A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer

MCM8 interacts with DDX5 to promote R-loop resolution

MCM8 has emerged as a core gene in reproductive aging and is crucial for meiotic homologous recombination repair. It also safeguards genome stability by coordinating the replication stress response during mitosis, but its function in mitotic germ cells remains elusive. Here we found that disabling MCM8 in mice resulted in proliferation defects of primordial germ cells (PGCs) and ultimately impaired fertility. We further demonstrated that MCM8 interacted with two known helicases DDX5 and DHX9, and loss of MCM8 led to R-loop accumulation by reducing the retention of these helicases at R-loops, thus inducing genome instability. Cells expressing premature ovarian insufficiency-causative mutants of MCM8 with decreased interaction with DDX5 displayed increased R-loop levels. These results show MCM8 interacts with R-loop-resolving factors to prevent R-loop-induced DNA damage, which may contribute to the maintenance of genome integrity of PGCs and reproductive reserve establishment. Our findings thus reveal an essential role for MCM8 in PGC development and improve our understanding of reproductive aging caused by genome instability in mitotic germ cells.

Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19

Dexamethasone is the standard of care for critically ill patients with COVID-19, but the mechanisms by which it decreases mortality and its immunological effects in this setting are not understood. Here we perform bulk and single-cell RNA sequencing of samples from the lower respiratory tract and blood, and assess plasma cytokine profiling to study the effects of dexamethasone on both systemic and pulmonary immune cell compartments. In blood samples, dexamethasone is associated with decreased expression of genes associated with T cell activation, including TNFSFR4 and IL21R. We also identify decreased expression of several immune pathways, including major histocompatibility complex-II signaling, selectin P ligand signaling, and T cell recruitment by intercellular adhesion molecule and integrin activation, suggesting these are potential mechanisms of the therapeutic benefit of steroids in COVID-19. We identify additional compartment- and cell- specific differences in the effect of dexamethasone that are reproducible in publicly available datasets, including steroid-resistant interferon pathway expression in the respiratory tract, which may be additional therapeutic targets. In summary, we demonstrate compartment-specific effects of dexamethasone in critically ill COVID-19 patients, providing mechanistic insights with potential therapeutic relevance. Our results highlight the importance of studying compartmentalized inflammation in critically ill patients.

Adult Human, but Not Rodent, Spermatogonial Stem Cells Retain States with a Foetal-like Signature

Spermatogenesis involves a complex process of cellular differentiation maintained by spermatogonial stem cells (SSCs). Being critical to male reproduction, it is generally assumed that spermatogenesis starts and ends in equivalent transcriptional states in related species. Based on single-cell gene expression profiling, it has been proposed that undifferentiated human spermatogonia can be subclassified into four heterogenous subtypes, termed states 0, 0A, 0B, and 1. To increase the resolution of the undifferentiated compartment and trace the origin of the spermatogenic trajectory, we re-analysed the single-cell (sc) RNA-sequencing libraries of 34 post-pubescent human testes to generate an integrated atlas of germ cell differentiation. We then used this atlas to perform comparative analyses of the putative SSC transcriptome both across human development (using 28 foetal and pre-pubertal scRNA-seq libraries) and across species (including data from sheep, pig, buffalo, rhesus and cynomolgus macaque, rat, and mouse). Alongside its detailed characterisation, we show that the transcriptional heterogeneity of the undifferentiated spermatogonial cell compartment varies not only between species but across development. Our findings associate 'state 0B' with a suppressive transcriptomic programme that, in adult humans, acts to functionally oppose proliferation and maintain cells in a ready-to-react state. Consistent with this conclusion, we show that human foetal germ cells-which are mitotically arrested-can be characterised solely as state 0B. While germ cells with a state 0B signature are also present in foetal mice (and are likely conserved at this stage throughout mammals), they are not maintained into adulthood. We conjecture that in rodents, the foetal-like state 0B differentiates at birth into the renewing SSC population, whereas in humans it is maintained as a reserve population, supporting testicular homeostasis over a longer reproductive lifespan while reducing mutagenic load. Together, these results suggest that SSCs adopt differing evolutionary strategies across species to ensure fertility and genome integrity over vastly differing life histories and reproductive timeframes.

Dysregulation of CD4+ and CD8+ resident memory T, myeloid, and stromal cells in steroid-experienced, checkpoint inhibitor colitis

BACKGROUND

Colitis caused by checkpoint inhibitors (CPI) is frequent and is treated with empiric steroids, but CPI colitis mechanisms in steroid-experienced or refractory disease are unclear.

METHODS

Using colon biopsies and blood from predominantly steroid-experienced CPI colitis patients, we performed multiplexed single-cell transcriptomics and proteomics to nominate contributing populations.

RESULTS

CPI colitis biopsies showed enrichment of CD4+resident memory (RM) T cells in addition to CD8+ RM and cytotoxic CD8+ T cells. Matching T cell receptor (TCR) clonotypes suggested that both RMs are progenitors that yield cytotoxic effectors. Activated, CD38+ HLA-DR+ CD4+ RM and cytotoxic CD8+ T cells were enriched in steroid-experienced and a validation data set of steroid-naïve CPI colitis, underscoring their pathogenic potential across steroid exposure. Distinct from ulcerative colitis, CPI colitis exhibited perturbed stromal metabolism (NAD+, tryptophan) impacting epithelial survival and inflammation. Endothelial cells in CPI colitis after anti-TNF and anti-cytotoxic T-lymphocyte-associated antigen 4 (anti-CTLA-4) upregulated the integrin α4β7 ligand molecular vascular addressin cell adhesion molecule 1 (MAdCAM-1), which may preferentially respond to vedolizumab (anti-α4β7).

CONCLUSIONS

These findings nominate CD4+ RM and MAdCAM-1+ endothelial cells for targeting in specific subsets of CPI colitis patients.

RNA damage compartmentalization by DHX9 stress granules

Biomolecules incur damage during stress conditions, and damage partitioning represents a vital survival strategy for cells. Here, we identified a distinct stress granule (SG), marked by dsRNA helicase DHX9, which compartmentalizes ultraviolet (UV)-induced RNA, but not DNA, damage. Our FANCI technology revealed that DHX9 SGs are enriched in damaged intron RNA, in contrast to classical SGs that are composed of mature mRNA. UV exposure causes RNA crosslinking damage, impedes intron splicing and decay, and triggers DHX9 SGs within daughter cells. DHX9 SGs promote cell survival and induce dsRNA-related immune response and translation shutdown, differentiating them from classical SGs that assemble downstream of translation arrest. DHX9 modulates dsRNA abundance in the DHX9 SGs and promotes cell viability. Autophagy receptor p62 is activated and important for DHX9 SG disassembly. Our findings establish non-canonical DHX9 SGs as a dedicated non-membrane-bound cytoplasmic compartment that safeguards daughter cells from parental RNA damage.

Proteome-scale movements and compartment connectivity during the eukaryotic cell cycle

Cell cycle progression relies on coordinated changes in the composition and subcellular localization of the proteome. By applying two distinct convolutional neural networks on images of millions of live yeast cells, we resolved proteome-level dynamics in both concentration and localization during the cell cycle, with resolution of ∼20 subcellular localization classes. We show that a quarter of the proteome displays cell cycle periodicity, with proteins tending to be controlled either at the level of localization or concentration, but not both. Distinct levels of protein regulation are preferentially utilized for different aspects of the cell cycle, with changes in protein concentration being mostly involved in cell cycle control and changes in protein localization in the biophysical implementation of the cell cycle program. We present a resource for exploring global proteome dynamics during the cell cycle, which will aid in understanding a fundamental biological process at a systems level.

Expression and function of NF-Y subunits in cancer

NF-Y is a Transcription Factor (TF) targeting the CCAAT box regulatory element. It consists of the NF-YB/NF-YC heterodimer, each containing an Histone Fold Domain (HFD), and the sequence-specific subunit NF-YA. NF-YA expression is associated with cell proliferation and absent in some post-mitotic cells. The review summarizes recent findings impacting on cancer development. The logic of the NF-Y regulome points to pro-growth, oncogenic genes in the cell-cycle, metabolism and transcriptional regulation routes. NF-YA is involved in growth/differentiation decisions upon cell-cycle re-entry after mitosis and it is widely overexpressed in tumors, the HFD subunits in some tumor types or subtypes. Overexpression of NF-Y -mostly NF-YA- is oncogenic and decreases sensitivity to anti-neoplastic drugs. The specific roles of NF-YA and NF-YC isoforms generated by alternative splicing -AS- are discussed, including the prognostic value of their levels, although the specific molecular mechanisms of activity are still to be deciphered.

Single-cell and spatial multi-omics highlight effects of anti-integrin therapy across cellular compartments in ulcerative colitis

Ulcerative colitis (UC) is driven by immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin antibody that is effective for treating UC. VDZ is known to inhibit lymphocyte trafficking to the intestine, but its broader effects on other cell subsets are less defined. To identify the inflammatory cells that contribute to colitis and are affected by VDZ, we perform single-cell transcriptomic and proteomic analyses of peripheral blood and colonic biopsies in healthy controls and patients with UC on VDZ or other therapies. Here we show that VDZ treatment is associated with alterations in circulating and tissue mononuclear phagocyte (MNP) subsets, along with modest shifts in lymphocytes. Spatial multi-omics of formalin-fixed biopsies demonstrates trends towards increased abundance and proximity of MNP and fibroblast subsets in active colitis. Spatial transcriptomics of archived specimens pre-treatment identifies epithelial-, MNP-, and fibroblast-enriched genes related to VDZ responsiveness, highlighting important roles for these subsets in UC.

Single-cell and spatial multi-omics highlight effects of anti-integrin therapy across cellular compartments in ulcerative colitis

Ulcerative colitis (UC) is driven by immune and stromal subsets, culminating in epithelial injury. Vedolizumab (VDZ) is an anti-integrin antibody that is effective for treating UC. VDZ is known to inhibit lymphocyte trafficking to the intestine, but its broader effects on other cell subsets are less defined. To identify the inflammatory cells that contribute to colitis and are affected by VDZ, we performed single-cell transcriptomic and proteomic analyses of peripheral blood and colonic biopsies in healthy controls and patients with UC on VDZ or other therapies. Here we show that VDZ treatment is associated with alterations in circulating and tissue mononuclear phagocyte (MNP) subsets, along with modest shifts in lymphocytes. Spatial multi-omics of formalin-fixed biopsies demonstrates trends towards increased abundance and proximity of MNP and fibroblast subsets in active colitis. Spatial transcriptomics of archived specimens pre-treatment identifies epithelial-, MNP-, and fibroblast-enriched genes related to VDZ responsiveness, highlighting important roles for these subsets in UC.

Loss of p53-DREAM-mediated repression of cell cycle genes as a driver of lymph node metastasis in head and neck cancer

BACKGROUND

The prognosis for patients with head and neck cancer (HNC) is poor and has improved little in recent decades, partially due to lack of therapeutic options. To identify effective therapeutic targets, we sought to identify molecular pathways that drive metastasis and HNC progression, through large-scale systematic analyses of transcriptomic data.

METHODS

We performed meta-analysis across 29 gene expression studies including 2074 primary HNC biopsies to identify genes and transcriptional pathways associated with survival and lymph node metastasis (LNM). To understand the biological roles of these genes in HNC, we identified their associated cancer pathways, as well as the cell types that express them within HNC tumor microenvironments, by integrating single-cell RNA-seq and bulk RNA-seq from sorted cell populations.

RESULTS

Patient survival-associated genes were heterogenous and included drivers of diverse tumor biological processes: these included tumor-intrinsic processes such as epithelial dedifferentiation and epithelial to mesenchymal transition, as well as tumor microenvironmental factors such as T cell-mediated immunity and cancer-associated fibroblast activity. Unexpectedly, LNM-associated genes were almost universally associated with epithelial dedifferentiation within malignant cells. Genes negatively associated with LNM consisted of regulators of squamous epithelial differentiation that are expressed within well-differentiated malignant cells, while those positively associated with LNM represented cell cycle regulators that are normally repressed by the p53-DREAM pathway. These pro-LNM genes are overexpressed in proliferating malignant cells of TP53 mutated and HPV + ve HNCs and are strongly associated with stemness, suggesting that they represent markers of pre-metastatic cancer stem-like cells. LNM-associated genes are deregulated in high-grade oral precancerous lesions, and deregulated further in primary HNCs with advancing tumor grade and deregulated further still in lymph node metastases.

CONCLUSIONS

In HNC, patient survival is affected by multiple biological processes and is strongly influenced by the tumor immune and stromal microenvironments. In contrast, LNM appears to be driven primarily by malignant cell plasticity, characterized by epithelial dedifferentiation coupled with EMT-independent proliferation and stemness. Our findings postulate that LNM is initially caused by loss of p53-DREAM-mediated repression of cell cycle genes during early tumorigenesis.

The p53/ZEB1-PLD3 feedback loop regulates cell proliferation in breast cancer

Breast cancer is the most prevalent cancer globally, endangering women's physical and mental health. Phospholipase D3 (PLD3) belongs to the phosphodiesterase family (PLD). PLD3 is related to insulin-mediated phosphorylation of the AKT pathway, suggesting that it may play a role in the occurrence and development of malignant tumors. This study may further explore the molecular mechanism of PLD3 inhibiting breast cancer cell proliferation. In this study, we demonstrated that PLD3 and miR-6796 are co-expressed in breast cancer. PLD3 can bind with CDK1 and inhibit its expression, leading to mitotic arrest and inhibiting breast cancer proliferation. Wild-type p53 regulates PLD3 and miR-6796 expression by competitively binding to the PLD3 promoter with ZEB1. DNMT3B, as the target gene of miR-6796, is recruited into the PLD3 promoter by combining with ZEB1 to regulate the DNA methylation of the PLD3 promoter and ultimately affect PLD3 and miR-6796 expression. In conclusion, we revealed the role and molecular mechanism of PLD3 and its embedded miR-6796 in breast cancer proliferation, providing clues and a theoretical foundation for future research and development of therapeutic targets and prognostic markers for breast cancer.

All-in-One Engineering Multifunctional Nanoplatforms for Sensitizing Tumor Low-Temperature Photothermal Therapy In Vivo

Low-temperature photothermal therapy (PTT) is a noninvasive method that harnesses the photothermal effect at low temperatures to selectively eliminate tumor cells, while safeguarding normal tissues, minimizing thermal damage, and enhancing treatment safety. First we evaluated the transcriptome of tumor cells at the gene level following low-temperature treatment and observed significant enrichment of genes involved in cell cycle and heat response-related signaling pathways. To address this challenge, we have developed an engineering multifunctional nanoplatform that offered an all-in-one strategy for efficient sensitization of low-temperature PTT. Specifically, we utilized MoS2 nanoparticles as the photothermal core to generate low temperature (40-48 °C). The nanoplatform was coated with DPA to load CPT-11 and Fe2+ and was further modified with PEG and iRGD to enhance tumor specificity (MoS2/Fe@CPT-11-PEG-iRGD). Laser- and acid-triggered release of CPT-11 can significantly increase intracellular H2O2 content, cooperate with Fe2+ ions to increase intracellular lipid ROS content, and activate ferroptosis. Furthermore, CPT-11 induced cell cycle arrest in the temperature-sensitive S-phase, and increased lipid ROS levels contributed to the degradation of HSPs protein expression. This synergistic approach could effectively induce tumor cell death by the sensitized low-temperature PTT and the combination of ferroptosis and chemotherapy. Our nanoplatform can also maximize tumor cell eradication and prolong the survival time of tumor-bearing mice in vivo. The multifunctional approach will provide more possibilities for clinical applications of low-temperature PTT and potential avenues for the development of multiple tumor treatments.

Single-Cell RNA Analysis Reveals Cell-Intrinsic Functions of CAR T Cells Correlating with Response in a Phase II Study of Lymphoma Patients

PURPOSE

Although CD19 chimeric antigen receptor T cells (CAR-T) therapy has shown remarkable success in B-cell malignancies, a substantial fraction of patients do not obtain a long-term clinical response. This could be influenced by the quality of the individual CAR-T infusion product. To shed some light on this, clinical outcome was correlated to characteristics of CAR-T infusion products.

PATIENTS AND METHODS

In this phase II study, patients with B-cell lymphoma (n = 23) or leukemia (n = 1) received one or two infusions of third-generation CD19-directed CAR-Ts (2 × 108/m2). The clinical trial was registered at clinicaltrials.gov: NCT03068416. We investigated the transcriptional profile of individual CD19 CAR-T infusion products using targeted single-cell RNA sequencing and multicolor flow cytometry.

RESULTS

Two CAR-T infusions were not better than one in the settings used in this study. As for the CAR-T infusion products, we found that effector-like CD8+CAR-Ts with a high polyfunctionality, high cytotoxic and cytokine production profile, and low dysfunctional signature were associated with clinical response. An extended ex vivo expansion time during CAR-T manufacturing negatively influenced the proportion of effector CD8+CAR-Ts in the infusion product.

CONCLUSIONS

We identified cell-intrinsic characteristics of effector CD8+CAR-Ts correlating with response that could be used as an indicator for clinical outcome. The results in the study also serve as a guide to CAR-T manufacturing practices.

An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers

An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecular identity of aggressive cancer cells. We used epithelial primary cells and developed a breast cancer stem cell–based progressive model. The superiority of the early-transformed isolated molecular index was evaluated by large-scale analysis in solid cancers. BMP2-driven cell transformation increases CD10 expression which preserves stemness properties. Our model identified a unique set of 159 genes enriched in G2–M cell-cycle phases and spindle assembly complex. Using samples predisposed to transformation, we confirmed the value of an early neoplasia index associated to CD10 (ENI10) to discriminate premalignant status of a human tissue. Using a stratified Cox model, a large-scale analysis (>10,000 samples, The Cancer Genome Atlas Pan-Cancer) validated a strong risk gradient (HRs reaching HR = 5.15; 95% confidence interval: 4.00–6.64) for high ENI10 levels. Through different databases, Cox regression model analyses highlighted an association between ENI10 and poor progression-free intervals for more than 50% of cancer subtypes tested, and the potential of ENI10 to predict drug efficacy. The ENI10 index constitutes a robust tool to detect pretransformed tissues and identify high-risk patients at diagnosis. Owing to its biological link with refractory cancer stem cells, the ENI10 index constitutes a unique way of identifying effective treatments to improve clinical care.

SIGNIFICANCE

We identified a molecular signature called ENI10 which, owing to its biological link with stem cell properties, predicts patient outcome and drugs efficiency in breast and several other cancers. ENI10 should allow early and optimized clinical management of a broad number of cancers, regardless of the stage of tumor progression.

Distinct pulmonary and systemic effects of dexamethasone in severe COVID-19

Dexamethasone is the standard of care for critically ill patients with COVID-19, but the mechanisms by which it decreases mortality and its immunological effects in this setting are not understood. We performed bulk and single-cell RNA sequencing of the lower respiratory tract and blood, and plasma cytokine profiling to study the effect of dexamethasone on systemic and pulmonary immune cells. We find decreased signatures of antigen presentation, T cell recruitment, and viral injury in patients treated with dexamethasone. We identify compartment- and cell- specific differences in the effect of dexamethasone in patients with severe COVID-19 that are reproducible in publicly available datasets. Our results highlight the importance of studying compartmentalized inflammation in critically ill patients.

Faulty Metabolism: A Potential Instigator of an Aggressive Phenotype in Cdk5-dependent Medullary Thyroid Carcinoma

Mechanistic modeling of cancers such as Medullary Thyroid Carcinoma (MTC) to emulate patient-specific phenotypes is challenging. The discovery of potential diagnostic markers and druggable targets in MTC urgently requires clinically relevant animal models. Here we established orthotopic mouse models of MTC driven by aberrantly active Cdk5 using cell-specific promoters. Each of the two models elicits distinct growth differences that recapitulate the less or more aggressive forms of human tumors. The comparative mutational and transcriptomic landscape of tumors revealed significant alterations in mitotic cell cycle processes coupled with the slow-growing tumor phenotype. Conversely, perturbation in metabolic pathways emerged as critical for aggressive tumor growth. Moreover, an overlapping mutational profile was identified between mouse and human tumors. Gene prioritization revealed putative downstream effectors of Cdk5 which may contribute to the slow and aggressive growth in the mouse MTC models. In addition, Cdk5/p25 phosphorylation sites identified as biomarkers for Cdk5-driven neuroendocrine tumors (NETs) were detected in both slow and rapid onset models and were also histologically present in human MTC. Thus, this study directly relates mouse and human MTC models and uncovers vulnerable pathways potentially responsible for differential tumor growth rates. Functional validation of our findings may lead to better prediction of patient-specific personalized combinational therapies.

Transcriptome analysis of the binucleate ciliate Tetrahymena thermophila with asynchronous nuclear cell cycles

Tetrahymena thermophila harbors two functionally and physically distinct nuclei within a shared cytoplasm. During vegetative growth, the "cell cycles" of the diploid micronucleus and polyploid macronucleus are offset. Micronuclear S phase initiates just before cytokinesis and is completed in daughter cells before onset of macronuclear DNA replication. Mitotic micronuclear division occurs mid-cell cycle, while macronuclear amitosis is coupled to cell division. Here we report the first RNA-seq cell cycle analysis of a binucleated ciliated protozoan. RNA was isolated across 1.5 vegetative cell cycles, starting with a macronuclear G1 population synchronized by centrifugal elutriation. Using MetaCycle, 3244 of the 26,000+ predicted genes were shown to be cell cycle regulated. Proteins present in both nuclei exhibit a single mRNA peak that always precedes their macronuclear function. Nucleus-limited genes, including nucleoporins and importins, are expressed before their respective nucleus-specific role. Cyclin D and A/B gene family members exhibit different expression patterns that suggest nucleus-restricted roles. Periodically expressed genes cluster into seven cyclic patterns. Four clusters have known PANTHER gene ontology terms associated with G1/S and G2/M phase. We propose that these clusters encode known and novel factors that coordinate micro- and macronuclear-specific events such as mitosis, amitosis, DNA replication, and cell division.

HMMR potential as a diagnostic and prognostic biomarker of cancer-speculation based on a pan-cancer analysis

Background

Although the status of universal upregulation for the Hyaluronan-Mediated Motility Receptor (HMMR) in pan-cancer is still unknown, HMMR is upregulated and associated with poor prognosis for some tumors.

Methods

Exploring HMMR expression in different tumor types using The Cancer Genome Atlas (TCGA) or other public databases for a pan-cancer analysis, exploring the relationship between HMMR and tumor prognosis, and exploring the role of HMMR in tumor immunity.

Results

No matter the pairing or unpairing of data, HMMR expression generally increased compared to corresponding normal tissue. Based on a CCLE study, our results indicated that HMMR is widely expressed in various tumor cells. For most tumor types, high HMMR expression was associated with reduced Overall Survival (OS), Return to Functional Status (RFS), and Platinum Free Interval (PFI). ROC curves indicated that HMMR displays high prediction potential for most tumor types. In pan-cancer, HMMR is correlated with some clinical staging, immune cells, and immune checkpoints for some tumors. The GO/KEGG enrichment analysis results for proteins most closely related to HMMR indicate that the most highly enriched pathways are all related to tumor development.

Conclusions

Our pan-cancer analysis of HMMR suggests that HMMR can be used as a potential diagnostic and prognostic indicator of pan-cancer and that HMMR may be involved in tumor development.

LARP6 Regulates Keloid Fibroblast Proliferation, Invasion, and Ability to Synthesize Collagen

Keloid is a skin fibroproliferative disease currently having no uniformly successful treatment. The lesion is composed of actively proliferating and collagen-overproducing fibroblasts. LARP6 is an RNA-binding protein able to regulate collagen synthesis in fibroblasts and to promote proliferation and invasion of tumor cells. To explore LARP6's likely functions in keloid pathogenesis, we performed immunohistochemistry staining on human keloid tissues and discovered markedly upregulated LARP6 expression in lesion fibroblasts compared with that of normal skin and hypertrophic scar tissues. In addition, the keloid tissue‒derived fibroblasts showed constitutive upregulation of LARP6 expression as well as significantly upregulated mRNA and protein expressions of type I collagen and enhanced cell proliferation and invasive behavior in cell culture system. Intriguingly, LARP6 knockdown by targeting with small interfering RNAs significantly inhibited type I collagen expression, proliferation, and invasion capability of keloid tissue‒derived fibroblasts relative to that of normal skin‒ and hypertrophic scar‒derived fibroblasts and control keloid tissue‒derived fibroblasts that were transfected with a scrambled small interfering RNA. In conclusion, the abnormally upregulated expression of LARP6 in fibroblasts may play an important role in the growth and invasive behavior of keloid lesions.

ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes

MOTIVATION

Single-cell RNA sequencing (scRNA-seq) analysis reveals heterogeneity and dynamic cell transitions. However, conventional gene-based analyses require intensive manual curation to interpret biological implications of computational results. Hence, a theory for efficiently annotating individual cells remains warranted.

RESULTS

We present ASURAT, a computational tool for simultaneously performing unsupervised clustering and functional annotation of disease, cell type, biological process and signaling pathway activity for single-cell transcriptomic data, using a correlation graph decomposition for genes in database-derived functional terms. We validated the usability and clustering performance of ASURAT using scRNA-seq datasets for human peripheral blood mononuclear cells, which required fewer manual curations than existing methods. Moreover, we applied ASURAT to scRNA-seq and spatial transcriptome datasets for human small cell lung cancer and pancreatic ductal adenocarcinoma, respectively, identifying previously overlooked subpopulations and differentially expressed genes. ASURAT is a powerful tool for dissecting cell subpopulations and improving biological interpretability of complex and noisy transcriptomic data.

AVAILABILITY AND IMPLEMENTATION

ASURAT is published on Bioconductor (https://doi.org/10.18129/B9.bioc.ASURAT). The codes for analyzing data in this article are available at Github (https://github.com/keita-iida/ASURATBI) and figshare (https://doi.org/10.6084/m9.figshare.19200254.v4).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Quantitative profiling of adaptation to cyclin E overproduction

Cyclin E/CDK2 drives cell cycle progression from G1 to S phase. Despite the toxicity of cyclin E overproduction in mammalian cells, the cyclin E gene is overexpressed in some cancers. To further understand how cells can tolerate high cyclin E, we characterized non-transformed epithelial cells subjected to chronic cyclin E overproduction. Cells overproducing cyclin E, but not cyclins D or A, briefly experienced truncated G1 phases followed by a transient period of DNA replication origin underlicensing, replication stress, and impaired proliferation. Individual cells displayed substantial intercellular heterogeneity in cell cycle dynamics and CDK activity. Each phenotype improved rapidly despite high cyclin E-associated activity. Transcriptome analysis revealed adapted cells down-regulated a cohort of G1-regulated genes. Withdrawing cyclin E from adapted cells only partially reversed underlicensing indicating that adaptation is at least partly non-genetic. This study provides evidence that mammalian cyclin E/CDK inhibits origin licensing indirectly through premature S phase onset and provides mechanistic insight into the relationship between CDKs and licensing. It serves as an example of oncogene adaptation that may recapitulate molecular changes during tumorigenesis.

Holistic Characterization of Tumor Monocyte-to-Macrophage Differentiation Integrates Distinct Immune Phenotypes in Kidney Cancer

The tumor immune microenvironment (TIME) is commonly infiltrated by diverse collections of myeloid cells. Yet, the complexity of myeloid-cell identity and plasticity has challenged efforts to define bona fide populations and determine their connections to T-cell function and their relationship to patient outcome. Here, we have leveraged single-cell RNA-sequencing analysis of several mouse and human tumors and found that monocyte-macrophage diversity is characterized by a combination of conserved lineage states as well as transcriptional programs accessed along the differentiation trajectory. We also found in mouse models that tumor monocyte-to-macrophage progression was profoundly tied to regulatory T cell (Treg) abundance. In human kidney cancer, heterogeneity in macrophage accumulation and myeloid composition corresponded to variance in, not only Treg density, but also the quality of infiltrating CD8+ T cells. In this way, holistic analysis of monocyte-to-macrophage differentiation creates a framework for critically different immune states.

Single-cell transcriptomics identifies potential cells of origin of MYC rhabdoid tumors

Rhabdoid tumors (RT) are rare and highly aggressive pediatric neoplasms. Their epigenetically-driven intertumoral heterogeneity is well described; however, the cellular origin of RT remains an enigma. Here, we establish and characterize different genetically engineered mouse models driven under the control of distinct promoters and being active in early progenitor cell types with diverse embryonic onsets. From all models only Sox2-positive progenitor cells give rise to murine RT. Using single-cell analyses, we identify distinct cells of origin for the SHH and MYC subgroups of RT, rooting in early stages of embryogenesis. Intra- and extracranial MYC tumors harbor common genetic programs and potentially originate from fetal primordial germ cells (PGCs). Using PGC specific Smarcb1 knockout mouse models we validate that MYC RT originate from these progenitor cells. We uncover an epigenetic imbalance in MYC tumors compared to PGCs being sustained by epigenetically-driven subpopulations. Importantly, treatments with the DNA demethylating agent decitabine successfully impair tumor growth in vitro and in vivo. In summary, our work sheds light on the origin of RT and supports the clinical relevance of DNA methyltransferase inhibitors against this disease.

Rhabdoid tumors (RT) are aggressive paediatric cancers with yet unknown cells of origin. Here, the authors establish genetically engineered mouse models of RT and, using single-cell RNA-seq and epigenomics, identify potential cells of origin for the SHH and MYC subtypes.

Modeling Progression of Single Cell Populations Through the Cell Cycle as a Sequence of Switches

Cell cycle is a biological process underlying the existence and propagation of life in time and space. It has been an object for mathematical modeling for long, with several alternative mechanistic modeling principles suggested, describing in more or less details the known molecular mechanisms. Recently, cell cycle has been investigated at single cell level in snapshots of unsynchronized cell populations, exploiting the new methods for transcriptomic and proteomic molecular profiling. This raises a need for simplified semi-phenomenological cell cycle models, in order to formalize the processes underlying the cell cycle, at a higher abstracted level. Here we suggest a modeling framework, recapitulating the most important properties of the cell cycle as a limit trajectory of a dynamical process characterized by several internal states with switches between them. In the simplest form, this leads to a limit cycle trajectory, composed by linear segments in logarithmic coordinates describing some extensive (depending on system size) cell properties. We prove a theorem connecting the effective embedding dimensionality of the cell cycle trajectory with the number of its linear segments. We also develop a simplified kinetic model with piecewise-constant kinetic rates describing the dynamics of lumps of genes involved in S-phase and G2/M phases. We show how the developed cell cycle models can be applied to analyze the available single cell datasets and simulate certain properties of the observed cell cycle trajectories. Based on our model, we can predict with good accuracy the cell line doubling time from the length of cell cycle trajectory.

Localized Proteasomal Degradation: From the Nucleus to Cell Periphery

The proteasome is responsible for selective degradation of most cellular proteins. Abundantly present in the cell, proteasomes not only diffuse in the cytoplasm and the nucleus but also associate with the chromatin, cytoskeleton, various membranes and membraneless organelles/condensates. How and why the proteasome gets to these specific subcellular compartments remains poorly understood, although increasing evidence supports the hypothesis that intracellular localization may have profound impacts on the activity, substrate accessibility and stability/integrity of the proteasome. In this short review, I summarize recent advances on the functions, regulations and targeting mechanisms of proteasomes, especially those localized to the nuclear condensates and membrane structures of the cell, and I discuss the biological significance thereof in mediating compartmentalized protein degradation.

Prediction of Time Series Gene Expression and Structural Analysis of Gene Regulatory Networks Using Recurrent Neural Networks

Methods for time series prediction and classification of gene regulatory networks (GRNs) from gene expression data have been treated separately so far. The recent emergence of attention-based recurrent neural network (RNN) models boosted the interpretability of RNN parameters, making them appealing for the understanding of gene interactions. In this work, we generated synthetic time series gene expression data from a range of archetypal GRNs and we relied on a dual attention RNN to predict the gene temporal dynamics. We show that the prediction is extremely accurate for GRNs with different architectures. Next, we focused on the attention mechanism of the RNN and, using tools from graph theory, we found that its graph properties allow one to hierarchically distinguish different architectures of the GRN. We show that the GRN responded differently to the addition of noise in the prediction by the RNN and we related the noise response to the analysis of the attention mechanism. In conclusion, this work provides a way to understand and exploit the attention mechanism of RNNs and it paves the way to RNN-based methods for time series prediction and inference of GRNs from gene expression data.

Discovering dominant tumor immune archetypes in a pan-cancer census

Cancers display significant heterogeneity with respect to tissue of origin, driver mutations, and other features of the surrounding tissue. It is likely that individual tumors engage common patterns of the immune system-here "archetypes"-creating prototypical non-destructive tumor immune microenvironments (TMEs) and modulating tumor-targeting. To discover the dominant immune system archetypes, the University of California, San Francisco (UCSF) Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub-compartments uncovered dominant patterns of immune composition across cancers. These archetypes were profound insofar as they also differentiated tumors based upon unique immune and tumor gene-expression patterns. They also partitioned well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune organization and provides a rational path forward to learn how to modulate these to improve therapy.

AKIRIN2 controls the nuclear import of proteasomes in vertebrates

Protein expression and turnover are controlled through a complex interplay of transcriptional, post-transcriptional and post-translational mechanisms to enable spatial and temporal regulation of cellular processes. To systematically elucidate such gene regulatory networks, we developed a CRISPR screening assay based on time-controlled Cas9 mutagenesis, intracellular immunostaining and fluorescence-activated cell sorting that enables the identification of regulatory factors independent of their effects on cellular fitness. We pioneered this approach by systematically probing the regulation of the transcription factor MYC, a master regulator of cell growth^1-3. Our screens uncover a highly conserved protein, AKIRIN2, that is essentially required for nuclear protein degradation. We found that AKIRIN2 forms homodimers that directly bind to fully assembled 20S proteasomes to mediate their nuclear import. During mitosis, proteasomes are excluded from condensing chromatin and re-imported into newly formed daughter nuclei in a highly dynamic, AKIRIN2-dependent process. Cells undergoing mitosis in the absence of AKIRIN2 become devoid of nuclear proteasomes, rapidly causing accumulation of MYC and other nuclear proteins. Collectively, our study reveals a dedicated pathway controlling the nuclear import of proteasomes in vertebrates and establishes a scalable approach to decipher regulators in essential cellular processes.

Joint changes in RNA, RNA polymerase II, and promoter activity through the cell cycle identify non-coding RNAs involved in proliferation

Proper regulation of the cell cycle is necessary for normal growth and development of all organisms. Conversely, altered cell cycle regulation often underlies proliferative diseases such as cancer. Long non-coding RNAs (lncRNAs) are recognized as important regulators of gene expression and are often found dysregulated in diseases, including cancers. However, identifying lncRNAs with cell cycle functions is challenging due to their often low and cell-type specific expression. We present a highly effective method that analyses changes in promoter activity, transcription, and RNA levels for identifying genes enriched for cell cycle functions. Specifically, by combining RNA sequencing with ChIP sequencing through the cell cycle of synchronized human keratinocytes, we identified 1009 genes with cell cycle-dependent expression and correlated changes in RNA polymerase II occupancy or promoter activity as measured by histone 3 lysine 4 trimethylation (H3K4me3). These genes were highly enriched for genes with known cell cycle functions and included 57 lncRNAs. We selected four of these lncRNAs-SNHG26, EMSLR, ZFAS1, and EPB41L4A-AS1-for further experimental validation and found that knockdown of each of the four lncRNAs affected cell cycle phase distributions and reduced proliferation in multiple cell lines. These results show that many genes with cell cycle functions have concomitant cell-cycle dependent changes in promoter activity, transcription, and RNA levels and support that our multi-omics method is well suited for identifying lncRNAs involved in the cell cycle.

Spatial transcriptional mapping of the human nephrogenic program

Congenital abnormalities of the kidney and urinary tract are among the most common birth defects, affecting 3% of newborns. The human kidney forms around a million nephrons from a pool of nephron progenitors over a 30-week period of development. To establish a framework for human nephrogenesis, we spatially resolved a stereotypical process by which equipotent nephron progenitors generate a nephron anlage, then applied data-driven approaches to construct three-dimensional protein maps on anatomical models of the nephrogenic program. Single-cell RNA sequencing identified progenitor states, which were spatially mapped to the nephron anatomy, enabling the generation of functional gene networks predicting interactions within and between nephron cell types. Network mining identified known developmental disease genes and predicted targets of interest. The spatially resolved nephrogenic program made available through the Human Nephrogenesis Atlas (https://sckidney.flatironinstitute.org/) will facilitate an understanding of kidney development and disease and enhance efforts to generate new kidney structures.

The unique biology of germinal center B cells

Germinal center (GC) B cells are the source of the high-affinity, class-switched antibodies required for protective immunity. The unique biology of GC B cells involves iterative rounds of antibody gene somatic hypermutation coupled to multiple selection and differentiation pathways. Recent advances in areas such as single cell and gene editing technologies have shed new light upon these complex and dynamic processes. We review these findings here and integrate them into the current understanding of GC B cell replication and death, the retention of high-affinity and class-switched B cells in the GC, and differentiation into plasma and memory cell effectors. We also discuss how the biology of GC responses relates to vaccine effectiveness and outline current and future challenges in the field.

Selective therapeutic strategy for p53-deficient cancer by targeting dysregulation in DNA repair

Breast carcinomas commonly carry mutations in the tumor suppressor p53, although therapeutic efforts to target mutant p53 have previously been unfruitful. Here we report a selective combination therapy strategy for treatment of p53 mutant cancers. Genomic data revealed that p53 mutant cancers exhibit high replication activity and express high levels of the Base-Excision Repair (BER) pathway, whereas experimental testing showed substantial dysregulation in BER. This defect rendered accumulation of DNA damage in p53 mutant cells upon treatment with deoxyuridine analogues. Notably, inhibition of poly (ADP-ribose) polymerase (PARP) greatly enhanced this response, whereas normal cells responded with activation of the p53-p21 axis and cell cycle arrest. Inactivation of either p53 or p21/CDKN1A conferred the p53 mutant phenotype. Preclinical animal studies demonstrated a greater anti-neoplastic efficacy of the drug combination (deoxyuridine analogue and PARP inhibitor) than either drug alone. This work illustrates a selective combination therapy strategy for p53 mutant cancers that will improve survival rates and outcomes for thousands of breast cancer patients.

SC1: A Tool for Interactive Web-Based Single-Cell RNA-Seq Data Analysis

Single-cell RNA-Seq (scRNA-Seq) is critical for studying cellular function and phenotypic heterogeneity as well as the development of tissues and tumors. In this study, we present SC1 a web-based highly interactive scRNA-Seq data analysis tool publicly accessible at https://sc1.engr.uconn.edu. The tool presents an integrated workflow for scRNA-Seq analysis, implements a novel method of selecting informative genes based on term-frequency inverse-document-frequency scores, and provides a broad range of methods for clustering, differential expression analysis, gene enrichment, interactive visualization, and cell cycle analysis. The tool integrates other single-cell omics data modalities such as T-cell receptor (TCR)-Seq and supports several single-cell sequencing technologies. In just a few steps, researchers can generate a comprehensive analysis and gain powerful insights from their scRNA-Seq data.

G2S3: A gene graph-based imputation method for single-cell RNA sequencing data

Single-cell RNA sequencing technology provides an opportunity to study gene expression at single-cell resolution. However, prevalent dropout events result in high data sparsity and noise that may obscure downstream analyses in single-cell transcriptomic studies. We propose a new method, G2S3, that imputes dropouts by borrowing information from adjacent genes in a sparse gene graph learned from gene expression profiles across cells. We applied G2S3 and ten existing imputation methods to eight single-cell transcriptomic datasets and compared their performance. Our results demonstrated that G2S3 has superior overall performance in recovering gene expression, identifying cell subtypes, reconstructing cell trajectories, identifying differentially expressed genes, and recovering gene regulatory and correlation relationships. Moreover, G2S3 is computationally efficient for imputation in large-scale single-cell transcriptomic datasets.

Long Noncoding RNAs at the Crossroads of Cell Cycle and Genome Integrity

The cell cycle is controlled by guardian proteins that coordinate the process of cell growth and cell division. Alterations in these processes lead to genome instability, which has a causal link to many human diseases. Beyond their well-characterized role of influencing protein-coding genes, an increasing body of evidence has revealed that long noncoding RNAs (lncRNAs) actively participate in regulation of the cell cycle and safeguarding of genome integrity. LncRNAs are versatile molecules that act via a wide array of mechanisms. In this review, we discuss how lncRNAs are implicated in control of the cell cycle and maintenance of genome stability and how changes in lncRNA-regulatory networks lead to proliferative diseases such as cancer.

Temporal Dynamic Methods for Bulk RNA-Seq Time Series Data

Dynamic studies in time course experimental designs and clinical approaches have been widely used by the biomedical community. These applications are particularly relevant in stimuli-response models under environmental conditions, characterization of gradient biological processes in developmental biology, identification of therapeutic effects in clinical trials, disease progressive models, cell-cycle, and circadian periodicity. Despite their feasibility and popularity, sophisticated dynamic methods that are well validated in large-scale comparative studies, in terms of statistical and computational rigor, are less benchmarked, comparing to their static counterparts. To date, a number of novel methods in bulk RNA-Seq data have been developed for the various time-dependent stimuli, circadian rhythms, cell-lineage in differentiation, and disease progression. Here, we comprehensively review a key set of representative dynamic strategies and discuss current issues associated with the detection of dynamically changing genes. We also provide recommendations for future directions for studying non-periodical, periodical time course data, and meta-dynamic datasets.

Spatiotemporal dissection of the cell cycle with single-cell proteogenomics

The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer^1-3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.

Dual RNA 3'-end processing of H2A.X messenger RNA maintains DNA damage repair throughout the cell cycle

Phosphorylated H2A.X is a critical chromatin marker of DNA damage repair (DDR) in higher eukaryotes. However, H2A.X gene expression remains relatively uncharacterised. Replication-dependent (RD) histone genes generate poly(A)- mRNA encoding new histones to package DNA during replication. In contrast, replication-independent (RI) histone genes synthesise poly(A)+ mRNA throughout the cell cycle, translated into histone variants that confer specific epigenetic patterns on chromatin. Remarkably H2AFX, encoding H2A.X, is a hybrid histone gene, generating both poly(A)+ and poly(A)- mRNA isoforms. Here we report that the selective removal of either mRNA isoform reveals different effects in different cell types. In some cells, RD H2A.X poly(A)- mRNA generates sufficient histone for deposition onto DDR associated chromatin. In contrast, cells making predominantly poly(A)+ mRNA require this isoform for de novo H2A.X synthesis, required for efficient DDR. This highlights the importance of differential H2A.X mRNA 3’-end processing in the maintenance of effective DDR.

H2A.X histone variant gene encodes poly(A)+ and poly(A)- mRNA isoforms which are differentially expressed depending on cell lines. Here the authors show that upon DNA damage, cells expressing more poly(A)+ isoform require this isoform for de novo H2A.X synthesis while cells with more poly(A)- isoform have sufficient H2A.X present in chromatin.

The transcriptome dynamics of single cells during the cell cycle

The cell cycle is among the most basic phenomena in biology. Despite advances in single-cell analysis, dynamics and topology of the cell cycle in high-dimensional gene expression space remain largely unknown. We developed a linear analysis of transcriptome data which reveals that cells move along a planar circular trajectory in transcriptome space during the cycle. Non-cycling gene expression adds a third dimension causing helical motion on a cylinder. We find in immortalized cell lines that cell cycle transcriptome dynamics occur largely independently from other cellular processes. We offer a simple method ("Revelio") to order unsynchronized cells in time. Precise removal of cell cycle effects from the data becomes a straightforward operation. The shape of the trajectory implies that each gene is upregulated only once during the cycle, and only two dynamic components represented by groups of genes drive transcriptome dynamics. It indicates that the cell cycle has evolved to minimize changes of transcriptional activity and the related regulatory effort. This design principle of the cell cycle may be of relevance to many other cellular differentiation processes.

Global Absence and Targeting of Protective Immune States in Severe COVID-19

While SARS-CoV-2 infection has pleiotropic and systemic effects in some patients, many others experience milder symptoms. We sought a holistic understanding of the severe/mild distinction in COVID-19 pathology, and its origins. We performed a whole-blood preserving single-cell analysis protocol to integrate contributions from all major cell types including neutrophils, monocytes, platelets, lymphocytes and the contents of serum. Patients with mild COVID-19 disease display a coordinated pattern of interferon-stimulated gene (ISG) expression across every cell population and these cells are systemically absent in patients with severe disease. Severe COVID-19 patients also paradoxically produce very high anti-SARS-CoV-2 antibody titers and have lower viral load as compared to mild disease. Examination of the serum from severe patients demonstrates that they uniquely produce antibodies with multiple patterns of specificity against interferon-stimulated cells and that those antibodies functionally block the production of the mild disease-associated ISG-expressing cells. Overzealous and auto-directed antibody responses pit the immune system against itself in many COVID-19 patients and this defines targets for immunotherapies to allow immune systems to provide viral defense.

One Sentence Summary

In severe COVID-19 patients, the immune system fails to generate cells that define mild disease; antibodies in their serum actively prevents the successful production of those cells.

Splicing to Keep Cycling: The Importance of Pre-mRNA Splicing during the Cell Cycle

Pre-mRNA splicing is a fundamental process in mammalian gene expression, and alternative splicing plays an extensive role in generating protein diversity. Because the majority of genes undergo pre-mRNA splicing, most cellular processes depend on proper spliceosome function. We focus on the cell cycle and describe its dependence on pre-mRNA splicing and accurate alternative splicing. We outline the key cell-cycle factors and their known alternative splicing isoforms. We discuss different levels of pre-mRNA splicing regulation such as post-translational modifications and changes in the expression of splicing factors. We describe the effect of chromatin dynamics on pre-mRNA splicing during the cell cycle. In addition, we focus on spliceosome component SF3B1, which is mutated in many types of cancer, and describe the link between SF3B1 and its inhibitors and the cell cycle.

The Contribution of lincRNAs at the Interface between Cell Cycle Regulation and Cell State Maintenance

Cell cycle progression is controlled by the interplay of established cell cycle regulators. Changes in these regulators' activity underpin differences in cell cycle kinetics between cell types. We investigated whether long intergenic noncoding RNAs (lincRNAs) contribute to embryonic stem cell cycle adaptations. Using single-cell RNA sequencing data for mouse embryonic stem cells (mESCs) staged as G1, S, or G2/M we found differentially expressed lincRNAs are enriched among cell cycle-regulated genes. These lincRNAs (CC-lincRNAs) are co-expressed with genes involved in cell cycle regulation. We tested the impact of two CC-lincRNA candidates and show using CRISPR activation that increasing their expression is associated with deregulated cell cycle progression. Interestingly, CC-lincRNAs are often differentially expressed between G1 and S, their promoters are enriched in pluripotency transcription factor (TF) binding sites, and their transcripts are frequently co-regulated with genes involved in the maintenance of pluripotency, suggesting a contribution of CC-lincRNAs to mESC cell cycle adaptations.

•

Genes differentially expressed between mESC cell cycle stages are enriched in lincRNAs

•

CC-lincRNAs are co-expressed with cell cycle and pluripotency genes

•

CC-lincRNAs are often mESC specific and their promoters enriched in pluripotency TFs

•

Upregulation of two CC-lincRNAs results in deregulated mESC cell cycle progression

Cell cycle transcriptomics of Capsaspora provides insights into the evolution of cyclin-CDK machinery

Progression through the cell cycle in eukaryotes is regulated on multiple levels. The main driver of the cell cycle progression is the periodic activity of cyclin-dependent kinase (CDK) complexes. In parallel, transcription during the cell cycle is regulated by a transcriptional program that ensures the just-in-time gene expression. Many core cell cycle regulators are widely conserved in eukaryotes, among them cyclins and CDKs; however, periodic transcriptional programs are divergent between distantly related species. In addition, many otherwise conserved cell cycle regulators have been lost and independently evolved in yeast, a widely used model organism for cell cycle research. For a better understanding of the evolution of the cell cycle regulation in opisthokonts, we investigated the transcriptional program during the cell cycle of the filasterean Capsaspora owczarzaki, a unicellular species closely related to animals. We developed a protocol for cell cycle synchronization in Capsaspora cultures and assessed gene expression over time across the entire cell cycle. We identified a set of 801 periodic genes that grouped into five clusters of expression over time. Comparison with datasets from other eukaryotes revealed that the periodic transcriptional program of Capsaspora is most similar to that of animal cells. We found that orthologues of cyclin A, B and E are expressed at the same cell cycle stages as in human cells and in the same temporal order. However, in contrast to human cells where these cyclins interact with multiple CDKs, Capsaspora cyclins likely interact with a single ancestral CDK1-3. Thus, the Capsaspora cyclin-CDK system could represent an intermediate state in the evolution of animal-like cyclin-CDK regulation. Overall, our results demonstrate that Capsaspora could be a useful unicellular model system for animal cell cycle regulation.

netNMF-sc: leveraging gene-gene interactions for imputation and dimensionality reduction in single-cell expression analysis

Single-cell RNA-sequencing (scRNA-seq) enables high-throughput measurement of RNA expression in single cells. However, because of technical limitations, scRNA-seq data often contain zero counts for many transcripts in individual cells. These zero counts, or dropout events, complicate the analysis of scRNA-seq data using standard methods developed for bulk RNA-seq data. Current scRNA-seq analysis methods typically overcome dropout by combining information across cells in a lower-dimensional space, leveraging the observation that cells generally occupy a small number of RNA expression states. We introduce netNMF-sc, an algorithm for scRNA-seq analysis that leverages information across both cells and genes. netNMF-sc learns a low-dimensional representation of scRNA-seq transcript counts using network-regularized non-negative matrix factorization. The network regularization takes advantage of prior knowledge of gene–gene interactions, encouraging pairs of genes with known interactions to be nearby each other in the low-dimensional representation. The resulting matrix factorization imputes gene abundance for both zero and nonzero counts and can be used to cluster cells into meaningful subpopulations. We show that netNMF-sc outperforms existing methods at clustering cells and estimating gene–gene covariance using both simulated and real scRNA-seq data, with increasing advantages at higher dropout rates (e.g., >60%). We also show that the results from netNMF-sc are robust to variation in the input network, with more representative networks leading to greater performance gains.

Tales from topographic oceans: topologically associated domains and cancer

The 3D organization of the genome within the cell nucleus has come into sharp focus over the last decade. This has largely arisen because of the application of genomic approaches that have revealed numerous levels of genomic and chromatin interactions, including topologically associated domains (TADs). The current review examines how these domains were identified, are organized, how their boundaries arise and are regulated, and how genes within TADs are coordinately regulated. There are many examples of the disruption to TAD structure in cancer and the altered regulation, structure and function of TADs are discussed in the context of hormone responsive cancers, including breast, prostate and ovarian cancer. Finally, some aspects of the statistical insight and computational skills required to interrogate TAD organization are considered and future directions discussed.

Cooperative Effects of Cytosine Methylation on DNA Structure and Dynamics

The behavior of the structural parameters of DNA considering different levels of methylation in CpG islands is studied by means of full-atom molecular dynamics simulations and electronic circular dichroism, both in an artificial model system and in a gene promoter sequence. It is demonstrated that methylation although intrinsically brings quite local perturbations may, if its level is high enough, induce cooperative effects that strongly modify the DNA backbone torsional parameters altering the helicity as compared to the nonmethylated case. Because methylation of the CpG island is correlated with the regulation of gene expression, understanding the structural modifications induced in DNA is crucial to characterize all the fine equilibria into play in epigenetics phenomena.

Assembly of a parts list of the human mitotic cell cycle machinery

The set of proteins required for mitotic division remains poorly characterized. Here, an extensive series of correlation analyses of human and mouse transcriptomics data were performed to identify genes strongly and reproducibly associated with cells undergoing S/G2-M phases of the cell cycle. In so doing, 701 cell cycle-associated genes were defined and while it was shown that many are only expressed during these phases, the expression of others is also driven by alternative promoters. Of this list, 496 genes have known cell cycle functions, whereas 205 were assigned as putative cell cycle genes, 53 of which are functionally uncharacterized. Among these, 27 were screened for subcellular localization revealing many to be nuclear localized and at least three to be novel centrosomal proteins. Furthermore, 10 others inhibited cell proliferation upon siRNA knockdown. This study presents the first comprehensive list of human cell cycle proteins, identifying many new candidate proteins.

Set2 methyltransferase facilitates cell cycle progression by maintaining transcriptional fidelity

Methylation of histone H3 lysine 36 (H3K36me) by yeast Set2 is critical for the maintenance of chromatin structure and transcriptional fidelity. However, we do not know the full range of Set2/H3K36me functions or the scope of mechanisms that regulate Set2-dependent H3K36 methylation. Here, we show that the APC/C^CDC20 complex regulates Set2 protein abundance during the cell cycle. Significantly, absence of Set2-mediated H3K36me causes a loss of cell cycle control and pronounced defects in the transcriptional fidelity of cell cycle regulatory genes, a class of genes that are generally long, hence highly dependent on Set2/H3K36me for their transcriptional fidelity. Because APC/C also controls human SETD2, and SETD2 likewise regulates cell cycle progression, our data imply an evolutionarily conserved cell cycle function for Set2/SETD2 that may explain why recurrent mutations of SETD2 contribute to human disease.

SNHG5 Promotes Breast Cancer Proliferation by Sponging the miR-154-5p/PCNA Axis

Breast cancer is the most common malignant tumor and the main cause of cancer-associated mortality in females worldwide. Long non-coding RNAs (lncRNAs) have been reported to play vital roles in breast cancer development and progression; however, our understanding of most lncRNAs in breast cancer is still limited. In this study, we demonstrated that small nucleolar RNA host gene 5 (SNHG5) promotes breast cancer cell proliferation both in vitro and in vivo, and depletion of SNHG5 significantly led to cell-cycle arrest at G1 phase. Accumulating evidence has shown that many lncRNA transcripts could function as competing endogenous RNAs (ceRNAs) by competitively binding common microRNAs (miRNAs). We found that SNHG5 acts as a sponge for miR-154-5p, reducing its ability to repress proliferating cell nuclear antigen (PCNA). SNHG5 promoted breast cancer proliferation and cell-cycle progression by upregulation of PCNA expression. Clinically, we observed an increased SNHG5 expression in breast cancer, whereas miR-154-5p was decreased in breast cancer tissues compared with the adjacent normal breast tissues. Furthermore, the SNHG5 expression was significantly negatively correlated with miR-154-5p expression. Taken together, our data uncover the SNHG5-miR-154-5p-PCNA axis and provide a novel mechanism to explain breast cancer proliferation.