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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.

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 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.

BackgroundThe 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.MethodsTo 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.ResultsTrophoblast 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.ConclusionOur 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.

Multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system (CNS), is associated with dysregulation of microRNAs (miRNA). We here analyzed all classes of small non-coding RNAs (sncRNAs) in matching peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF) cells and cell-free CSF from relapsing-remitting (RRMS, n=12 in relapse, n=11 in remission), secondary progressive (SPMS, n=6) MS patients and non-inflammatory and inflammatory neurological disease controls (NINDC, n=11; INDC, n=5). We show widespread changes in small nuclear, nucleolar, transfer RNAs and miRNAs. In CSF cells, 133/133 and 115/117 differentially expressed sncRNAs are increased in RRMS relapse compared to remission and RRMS compared to NINDC, respectively. In contrast, 65/67 differentially expressed PBMC sncRNAs are decreased in RRMS compared to NINDC. The striking contrast between 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 target organ.

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. Faridani and colleagues describe Small-seq, a protocol for generating sequencing libraries of small RNAs from single cells.

Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states1. However, current single-cell RNA-sequencing (scRNA-seq) 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 that combines full-length transcriptome coverage with a 5’ unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.

Large-scale sequencing of RNA from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states

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. Allele-specific single-cell RNA sequencing provides insights into transcription kinetics, with data indicating that core promoter sequences affect burst size, whereas enhancers mainly affect burst frequency.

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.

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.

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.

Antisense agents that target growth-essential genes display surprisingly potent bactericidal properties. In particular, peptide nucleic acid (PNA) and phosphorodiamidate morpholino oligomers linked to cationic carrier peptides are effective in time kill assays and as inhibitors of bacterial peritonitis in mice. It is unclear how these relatively large antimicrobials overcome stringent bacterial barriers and mediate killing. Here we determined the transit kinetics of peptide–PNAs and observed an accumulation of cell-associated PNA in Escherichia coli and slow efflux. An inhibitor of drug efflux pumps did not alter peptide–PNA potency, indicating a lack of active efflux from cells. Consistent with cell retention, the post-antibiotic effect (PAE) of the anti-acyl carrier protein (acpP) peptide–PNA was greater than 11 hours. Bacterial cell accumulation and a long PAE are properties of significant interest for antimicrobial development.

A combination of single-cell transcriptomics with in situ hybridization information enables single cells to be positioned within their tissue.

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.

Genome-wide transcriptome analyses are routinely used to monitor tissue-, disease- and cell type–specific 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.

The large tegument proteins of herpesviruses encode conserved cysteine proteases of unknown function. Here we show that BPLF1, the Epstein-Barr-virus-encoded member of this protease family, is a deneddylase that regulates virus production by modulating the activity of cullin-RING ligases (CRLs). BPLF1 hydrolyses NEDD8 conjugates in vitro, acts as a deneddylase in vivo, binds to cullins and stabilizes CRL substrates. Expression of BPLF1 alone or in the context of the productive virus cycle induces accumulation of the licensing factor CDT1 and deregulates S-phase DNA synthesis. Inhibition of BPLF1 during the productive virus cycle prevents cellular DNA re-replication and inhibits virus replication. Viral DNA synthesis is restored by overexpression of CDT1. Homologues encoded by other herpesviruses share the deneddylase activity. Thus, these enzymes are likely to have a key function in the virus life cycle by inducing a replication-permissive S-phase-like cellular environment.

Double-stranded RNA (dsRNA) is formed in cells as intra- and intermolecular RNA interactions and is involved in a range of biological processes including RNA metabolism, RNA interference and translation control mediated by natural antisense RNA and microRNA. Despite this breadth of activities, few molecular tools are available to analyse dsRNA as native hybrids. We describe a two-step ligation method for enzymatic joining of dsRNA adaptors to any dsRNA molecule in its duplex form without a need for prior sequence or termini information. The method is specific for dsRNA and can ligate various adaptors to label, map or amplify dsRNA sequences. When combined with reverse transcription–polymerase chain reaction, the method is sensitive and can detect low nanomolar concentrations of dsRNA in total RNA. As examples, we mapped dsRNA/single-stranded RNA junctions within Escherichia coli hok mRNA and the human immunodeficiency virus TAR element using RNA from bacteria and mammalian cells.

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 × 106 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.

Short regulatory RNAs are widespread in bacteria,and many function through antisense recognitionof mRNA. Among the best studied antisensetranscripts are RNA antitoxins that repress toxinmRNA translation. The hok/sok locus of plasmid R1from Escherichia coli is an established model forRNA antitoxin action. Base-pairing between hokmRNA and Sok-antisense-RNA increases plasmidmaintenance through post-segregational-killing ofplasmid-free progeny cells. To test the model andthe idea that sequestration of Sok-RNA activity couldprovide a novel antimicrobial strategy, we designedanti Sok peptide nucleic acid (PNA) oligomers that,according to the model, would act as competitiveinhibitors of hok mRNA::Sok-RNA interactions. Inhok/sok-carrying cells, anti Sok PNAs were morebactericidal than rifampicin. Also, anti Sok PNAsinduced ghost cell morphology and an accumulationof mature hok mRNA, consistent with cell killingthrough synthesis of Hok protein. The results sup-port the sense/antisense model for hok mRNArepression by Sok-RNA and demonstrate that anti-sense agents can be used to out-compete RNA::RNAinteractions in bacteria. Finally, BLAST analyses of 200 prokaryotic genomes revealed that manyenteric bacteria have multiple hok/sok homologousand analogous RNA-regulated toxin–antitoxin loci.Therefore, it is possible to activate suicide in bacteriaby targeting antitoxins.INTRODUCTIONNon-coding regulatory RNAs are widely expressed in manygenomes (1,2). A large number of non-coding RNAs arecomplementary to active open reading frames, yet there isonly limited evidence for direct sense/antisense interactions.Antisense transcripts are encoded both in-cis and in-transand are believed to modulate RNA processing, decay andtranslation through direct pairing with complementary targetsequences (3). Bacterial genomes and plasmids contain anumber of annotated as well as predicted sense and antisensegenes. Despite predictions of widespread sense/antisensepairing in several species (4–7), there have been few attemptsto experimentally probe these structures and test the effects ofdisrupted interactions (8).A paradigm for sense/antisense RNA pairing is the hok/soktoxin–antitoxin (TA) plasmid stabilization locus of theR1 plasmid in E. coli (9). The hok/sok locus codes for threegenes: hok (host killing) encodes a highly toxic trans-membrane protein that irreversibly damages the cell mem-brane (10). The mok (modulation of killing) reading frameoverlaps with hok sequences and is required for hok expres-sion and translation. Finally, the sok (suppression of killing)gene encodes a small antisense RNA in-cis that blocks trans-lation of the mok reading frame and thus inhibits expressionof hokmRNA (11). Pairing between Sok and transcriptsis supported by in vitro and phylogenetic studies (12–14).Sok-RNA is very unstable (half-life in the order of 30 s)but driven by a strong promoter. In contrast, the full-lengthhok transcript is heavily structured, stable (half-life in theorder of 30 min) and inaccessible to either ribosome initiationor Sok-RNA binding. Slow 3

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.

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.