutation frequency in the unc-58 gene, with a maximum response observed at 1Gy. Significant differences were also found in gene expression between the irradiated (1Gy) and non-irradiated nematode lines. Differences in gene expression did not show clear clustering into certain gene categories, suggesting that the instability might be a chaotic process rather than a result of changes in the function of few specific genes such as, e.g., those responsible for DNA repair. Increased heterogeneity in gene expression, which has previously been described in irradiated cultured human lymphocytes, was also observed in the present study in C. elegans, the coefficient of variation of gene expression being higher in the progeny of irradiated nematodes than in control nematodes. To the best of our knowledge, this is the first publication reporting radiation-induced genomic instability in C. elegans.

Overexpression of SUMO perturbs the growth and development of Caenorhabditis elegans.

Small ubiquitin-related modifiers (SUMOs) are important regulator proteins. Caenorhabditis elegans contains a single SUMO ortholog, SMO-1, necessary for the reproduction of C. elegans. In this study, we constructed transgenic C. elegans strains expressing human SUMO-1 under the control of pan-neuronal (aex-3) or pan-muscular (myo-4) promoter and SUMO-2 under the control of myo-4 promoter. Interestingly, muscular overexpression of SUMO-1 or -2 resulted in morphological changes of the posterior part of the nematode. Movement, reproduction and aging of C. elegans were perturbed by the overexpression of SUMO-1 or -2. Genome-wide expression analyses revealed that several genes encoding components of SUMOylation pathway and ubiquitin-proteasome system were upregulated in SUMO-overexpressing nematodes. Since muscular overexpression of SMO-1 also brought up reproductive and mobility perturbations, our results imply that the phenotypes were largely due to an excess of SUMO, suggesting that a tight control of SUMO levels is important for the normal development of multicellular organisms.

Gene expression data analysis using Hellinger correlation in weighted gene co-expression networks (WGCNA).

Weighted gene co-expression network analysis (WGCNA) is used to detect clusters with highly correlated genes. Measurements of correlation most typically rely on linear relationships. However, a linear relationship does not always model pairwise functional-related dependence between genes. In this paper, we first compared 6 different correlation methods in their ability to capture complex dependence between genes in three different tissues. Next, we compared their gene-pairwise coefficient results and corresponding WGCNA results. Finally, we applied a recently proposed correlation method, Hellinger correlation, as a more sensitive correlation measurement in WGCNA. To test this method, we constructed gene networks containing co-expression gene modules from RNA-seq data of human frontal cortex from Alzheimer's disease patients. To test the generality, we also used a microarray data set from human frontal cortex, single cell RNA-seq data from human prefrontal cortex, RNA-seq data from human temporal cortex, and GTEx data from heart. The Hellinger correlation method captures essentially similar results as other linear correlations in WGCNA, but provides additional new functional relationships as exemplified by uncovering a link between inflammation and mitochondria function. We validated the network constructed with the microarray and single cell sequencing data sets and a RNA-seq dataset of temporal cortex. We observed that this new correlation method enables the detection of non-linear biologically meaningful relationships among genes robustly and provides a complementary new approach to WGCNA. Thus, the application of Hellinger correlation to WGCNA provides a more flexible correlation approach to modelling networks in gene expression analysis that uncovers novel network relationships.

Compromised autophagy and mitophagy in brain ageing and Alzheimer's diseases.

Alzheimer's disease (AD) is one of the most persistent and devastating neurodegenerative disorders of old age, and is characterized clinically by an insidious onset and a gradual, progressive deterioration of cognitive abilities, ranging from loss of memory to impairment of judgement and reasoning. Despite years of research, an effective cure is still not available. Autophagy is the cellular 'garbage' clearance system which plays fundamental roles in neurogenesis, neuronal development and activity, and brain health, including memory and learning. A selective sub-type of autophagy is mitophagy which recognizes and degrades damaged or superfluous mitochondria to maintain a healthy and necessary cellular mitochondrial pool. However, emerging evidence from animal models and human samples suggests an age-dependent reduction of autophagy and mitophagy, which are also compromised in AD. Upregulation of autophagy/mitophagy slows down memory loss and ameliorates clinical features in animal models of AD. In this review, we give an overview of autophagy and mitophagy and their link to the progression of AD. We also summarize approaches to upregulate autophagy/mitophagy. We hypothesize that age-dependent compromised autophagy/mitophagy is a cause of brain ageing and a risk factor for AD, while restoration of autophagy/mitophagy to more youthful levels could return the brain to health.

SMUG1 regulates fat homeostasis leading to a fatty liver phenotype in mice.

Fatty liver diseases are a major health threat across the western world, leading to cirrhosis and premature morbidity and mortality. Recently, a correlation between the base excision repair enzyme SMUG1 and metabolic homeostasis was identified. As the molecular mechanisms remain unknown, we exploited a SMUG1-knockout mouse model to gain insights into this association by characterizing the liver phenotype in young vs old SMUG1-null mice. We observed increased weight and fat content in one-year old animals, with altered activity of enzymes important for fatty acids influx and uptake. Consistently, lipidomic profiling showed accumulation of free fatty acids and triglycerides in SMUG1-null livers. Old SMUG1-knockout mice also displayed increased hepatocyte senescence and DNA damage at telomeres. Interestingly, RNA sequencing revealed widespread changes in the expression of lipid metabolic genes already in three months old animals. In summary, SMUG1 modulates fat metabolism favouring net lipogenesis and resulting in development of a fatty liver phenotype.

TAFFEL: Independent Enrichment Analysis of gene sets.

BACKGROUND: A major challenge in genomic research is identifying significant biological processes and generating new hypotheses from large gene sets. Gene sets often consist of multiple separate biological pathways, controlled by distinct regulatory mechanisms. Many of these pathways and the associated regulatory mechanisms might be obscured by a large number of other significant processes and thus not identified as significant by standard gene set enrichment analysis tools. RESULTS: We present a novel method called Independent Enrichment Analysis (IEA) and software TAFFEL that eases the task by clustering genes to subgroups using Gene Ontology categories and transcription regulators. IEA indicates transcriptional regulators putatively controlling biological functions in studied condition. CONCLUSIONS: We demonstrate that the developed method and TAFFEL tool give new insight to the analysis of differentially expressed genes and can generate novel hypotheses. Our comparison to other popular methods showed that the IEA method implemented in TAFFEL can find important biological phenomena, which are not reported by other methods.