SingmiR: a single-cell miRNA alignment and analysis tool.

Single-cell RNA sequencing (RNA-seq) has revolutionized our understanding of cell biology, developmental and pathophysiological molecular processes, paving the way toward novel diagnostic and therapeutic approaches. However, most of the gene regulatory processes on the single-cell level are still unknown, including post-transcriptional control conferred by microRNAs (miRNAs). Like the established single-cell gene expression analysis, advanced computational expertise is required to comprehensively process newly emerging single-cell miRNA-seq datasets. A web server providing a workflow tailored for single-cell miRNA-seq data with a self-explanatory interface is currently not available. Here, we present SingmiR, enabling the rapid (pre-)processing and quantification of human miRNAs from noncoding single-cell samples. It performs read trimming for different library preparation protocols, generates automated quality control reports and provides feature-normalized count files. Numerous standard and advanced analyses such as dimension reduction, clustered feature heatmaps, sample correlation heatmaps and differential expression statistics are implemented. We aim to speed up the prototyping pipeline for biologists developing single-cell miRNA-seq protocols on small to medium-sized datasets. SingmiR is freely available to all users without the need for a login at https://www.ccb.uni-saarland.de/singmir.

Characterizing expression changes in noncoding RNAs during aging and heterochronic parabiosis across mouse tissues.

Molecular mechanisms of organismal and cell aging remain incompletely understood. We, therefore, generated a body-wide map of noncoding RNA (ncRNA) expression in aging (16 organs at ten timepoints from 1 to 27 months) and rejuvenated mice. We found molecular aging trajectories are largely tissue-specific except for eight broadly deregulated microRNAs (miRNAs). Their individual abundance mirrors their presence in circulating plasma and extracellular vesicles (EVs) whereas tissue-specific ncRNAs were less present. For miR-29c-3p, we observe the largest correlation with aging in solid organs, plasma and EVs. In mice rejuvenated by heterochronic parabiosis, miR-29c-3p was the most prominent miRNA restored to similar levels found in young liver. miR-29c-3p targets the extracellular matrix and secretion pathways, known to be implicated in aging. We provide a map of organism-wide expression of ncRNAs with aging and rejuvenation and identify a set of broadly deregulated miRNAs, which may function as systemic regulators of aging via plasma and EVs.

Proteomic Landscape of Human Sperm in Patients with Different Spermatogenic Impairments.

Although the proteome of sperm has been characterized, there is still a lack of high-throughput studies on dysregulated proteins in sperm from subfertile men, with only a few studies on the sperm proteome in asthenozoospermic and oligoasthenozoospermic men. Using liquid chromatography-mass spectrometry (LC-MS/MS) along with bioinformatics analyses, we investigated the proteomic landscape of sperm collected from subfertile men (n = 22), i.e., asthenozoospermic men (n = 13), oligoasthenozoospermic men (n = 9) and normozoospermic controls (n = 31). We identified 4412 proteins in human sperm. Out of these, 1336 differentially abundant proteins were identified in 70% of the samples. In subfertile men, 32 proteins showed a lower abundance level and 34 showed a higher abundance level when compared with normozoospermic men. Compared to normozoospermic controls, 95 and 8 proteins showed a lower abundance level, and 86 and 1 proteins showed a higher abundance level in asthenozoospermic and oligoasthenozoospermic men, respectively. Sperm motility and count were negatively correlated with 13 and 35 and positively correlated with 37 and 20 differentially abundant proteins in asthenozoospermic and oligoasthenozoospermic men, respectively. The combination of the proteins APCS, APOE, and FLOT1 discriminates subfertile males from normozoospermic controls with an AUC value of 0.95. Combined APOE and FN1 proteins discriminate asthenozoospermic men form controls with an AUC of 1, and combined RUVBL1 and TFKC oligoasthenozoospermic men with an AUC of 0.93. Using a proteomic approach, we revealed the proteomic landscape of sperm collected from asthenozoospermic or oligoasthenozoospermic men. Identified abundance changes of several specific proteins are likely to impact sperm function leading to subfertility. The data also provide evidence for the usefulness of specific proteins or protein combinations to support future diagnosis of male subfertility.

Expression profiling analysis reveals key microRNA-mRNA interactions in patients with transposition of the great arteries and systemic left and right ventricles.

Background: Patients with transposition of the great arteries (TGA) have different connected systemic chambers and this determines the long-term morbidities and survival. Limited findings have been reported to systematically identify miRNA and mRNA expression levels in such cohorts of patients. In this study, we aimed to characterize miRNAs, mRNAs, and miRNA-mRNA interaction networks in patients with TGA, with a systemic left (LV) and right ventricle (RV). Materials and methods: Large panel of human miRNA and mRNA microarrays were conducted to determine the genome-wide expression profiles in the blood of 16 TGA-RV patients, 16 TGA-LV patients, and 16 age and gender-matched controls. Using real-time quantitative PCR (RT-qPCR), the differential expression level of a single miRNA was validated. Enrichment analyses of altered miRNA and mRNA expression levels were identified using bioinformatics tools. Results: Altered miRNA and mRNA expression levels were observed between TGA-RV and TGA-LV patients, together or separated, compared to controls. Among the deregulated miRNAs and mRNAs, 39 and 101 miRNAs were identified as significantly differentially expressed in patients with TGA (both TGA-RV and TGA-LV) and TGA-RV, when compared to matched controls. Furthermore, 51 miRNAs were identified as significantly differentially expressed in patients with TGA-RV when compared to patients with TGA-LV. RT-qPCR relative expression level was highly consistent with microarray analysis results. Similarly, 36 and 164 mRNAs were identified as significantly differentially expressed in patients with TGA (both TGA-RV and TGA-LV) and TGA-RV, when compared to matched controls. Additionally, miR-140-3p showed a higher expression level in patients with overt heart failure (FC = 1.54; P = 0.001) and miR-502-3p showed a higher expression level in patients died due to cardiac death (FC = 1.41; P = 0.011). Integrative analysis resulted in 21 and 23 target genes with higher and lower expression levels, respectively (r ≥ 0.50 and P < 0.05). These target genes (i.e., 21 and 23 target genes) showed an inverse direction of regulation with miRNA and exhibited a miRNA binding site position within the 3'UTR of the target gene. Conclusion: Our findings provide new insights into a potential molecular biomarker(s) for patients with TGA that may guide better risk stratification and the development of novel targeting therapies. Future studies are needed to investigate the potential significance of miRNAs and mRNAs in TGA-related cardiovascular diseases.

Comparative genome analyses of Mycobacteroides immunogenum reveals two potential novel subspecies.

Mycobacteroides immunogenum is an emerging opportunistic pathogen implicated in nosocomial infections. Comparative genome analyses may provide better insights into its genomic structure, functions and evolution. The present analysis showed that M. immunogenum has an open pan-genome. Approximately 36.8% of putative virulence genes were identified in the accessory regions of M. immunogenum. Phylogenetic analyses revealed two potential novel subspecies of M. immunogenum, supported by evidence from ANIb (average nucleotide identity using blast) and GGDC (Genome to Genome Distance Calculator) analyses. We identified 74 genomic islands (GIs) in Subspecies 1 and 23 GIs in Subspecies 2. All Subspecies 2-harboured GIs were not found in Subspecies 1, indicating that they might have been acquired by Subspecies 2 after their divergence. Subspecies 2 has more defence genes than Subspecies 1, suggesting that it might be more resistant to the insertion of foreign DNA and probably explaining why Subspecies 2 has fewer GIs. Positive selection analysis suggest that M. immunogenum has a lower selection pressure compared to non-pathogenic mycobacteria. Thirteen genes were positively selected and many were involved in virulence.