Corrigendum: Identification of extremely GC-rich micro RNAs for RT-qPCR data normalization in human plasma.

[This corrects the article DOI: 10.3389/fgene.2022.1058668.].

Age prediction from human blood plasma using proteomic and small RNA data: a comparative analysis.

Aging clocks, built from comprehensive molecular data, have emerged as promising tools in medicine, forensics, and ecological research. However, few studies have compared the suitability of different molecular data types to predict age in the same cohort and whether combining them would improve predictions. Here, we explored this at the level of proteins and small RNAs in 103 human blood plasma samples. First, we used a two-step mass spectrometry approach measuring 612 proteins to select and quantify 21 proteins that changed in abundance with age. Notably, proteins increasing with age were enriched for components of the complement system. Next, we used small RNA sequencing to select and quantify a set of 315 small RNAs that changed in abundance with age. Most of these were microRNAs (miRNAs), downregulated with age, and predicted to target genes related to growth, cancer, and senescence. Finally, we used the collected data to build age-predictive models. Among the different types of molecules, proteins yielded the most accurate model (R² = 0.59 ± 0.02), followed by miRNAs as the best-performing class of small RNAs (R² = 0.54 ± 0.02). Interestingly, the use of protein and miRNA data together improved predictions (R2 = 0.70 ± 0.01). Future work using larger sample sizes and a validation dataset will be necessary to confirm these results. Nevertheless, our study suggests that combining proteomic and miRNA data yields superior age predictions, possibly by capturing a broader range of age-related physiological changes. It will be interesting to determine if combining different molecular data types works as a general strategy to improve future aging clocks.

Contribution of mutant HSC clones to immature and mature cells in MDS and CMML, and variations with AZA therapy.

Myelodysplastic neoplasms (MDSs) and chronic myelomonocytic leukemia (CMML) are clonal disorders driven by progressively acquired somatic mutations in hematopoietic stem cells (HSCs). Hypomethylating agents (HMAs) can modify the clinical course of MDS and CMML. Clinical improvement does not require eradication of mutated cells and may be related to improved differentiation capacity of mutated HSCs. However, in patients with established disease it is unclear whether (1) HSCs with multiple mutations progress through differentiation with comparable frequency to their less mutated counterparts or (2) improvements in peripheral blood counts following HMA therapy are driven by residual wild-type HSCs or by clones with particular combinations of mutations. To address these questions, the somatic mutations of individual stem cells, progenitors (common myeloid progenitors, granulocyte monocyte progenitors, and megakaryocyte erythroid progenitors), and matched circulating hematopoietic cells (monocytes, neutrophils, and naïve B cells) in MDS and CMML were characterized via high-throughput single-cell genotyping, followed by bulk analysis in immature and mature cells before and after AZA treatment. The mutational burden was similar throughout differentiation, with even the most mutated stem and progenitor clones maintaining their capacity to differentiate to mature cell types in vivo. Increased contributions from productive mutant progenitors appear to underlie improved hematopoiesis in MDS following HMA therapy.

Uterine fluid microRNAs are dysregulated in women with recurrent implantation failure.

STUDY QUESTION: Is the composition of microRNAs (miRNAs) in uterine fluid (UF) of women with recurrent implantation failure (RIF) different from that of healthy fertile women? SUMMARY ANSWER: The composition of miRNAs in UF of women with RIF is different from that of healthy fertile women and the dysregulated miRNAs are associated with impaired endometrial receptivity and embryo implantation. WHAT IS KNOWN ALREADY: It has previously been demonstrated that the miRNAs secreted from endometrial cells into the UF contribute to the achievement of endometrial receptivity. Endometrial miRNAs are dysregulated in women with RIF. STUDY DESIGN, SIZE, DURATION: In this descriptive laboratory case-control study, miRNA abundancy was compared between UF collected during implantation phase from healthy fertile women (n = 17) and women with RIF (n = 34), which was defined as three failed IVF cycles with high-quality embryos. PARTICIPANTS/MATERIALS, SETTING, METHODS: Recruitment of study subjects and sampling of UF were performed at two university clinics in Stockholm, Sweden and Tartu, Estonia. The study participants monitored their menstrual cycles using an LH test kit. The UF samples were collected on Day LH + 7-9 by flushing with saline. Samples were processed for small RNA sequencing and mapped for miRNAs. The differential abundance of miRNAs in UF was compared between the two groups using differential expression analysis (DESeq2). Further downstream analyses, including miRNA target gene prediction (miRTarBase), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis (g:Profiler) and external validation using relevant published data, were performed on the dysregulated miRNAs. Two miRNAs were technically validated with quantitative real-time PCR (RT-PCR). MAIN RESULTS AND THE ROLE OF CHANCE: After processing of the sequencing data, there were 15 samples in the healthy fertile group and 33 samples in the RIF group. We found 61 differentially abundant UF miRNAs (34 upregulated and 27 downregulated) in RIF compared to healthy women with a false discovery rate of <0.05 and a fold change (FC) of ≤-2 or ≥2. When analyzed with published literature, we found that several of the differentially abundant miRNAs are expressed in endometrial epithelial cells and have been reported in endometrial extracellular vesicles and in association with endometrial receptivity and RIF. Their predicted target genes were further expressed both in the trophectodermal cells of blastocyst-stage embryos and endometrial mid-secretory epithelial cells, as assessed by publicly available single-cell transcriptome-sequencing studies. Pathway analysis further revealed that 25 pathways, having key roles in endometrial receptivity and implantation, were significantly enriched. Hsa-miR-486-5p (FC -20.32; P-value = 0.004) and hsa-miR-92b-3p (FC -9.72; P-value = 0.004) were successfully technically validated with RT-PCR. LARGE SCALE DATA: The data are available in Gene Expression Omnibus (GEO) at https://www.ncbi.nlm.nih.gov/geo/ with GEO accession number: GSE173289. LIMITATIONS, REASONS FOR CAUTION: This is a descriptive study with a limited number of study participants. Moreover, the identified differentially abundant miRNAs should be validated in a larger study cohort, and the predicted miRNA target genes and enriched pathways in RIF need to be confirmed and further explored in vitro. WIDER IMPLICATIONS OF THE FINDINGS: RIF is a major challenge in the current IVF setting with no diagnostic markers nor effective treatment options at hand. For the first time, total miRNAs have been extensively mapped in receptive phase UF of both healthy women with proven fertility and women diagnosed with RIF. Our observations shed further light on the molecular mechanisms behind RIF, with possible implications in future biomarker and clinical treatment studies. STUDY FUNDING/COMPETING INTEREST(S): This work was financially supported by the Swedish Research Council (2017-00932), a joint grant from Region Stockholm and Karolinska Institutet (ALF Medicine 2020, FoUI-954072), Estonian Research Council (PRG1076), Horizon 2020 innovation (ERIN, EU952516) and European Commission and Enterprise Estonia (EU48695). The authors have no competing interests to declare for the current study.

Identification of extremely GC-rich micro RNAs for RT-qPCR data normalization in human plasma.

We aimed at extending the repertoire of high-quality miRNA normalizers for reverse transcription-quantitative PCR (RT-qPCR) of human plasma with special emphasis on the extremely guanine-cytosine-rich portion of the miRNome. For high-throughput selection of stable candidates, microarray technology was preferred over small-RNA sequencing (sRNA-seq) since the latter underrepresented miRNAs with a guanine-cytosine (GC) content of at least 75% (p = 0.0002, n = 2). miRNA abundances measured on the microarray were ranked for consistency and uniformity using nine normalization approaches. The eleven most stable sequences included miRNAs of moderate, but also extreme GC content (45%-65%: miR-320d, miR-425-5p, miR-185-5p, miR-486-5p; 80%-95%: miR-1915-3p, miR-3656-5p, miR-3665-5p, miR-3960-5p, miR-4488-5p, miR-4497 and miR-4787-5p). In contrast, the seven extremely GC-rich miRNAs were not found in the two plasma miRNomes screened by sRNA-seq. Stem-loop RT-qPCR was employed for stability verification in 32 plasma samples of healthy male Caucasians (age range: 18-55 years). In general, inter-individual variance of miRNA abundance was low or very low as indicated by coefficient of variation (CV) values of 0.6%-8.2%. miR-3665 and miR-1915-3p outperformed in this analysis (CVs: 0.6 and 2.4%, respectively). The eight most stable sequences included four extremely GC-rich miRNAs (miR-1915-3p, miR-3665, miR-4787-5p and miR-4497). The best-performing duo normalization factor (NF) for the condition of human plasma, miR-320d and miR-4787-5p, also included a GC-extreme miRNA. In summary, the identification of extremely guanine-cytosine-rich plasma normalizers will help to increase accuracy of PCR-based miRNA quantification, thus raise the potential that miRNAs become markers for psychological stress reactions or early and precise diagnosis of clinical phenotypes. The novel miRNAs might also be useful for orthologous contexts considering their conservation in related animal genomes.

Trophoblast derived extracellular vesicles specifically alter the transcriptome of endometrial cells and may constitute a critical component of embryo-maternal communication.

BACKGROUND: The period of time when the embryo and the endometrium undergo significant morphological alterations to facilitate a successful implantation-known as "window of implantation"-is a critical moment in human reproduction. Embryo and the endometrium communicate extensively during this period, and lipid bilayer bound nanoscale extracellular vesicles (EVs) are purported to be integral to this communication. METHODS: To investigate the nature of the EV-mediated embryo-maternal communication, we have supplemented trophoblast analogue spheroid (JAr) derived EVs to an endometrial analogue (RL 95-2) cell layer and characterized the transcriptomic alterations using RNA sequencing. EVs derived from non-trophoblast cells (HEK293) were used as a negative control. The cargo of the EVs were also investigated through mRNA and miRNA sequencing. RESULTS: Trophoblast spheroid derived EVs induced drastic transcriptomic alterations in the endometrial cells while the non-trophoblast cell derived EVs failed to induce such changes demonstrating functional specificity in terms of EV origin. Through gene set enrichment analysis (GSEA), we found that the response in endometrial cells was focused on extracellular matrix remodelling and G protein-coupled receptors' signalling, both of which are of known functional relevance to endometrial receptivity. Approximately 9% of genes downregulated in endometrial cells were high-confidence predicted targets of miRNAs detected exclusively in trophoblast analogue-derived EVs, suggesting that only a small proportion of reduced expression in endometrial cells can be attributed directly to gene silencing by miRNAs carried as cargo in the EVs. CONCLUSION: Our study reveals that trophoblast derived EVs have the ability to modify the endometrial gene expression, potentially with functional importance for embryo-maternal communication during implantation, although the exact underlying signalling mechanisms remain to be elucidated.

Small noncoding RNA profiling across cellular and biofluid compartments and their implications for multiple sclerosis immunopathology.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease affecting the central nervous system (CNS). Small non-coding RNAs (sncRNAs) and, in particular, microRNAs (miRNAs) have frequently been associated with MS. Here, we performed a comprehensive analysis of all classes of sncRNAs in matching samples of peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF) cells, and cell-free CSF from relapsing-remitting (RRMS, n = 12 in relapse and n = 11 in remission) patients, secondary progressive (SPMS, n = 6) MS patients, and noninflammatory and inflammatory neurological disease controls (NINDC, n = 11; INDC, n = 5). We show widespread changes in miRNAs and sncRNA-derived fragments of small nuclear, nucleolar, and transfer RNAs. In CSF cells, 133 out of 133 and 115 out of 117 differentially expressed sncRNAs were increased in RRMS relapse compared to remission and RRMS compared to NINDC, respectively. In contrast, 65 out of 67 differentially expressed PBMC sncRNAs were decreased in RRMS compared to NINDC. The striking contrast between the periphery and CNS suggests that sncRNA-mediated mechanisms, including alternative splicing, RNA degradation, and mRNA translation, regulate the transcriptome of pathogenic cells primarily in the CNS target organ.

Single-cell RNA counting at allele and isoform resolution using Smart-seq3.

Large-scale sequencing of RNA from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states1. However, current short-read single-cell RNA-sequencing methods have limited ability to count RNAs at allele and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells2,3. Here we introduce Smart-seq3, which combines full-length transcriptome coverage with a 5' unique molecular identifier RNA counting strategy that enables in silico reconstruction of thousands of RNA molecules per cell. Of the counted and reconstructed molecules, 60% could be directly assigned to allelic origin and 30-50% to specific isoforms, and we identified substantial differences in isoform usage in different mouse strains and human cell types. Smart-seq3 greatly increased sensitivity compared to Smart-seq2, typically detecting thousands more transcripts per cell. We expect that Smart-seq3 will enable large-scale characterization of cell types and states across tissues and organisms.

Author Correction: Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Genomic encoding of transcriptional burst kinetics.

Mammalian gene expression is inherently stochastic1,2, and results in discrete bursts of RNA molecules that are synthesized from each allele3-7. Although transcription is known to be regulated by promoters and enhancers, it is unclear how cis-regulatory sequences encode transcriptional burst kinetics. Characterization of transcriptional bursting, including the burst size and frequency, has mainly relied on live-cell4,6,8 or single-molecule RNA fluorescence in situ hybridization3,5,8,9 recordings of selected loci. Here we determine transcriptome-wide burst frequencies and sizes for endogenous mouse and human genes using allele-sensitive single-cell RNA sequencing. We show that core promoter elements affect burst size and uncover synergistic effects between TATA and initiator elements, which were masked at mean expression levels. Notably, we provide transcriptome-wide evidence that enhancers control burst frequencies, and demonstrate that cell-type-specific gene expression is primarily shaped by changes in burst frequencies. Together, our data show that burst frequency is primarily encoded in enhancers and burst size in core promoters, and that allelic single-cell RNA sequencing is a powerful model for investigating transcriptional kinetics.

Small-seq for single-cell small-RNA sequencing.

Small RNAs participate in several cellular processes, including splicing, RNA modification, mRNA degradation, and translational arrest. Traditional methods for sequencing small RNAs require a large amount of cell material, limiting the possibilities for single-cell analyses. We describe Small-seq, a ligation-based method that enables the capture, sequencing, and molecular counting of small RNAs from individual mammalian cells. Here, we provide a detailed protocol for this approach that relies on standard reagents and instruments. The standard protocol captures a complex set of small RNAs, including microRNAs (miRNAs), fragments of tRNAs and small nucleolar RNAs (snoRNAs); however, miRNAs can be enriched through the addition of a size-selection step. Ready-to-sequence libraries can be generated in 2-3 d, starting from cell collection, with additional days needed to computationally map the sequence reads and calculate molecular counts.

Single-cell sequencing of the small-RNA transcriptome.

Little is known about the heterogeneity of small-RNA expression as small-RNA profiling has so far required large numbers of cells. Here we present a single-cell method for small-RNA sequencing and apply it to naive and primed human embryonic stem cells and cancer cells. Analysis of microRNAs and fragments of tRNAs and small nucleolar RNAs (snoRNAs) reveals the potential of microRNAs as markers for different cell types and states.

In Vivo Effects of Mesenchymal Stromal Cells in Two Patients With Severe Acute Respiratory Distress Syndrome.

UNLABELLED: Mesenchymal stromal cells (MSCs) have been investigated as a treatment for various inflammatory diseases because of their immunomodulatory and reparative properties. However, many basic questions concerning their mechanisms of action after systemic infusion remain unanswered. We performed a detailed analysis of the immunomodulatory properties and proteomic profile of MSCs systemically administered to two patients with severe refractory acute respiratory distress syndrome (ARDS) on a compassionate use basis and attempted to correlate these with in vivo anti-inflammatory actions. Both patients received 2×10(6) cells per kilogram, and each subsequently improved with resolution of respiratory, hemodynamic, and multiorgan failure. In parallel, a decrease was seen in multiple pulmonary and systemic markers of inflammation, including epithelial apoptosis, alveolar-capillary fluid leakage, and proinflammatory cytokines, microRNAs, and chemokines. In vitro studies of the MSCs demonstrated a broad anti-inflammatory capacity, including suppression of T-cell responses and induction of regulatory phenotypes in T cells, monocytes, and neutrophils. Some of these in vitro potency assessments correlated with, and were relevant to, the observed in vivo actions. These experiences highlight both the mechanistic information that can be gained from clinical experience and the value of correlating in vitro potency assessments with clinical effects. The findings also suggest, but do not prove, a beneficial effect of lung protective strategies using adoptively transferred MSCs in ARDS. Appropriate randomized clinical trials are required to further assess any potential clinical efficacy and investigate the effects on in vivo inflammation. SIGNIFICANCE: This article describes the cases of two patients with severe refractory adult respiratory syndrome (ARDS) who failed to improve after both standard life support measures, including mechanical ventilation, and additional measures, including extracorporeal ventilation (i.e., in a heart-lung machine). Unlike acute forms of ARDS (such in the current NIH-sponsored study of mesenchymal stromal cells in ARDS), recovery does not generally occur in such patients.

Epstein-Barr virus encoded microRNAs target SUMO-regulated cellular functions.

Post-translational modification by the small ubiquitin-like modifier (SUMO) regulates the cellular response to different types of stress and plays a pivotal role in the control of oncogenic viral infections. Here we investigated the capacity of microRNAs (miRNAs) encoded by Epstein-Barr virus to interfere with the SUMO signaling network. Using a computational strategy that scores different properties of miRNA-mRNA target pairs, we identified a minimal set of 575 members of the SUMO interactome that may be targeted by one or more Epstein-Barr virus miRNAs. A significant proportion of the candidates cluster in a functional network that controls chromatin organization, stress, DNA damage and immune responses, apoptosis and transforming growth factor beta signaling. Multiple components of the transforming growth factor beta signaling pathway were inhibited upon upregulation of the BamHI-H rightward open reading frame 1 (BHRF1) encoded miRNAs in cells transduced with recombinant lentiviruses or entering the productive virus cycle. These findings point to the capacity of viral miRNAs to interfere with SUMO-regulated cellular functions that control key aspects of viral replication and pathogenesis.

Full-length RNA-seq from single cells using Smart-seq2.

Emerging methods for the accurate quantification of gene expression in individual cells hold promise for revealing the extent, function and origins of cell-to-cell variability. Different high-throughput methods for single-cell RNA-seq have been introduced that vary in coverage, sensitivity and multiplexing ability. We recently introduced Smart-seq for transcriptome analysis from single cells, and we subsequently optimized the method for improved sensitivity, accuracy and full-length coverage across transcripts. Here we present a detailed protocol for Smart-seq2 that allows the generation of full-length cDNA and sequencing libraries by using standard reagents. The entire protocol takes ∼2 d from cell picking to having a final library ready for sequencing; sequencing will require an additional 1-3 d depending on the strategy and sequencer. The current limitations are the lack of strand specificity and the inability to detect nonpolyadenylated (polyA(-)) RNA.

Smart-seq2 for sensitive full-length transcriptome profiling in single cells.

Single-cell gene expression analyses hold promise for characterizing cellular heterogeneity, but current methods compromise on either the coverage, the sensitivity or the throughput. Here, we introduce Smart-seq2 with improved reverse transcription, template switching and preamplification to increase both yield and length of cDNA libraries generated from individual cells. Smart-seq2 transcriptome libraries have improved detection, coverage, bias and accuracy compared to Smart-seq libraries and are generated with off-the-shelf reagents at lower cost.

Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.

Genome-wide transcriptome analyses are routinely used to monitor tissue-, disease- and cell type­specific gene expression, but it has been technically challenging to generate expression profiles from single cells. Here we describe a robust mRNA-Seq protocol (Smart-Seq) that is applicable down to single cell levels. Compared with existing methods, Smart-Seq has improved read coverage across transcripts, which enhances detailed analyses of alternative transcript isoforms and identification of single-nucleotide polymorphisms. We determined the sensitivity and quantitative accuracy of Smart-Seq for single-cell transcriptomics by evaluating it on total RNA dilution series. We found that although gene expression estimates from single cells have increased noise, hundreds of differentially expressed genes could be identified using few cells per cell type. Applying Smart-Seq to circulating tumor cells from melanomas, we identified distinct gene expression patterns, including candidate biomarkers for melanoma circulating tumor cells. Our protocol will be useful for addressing fundamental biological problems requiring genome-wide transcriptome profiling in rare cells.

Analysis of microRNA signatures using size-coded ligation-mediated PCR.

The expression pattern and regulatory functions of microRNAs (miRNAs) are intensively investigated in various tissues, cell types and disorders. Differential miRNA expression signatures have been revealed in healthy and unhealthy tissues using high-throughput profiling methods. For further analyses of miRNA signatures in biological samples, we describe here a simple and efficient method to detect multiple miRNAs simultaneously in total RNA. The size-coded ligation-mediated polymerase chain reaction (SL-PCR) method is based on size-coded DNA probe hybridization in solution, followed-by ligation, PCR amplification and gel fractionation. The new method shows quantitative and specific detection of miRNAs. We profiled miRNAs of the let-7 family in a number of organisms, tissues and cell types and the results correspond with their incidence in the genome and reported expression levels. Finally, SL-PCR detected let-7 expression changes in human embryonic stem cells as they differentiate to neuron and also in young and aged mice brain and bone marrow. We conclude that the method can efficiently reveal miRNA signatures in a range of biological samples.