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Autologous epidermal cultures restore a functional epidermis on burned patients. Transgenic epidermal grafts do so also in genetic skin diseases such as Junctional Epidermolysis Bullosa. Clinical success strictly requires an adequate number of epidermal stem cells, detected as holoclone-forming cells, which can be only partially distinguished from the other clonogenic keratinocytes and cannot be prospectively isolated. Here we report that single-cell transcriptome analysis of primary human epidermal cultures identifies categories of genes clearly distinguishing the different keratinocyte clonal types, which are hierarchically organized along a continuous, mainly linear trajectory showing that stem cells sequentially generate progenitors producing terminally differentiated cells. Holoclone-forming cells display stem cell hallmarks as genes regulating DNA repair, chromosome segregation, spindle organization and telomerase activity. Finally, we identify FOXM1 as a YAP-dependent key regulator of epidermal stem cells. These findings improve criteria for measuring stem cells in epidermal cultures, which is an essential feature of the graft. Epidermal cultures can treat skin diseases, such as Junctional Epidermolysis Bullosa, but the signature of stem cells is unclear. By single cell RNAseq analyses on human keratinocytes, the authors identify the molecular profile of holoclones and the role of FOXM1 in regulating the proliferative potential of epidermal stem cells.

T cell memory relies on the generation of antigen-specific progenitors with stem-like properties. However, the identity of these progenitors has remained unclear, precluding a full understanding of the differentiation trajectories that underpin the heterogeneity of antigen-experienced T cells. We used a systematic approach guided by single-cell RNA-sequencing data to map the organizational structure of the human CD8 + memory T cell pool under physiological conditions. We identified two previously unrecognized subsets of clonally, epigenetically, functionally, phenotypically and transcriptionally distinct stem-like CD8 + memory T cells. Progenitors lacking the inhibitory receptors programmed death-1 (PD-1) and T cell immunoreceptor with Ig and ITIM domains (TIGIT) were committed to a functional lineage, whereas progenitors expressing PD-1 and TIGIT were committed to a dysfunctional, exhausted-like lineage. Collectively, these data reveal the existence of parallel differentiation programs in the human CD8 + memory T cell pool, with potentially broad implications for the development of immunotherapies and vaccines. The identity of stem-cell memory progenitor cells has been unclear. Lugli and colleagues use high-dimensional approaches to identify two new progenitor populations of human T cells—one giving rise to a functional lineage, the other to an exhausted-like one.

The molecular mechanisms responsible for the high immunosuppressive capacity of CD4+ Tregs in tumors are not well known. High-dimensional single-cell profiling of T cells from chemotherapy-naive individuals with non-small-cell lung cancer identified the transcription factor IRF4 as specifically expressed by a subset of intratumoral CD4+ effector Tregs with superior suppressive activity. In contrast to the IRF4- counterparts, IRF4+ Tregs expressed a vast array of suppressive molecules, and their presence correlated with multiple exhausted subpopulations of T cells. Integration of transcriptomic and epigenomic data revealed that IRF4, either alone or in combination with its partner BATF, directly controlled a molecular program responsible for immunosuppression in tumors. Accordingly, deletion of Irf4 exclusively in Tregs resulted in delayed tumor growth in mice while the abundance of IRF4+ Tregs correlated with poor prognosis in patients with multiple human cancers. Thus, a common mechanism underlies immunosuppression in the tumor microenvironment irrespective of the tumor type.

Human gut microbiota directly influences health and provides an extra means of adaptive potential to different lifestyles. To explore variation in gut microbiota and to understand how these bacteria may have co-evolved with humans, here we investigate the phylogenetic diversity and metabolite production of the gut microbiota from a community of human hunter-gatherers, the Hadza of Tanzania. We show that the Hadza have higher levels of microbial richness and biodiversity than Italian urban controls. Further comparisons with two rural farming African groups illustrate other features unique to Hadza that can be linked to a foraging lifestyle. These include absence of Bifidobacterium and differences in microbial composition between the sexes that probably reflect sexual division of labour. Furthermore, enrichment in Prevotella , Treponema and unclassified Bacteroidetes , as well as a peculiar arrangement of Clostridiales taxa, may enhance the Hadza’s ability to digest and extract valuable nutrition from fibrous plant foods. Gut microbes influence our health and may contribute to human adaptation to different lifestyles. Here, the authors describe the gut microbiome of a community of hunter-gatherers and identify unique features that could be linked to a foraging lifestyle.

The gut microbiota exerts a role in type 2 diabetes (T2D), and deviations from a mutualistic ecosystem layout are considered a key environmental factor contributing to the disease. Thus, the possibility of improving metabolic control in T2D by correcting gut microbiome dysbioses through diet has been evaluated. Here, we explore the potential of two different energy-restricted dietary approaches – the fibre-rich macrobiotic Ma-Pi 2 diet or a control diet recommended by Italian professional societies for T2D treatment – to correct gut microbiota dysbioses in T2D patients. In a previous 21-d open-label MADIAB trial, fifty-six overweight T2D patients were randomised to the Ma-Pi 2 or the control diet. For the present study, stools were collected before and after intervention from a subset of forty MADIAB participants, allowing us to characterise the gut microbiota by 16S rRNA sequencing and imputed metagenomics. To highlight microbiota dysbioses in T2D, the gut microbiota of thirteen normal-weight healthy controls were characterised. According to our findings, both diets were effective in modulating gut microbiome dysbioses in T2D, resulting in an increase of the ecosystem diversity and supporting the recovery of a balanced community of health-promoting SCFA producers, such as Faecalibacterium, Roseburia, Lachnospira, Bacteroides and Akkermansia. The Ma-Pi 2 diet, but not the control diet, was also effective in counteracting the increase of possible pro-inflammatory groups, such as Collinsella and Streptococcus, in the gut ecosystem, showing the potential to reverse pro-inflammatory dysbioses in T2D, and possibly explaining the greater efficacy in improving the metabolic control.

Long pentraxin 3 (PTX3) is an essential component of humoral innate immunity, involved in resistance to selected pathogens and in the regulation of inflammation 1 – 3 . The present study was designed to assess the presence and significance of PTX3 in Coronavirus Disease 2019 (COVID-19) 4 – 7 . RNA-sequencing analysis of peripheral blood mononuclear cells, single-cell bioinformatics analysis and immunohistochemistry of lung autopsy samples revealed that myelomonocytic cells and endothelial cells express high levels of PTX3 in patients with COVID-19. Increased plasma concentrations of PTX3 were detected in 96 patients with COVID-19. PTX3 emerged as a strong independent predictor of 28-d mortality in multivariable analysis, better than conventional markers of inflammation, in hospitalized patients with COVID-19. The prognostic significance of PTX3 abundance for mortality was confirmed in a second independent cohort (54 patients). Thus, circulating and lung myelomonocytic cells and endothelial cells are a major source of PTX3, and PTX3 plasma concentration can serve as an independent strong prognostic indicator of short-term mortality in COVID-19. Mantovani and colleagues report elevated circulating concentrations of the long pentraxin PTX3 in patients with severe COVID-19. Within this cohort, early detection of high PTX3 concentrations emerged as a strong predictor of decreased survival.

Background In bacterial genomes, there are two mechanisms to terminate the DNA transcription: the “intrinsic” or Rho-independent termination and the Rho-dependent termination. Intrinsic terminators are characterized by a RNA hairpin followed by a run of 6–8 U residues relatively easy to identify using one of the numerous available prediction programs. In contrast, Rho-dependent termination is mediated by the Rho protein factor that, firstly, binds to ribosome-free mRNA in a site characterized by a C > G content and then reaches the RNA polymerase to induce its release. Conversely on intrinsic terminators, the computational prediction of Rho-dependent terminators in prokaryotes is a very difficult problem because the sequence features required for the function of Rho are complex and poorly defined. This is the reason why it still does not exist an exhaustive Rho-dependent terminators prediction program. Results In this study we introduce RhoTermPredict, the first published algorithm for an exhaustive Rho-dependent terminators prediction in bacterial genomes. RhoTermPredict identifies these elements based on a previously proposed consensus motif common to all Rho-dependent transcription terminators. It essentially searches for a 78 nt long RUT site characterized by a C > G content and with regularly spaced C residues, followed by a putative pause site for the RNA polymerase. We tested RhoTermPredict performances by using available genomic and transcriptomic data of the microorganism Escherichia coli K-12, both in limited-length sequences and in the whole-genome, and available genomic sequences from Bacillus subtilis 168 and Salmonella enterica LT2 genomes. We also estimated the overlap between the predictions of RhoTermPredict and those obtained by the predictor of intrinsic terminators ARNold webtool. Our results demonstrated that RhoTermPredict is a very performing algorithm both for limited-length sequences (F 1 -score obtained about 0.7) and for a genome-wide analysis. Furthermore the degree of overlap with ARNold predictions was very low. Conclusions Our analysis shows that RhoTermPredict is a powerful tool for Rho-dependent terminators search in the three analyzed genomes and could fill this gap in computational genomics. We conclude that RhoTermPredict could be used in combination with an intrinsic terminators predictor in order to predict all the transcription terminators in bacterial genomes.

Human induced pluripotent stem cell-derived neural stem/progenitor cells (hiPSC-NSCs) hold promise for treating neurodegenerative and demyelinating disorders. However, comprehensive studies on their identity and safety remain limited. In this study, we demonstrate that hiPSC-NSCs adopt a radial glia-associated signature, sharing key epigenetic and transcriptional characteristics with human fetal neural stem cells (hfNSCs) while exhibiting divergent profiles from glioblastoma stem cells. Long-term transplantation studies in mice showed robust and stable engraftment of hiPSC-NSCs, with predominant differentiation into glial cells and no evidence of tumor formation. Additionally, we identified the Sterol Regulatory Element Binding Transcription Factor 1 (SREBF1) as a regulator of astroglial differentiation in hiPSC-NSCs. These findings provide valuable transcriptional and epigenetic reference datasets to prospectively define the maturation stage of NSCs derived from different hiPSC sources and demonstrate the long-term safety of hiPSC-NSCs, reinforcing their potential as a viable alternative to hfNSCs for clinical applications. Cell products derived from human induced pluripotent stem cells hold promise for regenerative therapies, but the safety of these transplanted cells must be carefully assessed. Here they show that hiPSC-derived neural stem/progenitor cells are able to stably engraft and generate glia cells in transplanted mouse brains with no evidence of tumor formation.

The human gastrointestinal tract (GIT) represents one of the most densely populated microbial ecosystems studied to date. Although this microbial consortium has been recognized to have a crucial impact on human health, its precise composition is still subject to intense investigation. Among the GIT microbiota, bifidobacteria represent an important commensal group, being among the first microbial colonizers of the gut. However, the prevalence and diversity of members of the genus Bifidobacterium in the infant intestinal microbiota has not yet been fully characterized, while some inconsistencies exist in literature regarding the abundance of this genus. In the current report, we assessed the complexity of the infant intestinal bifidobacterial population by analysis of pyrosequencing data of PCR amplicons derived from two hypervariable regions of the 16 S rRNA gene. Eleven faecal samples were collected from healthy infants of different geographical origins (Italy, Spain or Ireland), feeding type (breast milk or formula) and mode of delivery (vaginal or caesarean delivery), while in four cases, faecal samples of corresponding mothers were also analyzed. In contrast to several previously published culture-independent studies, our analysis revealed a predominance of bifidobacteria in the infant gut as well as a profile of co-occurrence of bifidobacterial species in the infant's intestine.

Background Over the last few decades, computational genomics has tremendously contributed to decipher biology from genome sequences and related data. Considerable effort has been devoted to the prediction of transcription promoter and terminator sites that represent the essential “punctuation marks” for DNA transcription. Computational prediction of promoters in prokaryotes is a problem whose solution is far from being determined in computational genomics. The majority of published bacterial promoter prediction tools are based on a consensus-sequences search and they were designed specifically for vegetative σ 70 promoters and, therefore, not suitable for promoter prediction in bacteria encoding a lot of σ factors, like actinomycetes. Results In this study we investigated the possibility to identify putative promoters in prokaryotes based on evolutionarily conserved motifs, and focused our attention on GC-rich bacteria in which promoter prediction with conventional, consensus-based algorithms is often not-exhaustive. Here, we introduce G4PromFinder, a novel algorithm that predicts putative promoters based on AT-rich elements and G-quadruplex DNA motifs. We tested its performances by using available genomic and transcriptomic data of the model microorganisms Streptomyces coelicolor A3(2) and Pseudomonas aeruginosa PA14. We compared our results with those obtained by three currently available promoter predicting algorithms: the σ 70 consensus-based PePPER, the σ factors consensus-based bTSSfinder, and PromPredict which is based on double-helix DNA stability. Our results demonstrated that G4PromFinder is more suitable than the three reference tools for both the genomes. In fact our algorithm achieved the higher accuracy (F 1 -scores 0.61 and 0.53 in the two genomes) as compared to the next best tool that is PromPredict (F 1 -scores 0.46 and 0.48). Consensus-based algorithms produced lower performances with the analyzed GC-rich genomes. Conclusions Our analysis shows that G4PromFinder is a powerful tool for promoter search in GC-rich bacteria, especially for bacteria coding for a lot of σ factors, such as the model microorganism S. coelicolor A3(2). Moreover consensus-based tools and, in general, tools that are based on specific features of bacterial σ factors seem to be less performing for promoter prediction in these types of bacterial genomes.