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.

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.

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.

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.

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.

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.

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.

A Genetically Encoded Bioluminescent System for Fast and Highly Sensitive Detection of Antibodies with a Bright Green Fluorescent Protein.

A method for fast and highly sensitive detection of antibodies in serum would greatly facilitate the early diagnosis of disease and infection and dose optimization of therapeutic antibody. Bioluminescence detection with LUMABS (renamed mNeonG-LUMABS, where mNeonG is short for mNeonGreen) sensors based on bioluminescence resonance energy transfer (BRET) between blue-emitting luciferase Nluc and green fluorescent protein (FP) mNeonGreen has been demonstrated to enable fast detection of antibodies directly in serum with reasonable sensitivity. However, some mNeonG-LUMABS sensors exhibit low sensitivity, and thus, sensitivity improvement remains imperative. Here, we report a bright green FP, Clover4, obtained by structure-guided mutagenesis of green FP Clover. Despite similar brightness and fluorescence spectra of Clover and mNeonGreen, Clover4-LUMABS sensors exhibit a largely increased dynamic range (maximum 20-fold) and much lower limit of detection (LOD) (maximum 5.6-fold), most likely because Clover4 is positioned in a more parallel orientation to Nluc in LUMABS. Due to modular design, Clover4-LUMABS offers a general BRET system for fast and highly sensitive antibody detection in serum.

Human amyloid beta and α-synuclein co-expression in neurons impair behavior and recapitulate features for Lewy body dementia in Caenorhabditis elegans.

Amyloid ß (Aß), a product of APP, and SNCA (α-synuclein (α-syn)) are two of the key proteins found in lesions associated with the age-related neurodegenerative disorders Alzheimer's disease (AD) and Parkinson's disease (PD), respectively. Previous clinical studies uncovered Aß and α-syn co-expression in the brains of patients, which lead to Lewy body dementia (LBD), a disease encompassing Dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD). To explore the pathogenesis and define the relationship between Aß and α-syn for LBD, we established a C. elegans model which co-expresses human Aß and α-syn with alanine 53 to threonine mutant (α-syn(A53T)) in pan-neurons. Compared to α-syn(A53T) single transgenic animals, pan-neuronal Aß and α-syn(A53T) co-expression further enhanced the thrashing, egg laying, serotonin and cholinergic signaling deficits, and dopaminergic neuron damage in C. elegans. In addition, Aß increased α-syn expression in transgenic animals. Transcriptome analysis of both Aß;α-syn(A53T) strains and DLB patients showed common downregulation in lipid metabolism and lysosome function genes, suggesting that a decrease of lysosome function may reduce the clearance ability in DLB, and this may lead to the further pathogenic protein accumulation. These findings suggest that our model can recapitulate some features in LBD and provides a mechanism by which Aß may exacerbate α-syn pathogenesis.

Dysregulation of MicroRNAs and PIWI-Interacting RNAs in a Caenorhabditis elegans Parkinson's Disease Model Overexpressing Human α-Synuclein and Influence of tdp-1.

MicroRNAs (miRNAs) and PIWI-interacting RNAs (piRNAs) regulate gene expression and biological processes through specific genetic and epigenetic mechanisms. Recent studies have described a dysregulation of small non-coding RNAs in Parkinson's disease (PD) tissues but have been limited in scope. Here, we extend these studies by comparing the dysregulation of both miRNAs and piRNAs from transgenic Caenorhabditis elegans (C. elegans) nematodes overexpressing pan-neuronally human α-synuclein wild-type (WT) (HASNWT OX) or mutant (HASNA53T OX). We observed 32 miRNAs and 112 piRNAs dysregulated in HASNA53T OX compared with WT. Genetic crosses of HASNA53T OX PD animal models with tdp-1 null mutants, the C. elegans ortholog of TDP-43, an RNA-binding protein aggregated in frontal temporal lobar degeneration, improved their behavioral deficits and changed the number of dysregulated miRNAs to 11 and piRNAs to none. Neuronal function-related genes T28F4.5, C34F6.1, C05C10.3, camt-1, and F54D10.3 were predicted to be targeted by cel-miR-1018, cel-miR-355-5p (C34F6.1 and C05C10.3), cel-miR-800-3p, and 21ur-1581 accordingly. This study provides a molecular landscape of small non-coding RNA dysregulation in an animal model that provides insight into the epigenetic changes, molecular processes, and interactions that occur during PD-associated neurodegenerative disorders.

An old weapon with a new function: PIWI-interacting RNAs in neurodegenerative diseases.

PIWI-interacting RNAs (piRNAs) are small non-coding transcripts that are highly conserved across species and regulate gene expression through pre- and post-transcriptional processes. piRNAs were originally discovered in germline cells and protect against transposable element expression to promote and maintain genome stability. In the recent decade, emerging roles of piRNAs have been revealed, including the roles in sterility, tumorigenesis, metabolic homeostasis, neurodevelopment, and neurodegenerative diseases. In this review, we summarize piRNA biogenesis in C. elegans, Drosophila, and mice, and further elaborate upon how piRNAs mitigate the harmful effects of transposons. Lastly, the most recent findings on piRNA participation in neurological diseases are highlighted. We speculate on the mechanisms of piRNA action in the development and progression of neurodegenerative diseases. Understanding the roles of piRNAs in neurological diseases may facilitate their applications in diagnostic and therapeutic practice.

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.

PDmethDB: A curated Parkinson's disease associated methylation information database.

Parkinson's disease (PD) is the second most common neurodegenerative disease, of which the histopathological hallmark is the formation of Lewy bodies consisting of α-synuclein as the major component. α-Synuclein can sequester DNA Methyltransferase 1 (DNMT1), the maintenance DNA methylation enzyme, from the nucleus and into the cytoplasm, leading to global DNA hypomethylation in human brain. As DNA methylation is a major epigenetic modification that regulates gene expression and there is no specific database storing PD associated methylation information, PDmethDB (Parkinson's Disease Methylation Database) aims to curate PD associated methylation information from literature to facilitate the study of the relationship between PD and methylation. Currently, PDmethDB contains 97,077 PD methylation associated entries among 12,308 molecules, 37,944 CpG sites, 31 tissues and 3 species through a review of about 1600 published papers. This includes information concerning the gene/molecule name, CpG site, methylation alteration, expression alteration, tissue, PMID, experimental method, and a brief description about the entry. PDmethDB provides a user-friendly interface to search, browse, download and submit data. PDmethDB supports browsing by molecule, species, tissue, gene region, methylation alteration and experimental methods. PDmethDB also shows the entry gene interaction network including protein-protein interactions and miRNA-targets interactions with a highlight of PD associated genes from DisGeNET database. PDmethDB aims to facilitate the understanding of the relationship between PD and methylation. Database URL: https://ageing.shinyapps.io/pdmethdb/.

TDP-1/TDP-43 potentiates human α-Synuclein (HASN) neurodegeneration in Caenorhabditis elegans.

TAR DNA binding protein (TDP-43) is a DNA/RNA binding protein whose pathological role in amyotrophic lateral sclerosis (ALS) and frontal temporal lobe dementia (FTLD) via formation of protein aggregates is well established. In contrast, knowledge concerning its interactions with other neuropathological aggregating proteins is poorly understood. Human α-synuclein (HASN) elicits dopaminergic neuron degeneration via protein aggregation in Parkinson's disease. HASN protein aggregates are also found in TDP-43 lesions and colocalize in Lewy Body Dementia (LBD). To better understand the interactions of TDP-43 and HASN, we investigated the effects of genetic deletion of tdp-1, the Caenorhabditis elegans ortholog of human TDP-43, as well as overexpression of TDP-43, in transgenic models overexpressing HASNWT and HASNA53T. Tdp-1 deletion improved the posture, movement, and developmental delay observed in transgenic animals pan-neuronally overexpressing HASNA53T, and attenuated the loss and impairment of dopaminergic neurons caused by HASNA53T or HASNWT overexpression. Tdp-1 deletion also led to a decrease in protein level, mRNA level and aggregate formation of HASN in living animals. RNA-seq studies suggested that tdp-1 supports expression of lysosomal genes and decreases expression of genes involved in heat shock. RNAi demonstrated that heat shock proteins can mediate HASN neuropathology. Co-overexpression of both human TDP-43 and HASNWT resulted in locomotion deficits, shorter lifespan, and more severe dopaminergic neuron impairments compared to single transgenes. Our results suggest TDP-1/TDP-43 potentiates HASN mediated neurodegeneration in C. elegans. This study indicates a multifunctional role for TDP-1/TDP-43 in neurodegeneration involving HASN.

De novo transcriptome assembly of a facultative parasitic nematode Pelodera (syn. Rhabditis) strongyloides.

Pelodera strongyloides is a generally free-living gonochoristic facultative nematode. The whole genomic sequence of P. strongyloides remains unknown but 4 small subunit ribosomal RNA (ssrRNA) gene sequences are available. This project launched a de novo transcriptome assembly with 100 bp paired-end RNA-seq reads from normal, starved and wet-plate cultured animals. Trinity assembly tool generated 104,634 transcript contigs with N50 contig being 2195 bp and average contig length at 1103 bp. Transcriptome BLASTX matching results of five nematodes (C. elegans, Strongyloides stercoralis, Necator americanus, Trichuris trichiura, and Pristionchus pacificus) were consistent with their evolutionary relationships. Sixteen genes were identified to be homologous to key elements of the C. elegans RNA interference system, such as Dicer, Argonaute, RNA-dependent RNA polymerase and double strand RNA transport proteins. In starved samples, we observed up-regulation of cuticle related genes and 3 dauer formation genes. Dauer morphology was captured with enlarged phasmid under light microscopy, and dauer and normal larvae counts in clumps had a Pearson's product-moment correlation of 0.805 with P-value = 0.0088. Our results demonstrate that P. strongyloides could be used for studying nematode-related human or pet parasitic diseases. The sequenced assembled transcriptome reported here may be useful to understand the evolution of parasitism in Nematoda.

Identification of potential blood biomarkers for Parkinson's disease by gene expression and DNA methylation data integration analysis.

BACKGROUND: Blood-based gene expression or epigenetic biomarkers of Parkinson's disease (PD) are highly desirable. However, accuracy and specificity need to be improved, and methods for the integration of gene expression with epigenetic data need to be developed in order to make this feasible. METHODS: Whole blood gene expression data and DNA methylation data were downloaded from Gene Expression Omnibus (GEO) database. A linear model was used to identify significantly differentially expressed genes (DEGs) and differentially methylated genes (DMGs) according to specific gene regions 5'-C-phosphate-G-3' (CpGs) or all gene regions CpGs in PD. Gene set enrichment analysis was then applied to DEGs and DMGs. Subsequently, data integration analysis was performed to identify robust PD-associated blood biomarkers. Finally, the random forest algorithm and a leave-one-out cross validation method were performed to construct classifiers based on gene expression data integrated with methylation data. RESULTS: Eighty-five (85) significantly hypo-methylated and upregulated genes in PD patients compared to healthy controls were identified. The dominant hypo-methylated regions of these genes were significantly different. Some genes had a single dominant hypo-methylated region, while others had multiple dominant hypo-methylated regions. One gene expression classifier and two gene methylation classifiers based on all or dominant methylation-altered region CpGs were constructed. All have a good prediction power for PD. CONCLUSIONS: Gene expression and methylation data integration analysis identified a blood-based 53-gene signature, which could be applied as a biomarker for PD.

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.

miRNA arm switching identifies novel tumour biomarkers.

BACKGROUND: microRNAs have been reported to play critical roles in cancer and to have potential as diagnostic biomarkers. During miRNA biogenesis, one strand of the miRNA hairpin precursor is preferentially selected as a functionally mature miRNA, while the other strand is typically degraded. Arm switching occurs when the strand preference is changed. This preference can be different and can change dynamically depending upon the species, tissue types, or development stages. Due to recent advances in next-generation sequencing methods, arm switching has been observed in a variety of cancers. METHODS: A tumour miRNA-Seq dataset was collected from The Cancer Genome Atlas (TCGA). The support vector machine (SVM) method combined with 5-fold cross validation was applied to select the best combination of arm-switched miRNA tumour markers. Survival analysis was also applied to identify patient survival associated miRNA markers. FINDINGS: We observed 51 arm-switched miRNAs and of these, 7 were associated with patient survival. Twenty-three 1-combination arm switching miRNAs with excellent diagnostic value were identified. Interestingly, ovarian cancer showed a significant difference in arm switching pattern compared with 32 other cancers. INTERPRETATION: These results suggest that arm switching miRNAs could be used as potential biomarkers for various cancers. FUND: This work was partially supported by the National Natural Science Foundation of China (no. 61472158, 61572227), and University of Macau Faculty of Health Sciences (MYRG2016-00101-FHS).

Using acs-22 mutant Caenorhabditis elegans to detect the toxicity of nanopolystyrene particles.

In this study, we employed Caenorhabditis elegans with acs-22 mutation to examine the in vivo effect of functional deficit in intestinal barrier on toxicity and translocation of nanopolystyrene particles. Mutation of acs-22 leads to deficit in intestinal barrier. After prolonged exposure, nanopolystyrene particles at concentrations ≥1 µg/L could cause toxicity on acs-22 mutant nematodes. acs-22 mutation resulted in translocation of nanopolystyrene particles into targeted organs through intestinal barrier in nanopolystyrene particles (1 µg/L) exposed nematodes. After prolonged exposure, nanopolystyrene particles (1 µg/L) dysregulated expressions of some genes required for the control of oxidative stress and activated expression of Nrf signaling pathway. Therefore, under certain pathological conditions, our results suggest the potential toxicity of nanoplastic particles at predicted environmental concentration on organisms after long-term exposure.

miRToolsGallery: a tag-based and rankable microRNA bioinformatics resources database portal.

Database URL: http://www.mirtoolsgallery.org.