Genome-wide transcriptional analysis of the human cell cycle identifies genes differentially regulated in normal and cancer cells

FOXM1 requires IDH1 for late genes expression in mitotic cells

Isocitrate dehydrogenase 1 (IDH1) is a metabolic enzyme that converts isocitrate to α-ketoglutarate in cells. However, research on IDH1 is more focused on the metabolite D-2-hydroxyglutarate than the cellular roles of the IDH1 protein. Metabolic enzymes can moonlight by participating in diverse cellular processes in cancer cells. This moonlighting function of the metabolic enzymes can contribute to changes in gene expression. It is unknown whether IDH1 associates with any transcription factor. We asked whether IDH1 coordinates with forkhead box protein M1 (FOXM1) in mitotic cells to regulate late genes expression. We found that depletion of IDH1 reduces canonical FOXM1-target expression in mitotic cells. Also, IDH1 binds to FOXM1 and a subset of MuvB proteins, Lin-9 and Lin-54, in mitotic cells. Based on these observations, we suggest that IDH1 coordinates with FOXM1 in mitotic cells to regulate late genes expression.

Gastric cancer actionable genomic alterations across diverse populations worldwide and pharmacogenomics strategies based on precision oncology

Introduction: Gastric cancer is one of the most prevalent types of cancer worldwide. The World Health Organization (WHO), the International Agency for Research on Cancer (IARC), and the Global Cancer Statistics (GLOBOCAN) reported an age standardized global incidence rate of 9.2 per 100,000 individuals for gastric cancer in 2022, with a mortality rate of 6.1. Despite considerable progress in precision oncology through the efforts of international consortia, understanding the genomic features and their influence on the effectiveness of anti-cancer treatments across diverse ethnic groups remains essential. Methods: Our study aimed to address this need by conducting integrated in silico analyses to identify actionable genomic alterations in gastric cancer driver genes, assess their impact using deleteriousness scores, and determine allele frequencies across nine global populations: European Finnish, European non-Finnish, Latino, East Asian, South Asian, African, Middle Eastern, Ashkenazi Jewish, and Amish. Furthermore, our goal was to prioritize targeted therapeutic strategies based on pharmacogenomics clinical guidelines, in silico drug prescriptions, and clinical trial data. Results: Our comprehensive analysis examined 275,634 variants within 60 gastric cancer driver genes from 730,947 exome sequences and 76,215 whole-genome sequences from unrelated individuals, identifying 13,542 annotated and predicted oncogenic variants. We prioritized the most prevalent and deleterious oncogenic variants for subsequent pharmacogenomics testing. Additionally, we discovered actionable genomic alterations in the ARID1A, ATM, BCOR, ERBB2, ERBB3, CDKN2A, KIT, PIK3CA, PTEN, NTRK3, TP53, and CDKN2A genes that could enhance the efficacy of anti-cancer therapies, as suggested by in silico drug prescription analyses, reviews of current pharmacogenomics clinical guidelines, and evaluations of phase III and IV clinical trials targeting gastric cancer driver proteins. Discussion: These findings underline the urgency of consolidating efforts to devise effective prevention measures, invest in genomic profiling for underrepresented populations, and ensure the inclusion of ethnic minorities in future clinical trials and cancer research in developed countries.

A neural network-based model framework for cell-fate decisions and development

Gene regulatory networks (GRNs) fulfill the essential function of maintaining the stability of cellular differentiation states by sustaining lineage-specific gene expression, while driving the progression of development. However, accounting for the relative stability of intermediate differentiation stages and their divergent trajectories remains a major challenge for models of developmental biology. Here, we develop an empirical data-based associative GRN model (AGRN) in which regulatory networks store multilineage stage-specific gene expression profiles as associative memory patterns. These networks are capable of responding to multiple instructive signals and, depending on signal timing and identity, can dynamically drive the differentiation of multipotent cells toward different cell state attractors. The AGRN dynamics can thus generate diverse lineage-committed cell populations in a robust yet flexible manner, providing an attractor-based explanation for signal-driven cell fate decisions during differentiation and offering a readily generalizable modelling tool that can be applied to a wide variety of cell specification systems.

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.

Adrenaline blocks key cell cycle genes and exhibits antifibrotic and vasoconstrictor effects in glaucoma surgery

Adrenaline is a sympathomimetic drug used to maintain pupil dilation and to decrease the risk of bleeding. The aim of this study was to demonstrate if adrenaline could exert antifibrotic effects in glaucoma surgery. Adrenaline was tested in fibroblast-populated collagen contraction assays and there was a dose-response decrease in fibroblast contractility: matrices decreased to 47.4% (P = 0.0002) and 86.6% (P = 0.0036) with adrenaline 0.0005% and 0.01%, respectively. There was no significant decrease in cell viability even at high concentrations. Human Tenon's fibroblasts were also treated with adrenaline (0%, 0.0005%, 0.01%) for 24 h and RNA-Sequencing was performed on the Illumina NextSeq 2000. We carried out detailed gene ontology, pathway, disease and drug enrichment analyses. Adrenaline 0.01% upregulated 26 G1/S and 11 S-phase genes, and downregulated 23 G2 and 17 M-phase genes (P < 0.05). Adrenaline demonstrated similar pathway enrichment to mitosis and spindle checkpoint regulation. Adrenaline 0.05% was also injected subconjunctivally during trabeculectomy, PreserFlo Microshunt and Baerveldt 350 tube surgeries, and patients did not experience any adverse effects. Adrenaline is a safe and cheap antifibrotic drug that significantly blocks key cell cycle genes when used at high concentrations. Unless contraindicated, we recommend subconjunctival injections of adrenaline (0.05%) in all glaucoma bleb-forming surgeries.

ATIC-Associated De Novo Purine Synthesis Is Critically Involved in Proliferative Arterial Disease

BACKGROUND

Proliferation of vascular smooth muscle cells (VSMCs) is a hallmark of arterial diseases, especially in arterial restenosis after angioplasty or stent placement. VSMCs reprogram their metabolism to meet the increased requirements of lipids, proteins, and nucleotides for their proliferation. De novo purine synthesis is one of critical pathways for nucleotide synthesis. However, its role in proliferation of VSMCs in these arterial diseases has not been defined.

METHODS

De novo purine synthesis in proliferative VSMCs was evaluated by liquid chromatography-tandem mass spectrometry. The expression of ATIC (5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/inosine monophosphate cyclohydrolase), the critical bifunctional enzyme in the last 2 steps of the de novo purine synthesis pathway, was assessed in VSMCs of proliferative arterial neointima. Global and VSMC-specific knockout of Atic mice were generated and used for examining the role of ATIC-associated purine metabolism in the formation of arterial neointima and atherosclerotic lesions.

RESULTS

In this study, we found that de novo purine synthesis was increased in proliferative VSMCs. Upregulated purine synthesis genes, including ATIC, were observed in the neointima of the injured vessels and atherosclerotic lesions both in mice and humans. Global or specific knockout of Atic in VSMCs inhibited cell proliferation, attenuating the arterial neointima in models of mouse atherosclerosis and arterial restenosis.

CONCLUSIONS

These results reveal that de novo purine synthesis plays an important role in VSMC proliferation in arterial disease. These findings suggest that targeting ATIC is a promising therapeutic approach to combat arterial diseases.

Targeting NOX4 disrupts the resistance of papillary thyroid carcinoma to chemotherapeutic drugs and lenvatinib

Advanced differentiated thyroid cancer cells are subjected to extreme nutritional starvation which contributes to develop resistance to treatments; however, the underlying mechanism remains unclear. Cells were subjected to serum deprivation by culture in medium containing 0.5% fetal bovine serum. A CCK8 assay, cell death Detection ELISAPLUS kit, and PI staining were conducted to determine cell viability, cell apoptosis, and cell cycle, respectively. NADPH oxidase 4 (NOX4) knockdown–stable cell lines were generated by lentivirus-mediated shRNA knockdown in BCPAP cells and TPC-1 cells. Etoposide and doxorubicin, two chemotherapeutic drugs, as well as lenvatinib were utilized to determine the effect of NOX4 on drug resistance. Lenvatinib-resistant BCPAP cells (LRBCs) were established to confirm this effect. The underlining mechanisms of NOX4 under starvation were explored using western blot. Finally, GLX351322, an inhibitor targeting NOX4, was used to inhibit NOX4-derived ROS in vitro and detect its effect on drug resistance of tumor cells in vivo. NOX4 is overexpressed under serum deprivation in BCPAP or TPC-1 cells. NOX4 knockdown impairs cell viability, increases cell apoptosis, extends G1 phase during cell cycle and modulates the level of energy-associated metabolites in starved cells. When the starved cells or LRBCs are treated with chemotherapeutic drugs or Lenvatinib, NOX4 knockdown inhibits cell viability and aggravates cell apoptosis depending on NOX4-derived ROS production. Mechanistically, starvation activates TGFβ1/SMAD3 signal, which mediates NOX4 upregulation. The upregulated NOX4 then triggers ERKs and PI3K/AKT pathway to influence cell apoptosis. GLX351322, a NOX4-derived ROS inhibitor, has an inhibitory effect on cell growth in vitro and the growth of BCPAP-derived even LRBCs-derived xenografts in vivo. These findings highlight NOX4 and NOX4-derived ROS as a potential therapeutic target in resistance to PTC.

The MuvB complex binds and stabilizes nucleosomes downstream of the transcription start site of cell-cycle dependent genes

The chromatin architecture in promoters is thought to regulate gene expression, but it remains uncertain how most transcription factors (TFs) impact nucleosome position. The MuvB TF complex regulates cell-cycle dependent gene-expression and is critical for differentiation and proliferation during development and cancer. MuvB can both positively and negatively regulate expression, but the structure of MuvB and its biochemical function are poorly understood. Here we determine the overall architecture of MuvB assembly and the crystal structure of a subcomplex critical for MuvB function in gene repression. We find that the MuvB subunits LIN9 and LIN37 function as scaffolding proteins that arrange the other subunits LIN52, LIN54 and RBAP48 for TF, DNA, and histone binding, respectively. Biochemical and structural data demonstrate that MuvB binds nucleosomes through an interface that is distinct from LIN54-DNA consensus site recognition and that MuvB increases nucleosome occupancy in a reconstituted promoter. We find in arrested cells that MuvB primarily associates with a tightly positioned +1 nucleosome near the transcription start site (TSS) of MuvB-regulated genes. These results support a model that MuvB binds and stabilizes nucleosomes just downstream of the TSS on its target promoters to repress gene expression.

The MuvB protein complex regulates genes that are differentially expressed through the cell cycle, yet its precise molecular function has remained unclear. Here the authors reveal MuvB associates with the nucleosome adjacent to the transcription start site of cell-cycle genes and that the tight positioning of this nucleosome correlates with MuvB-dependent gene repression.

Time-resolved single-cell sequencing identifies multiple waves of mRNA decay during the mitosis-to-G1 phase transition

Accurate control of the cell cycle is critical for development and tissue homeostasis, and requires precisely timed expression of many genes. Cell cycle gene expression is regulated through transcriptional and translational control, as well as through regulated protein degradation. Here, we show that widespread and temporally controlled mRNA decay acts as an additional mechanism for gene expression regulation during the cell cycle in human cells. We find that two waves of mRNA decay occur sequentially during the mitosis-to-G1 phase transition, and we identify the deadenylase CNOT1 as a factor that contributes to mRNA decay during this cell cycle transition. Collectively, our data show that, akin to protein degradation, scheduled mRNA decay helps to reshape cell cycle gene expression as cells move from mitosis into G1 phase.

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.

Recent insights into mechanisms preventing ectopic centromere formation

The centromere is a specialized chromosomal structure essential for chromosome segregation. Centromere dysfunction leads to chromosome segregation errors and genome instability. In most eukaryotes, centromere identity is specified epigenetically by CENP-A, a centromere-specific histone H3 variant. CENP-A replaces histone H3 in centromeres, and nucleates the assembly of the kinetochore complex. Mislocalization of CENP-A to non-centromeric regions causes ectopic assembly of CENP-A chromatin, which has a devastating impact on chromosome segregation and has been linked to a variety of human cancers. How non-centromeric regions are protected from CENP-A misincorporation in normal cells is largely unexplored. Here, we review the most recent advances on the mechanisms underlying the prevention of ectopic centromere formation, and discuss the implications in human disease.

Noncontact Multiphysics Probe for Spatiotemporal Resolved Single-Cell Manipulation and Analyses

Heterogeneity and spatial arrangement of individual cells within tissues are critical to the identity of the host multicellular organism. While current single-cell techniques are capable of resolving heterogeneity, they mostly rely on extracting target cells from their physiological environment and hence lose the spatiotemporal resolution required for understanding cellular networks. Here, a multifunctional noncontact scanning probe that can precisely perform multiple manipulation procedures on living single-cells, while within their physiological tissue environment, is demonstrated. The noncontact multiphysics probe (NMP) consists of fluidic apertures and "hump" shaped electrodes that simultaneously confine reagents and electric signals with a single-cell resolution. The NMP's unique electropermealization-based approach in transferring macromolecules through the cell membrane is presented. The technology's adjustable spatial ability is demonstrated by transfecting adjacent single-cells with different DNA plasmid vectors. The NMP technology also opens the door for controllable cytoplasm extraction from living single-cells. This powerful application is demonstrated by executing multiple time point biopsies on adherent cells without affecting the integrity of the extracted macromolecules or the viability of cells. Furthermore, the NMP's function as an electro-thermal based microfluidic whole-cell tweezer is reported. This work offers a multifunctional tool with unprecedented probing features for spatiotemporal single-cell analysis within tissue samples.

Aggregation-induced emission luminogens reveal cell cycle-dependent telomerase activity in cancer cells

Telomerase acts as an important biomarker for tumor identification, and synthesizes telomeric repeats at the end of chromosome telomeres during the replicative phase of the cell cycle; thus, the expression level of telomerase changes as the cell cycle progresses. TERT mRNA expression and telomerase activity were significantly increased in over 80% of human cancers from tissue specimens. Although many efforts have been made in detecting the activity of TERT mRNA and active telomerase, the heterogeneous behavior of the cell cycle was overlooked, which might affect the accuracy of the detection results. Herein, the AIEgen-based biosensing systems of PyTPA-DNA and Silole-R were developed to detect the cellular level of TERT mRNA and telomerase in different cell cycles. As a result, the fluorescence signal of cancer cells gradually increased from G0/G1, G1/S to S phase. In contrast, both cancer cells arrested at G2/M phase and normal cells exhibited negligible fluorescence intensities. Compared to normal tissues, malignant tumor samples demonstrated a significant turn-on fluorescence signal. Furthermore, the transcriptomics profiling revealed that tumor biomarkers changed as the cell cycle progressed and biomarkers of CA9, TK1 and EGFR were more abundantly expressed at early S stage. In this vein, our study presented advanced biosensing tools for more accurate analysis of the cell-cycle-dependent activity of TERT mRNA and active telomerase in clinical tissue samples.

Machine Intelligence in Single-Cell Data Analysis: Advances and New Challenges

The rapid development of single-cell technologies allows for dissecting cellular heterogeneity at different omics layers with an unprecedented resolution. In-dep analysis of cellular heterogeneity will boost our understanding of complex biological systems or processes, including cancer, immune system and chronic diseases, thereby providing valuable insights for clinical and translational research. In this review, we will focus on the application of machine learning methods in single-cell multi-omics data analysis. We will start with the pre-processing of single-cell RNA sequencing (scRNA-seq) data, including data imputation, cross-platform batch effect removal, and cell cycle and cell-type identification. Next, we will introduce advanced data analysis tools and methods used for copy number variance estimate, single-cell pseudo-time trajectory analysis, phylogenetic tree inference, cell-cell interaction, regulatory network inference, and integrated analysis of scRNA-seq and spatial transcriptome data. Finally, we will present the latest analyzing challenges, such as multi-omics integration and integrated analysis of scRNA-seq data.

Intricate Regulatory Mechanisms of the Anaphase-Promoting Complex/Cyclosome and Its Role in Chromatin Regulation

The ubiquitin (Ub)-proteasome system is vital to nearly every biological process in eukaryotes. Specifically, the conjugation of Ub to target proteins by Ub ligases, such as the Anaphase-Promoting Complex/Cyclosome (APC/C), is paramount for cell cycle transitions as it leads to the irreversible destruction of cell cycle regulators by the proteasome. Through this activity, the RING Ub ligase APC/C governs mitosis, G1, and numerous aspects of neurobiology. Pioneering cryo-EM, biochemical reconstitution, and cell-based studies have illuminated many aspects of the conformational dynamics of this large, multi-subunit complex and the sophisticated regulation of APC/C function. More recent studies have revealed new mechanisms that selectively dictate APC/C activity and explore additional pathways that are controlled by APC/C-mediated ubiquitination, including an intimate relationship with chromatin regulation. These tasks go beyond the traditional cell cycle role historically ascribed to the APC/C. Here, we review these novel findings, examine the mechanistic implications of APC/C regulation, and discuss the role of the APC/C in previously unappreciated signaling pathways.

What are the applications of single-cell RNA sequencing in cancer research: a systematic review

Single-cell RNA sequencing (scRNA-seq) is a tool for studying gene expression at the single-cell level that has been widely used due to its unprecedented high resolution. In the present review, we outline the preparation process and sequencing platforms for the scRNA-seq analysis of solid tumor specimens and discuss the main steps and methods used during data analysis, including quality control, batch-effect correction, normalization, cell cycle phase assignment, clustering, cell trajectory and pseudo-time reconstruction, differential expression analysis and gene set enrichment analysis, as well as gene regulatory network inference. Traditional bulk RNA sequencing does not address the heterogeneity within and between tumors, and since the development of the first scRNA-seq technique, this approach has been widely used in cancer research to better understand cancer cell biology and pathogenetic mechanisms. ScRNA-seq has been of great significance for the development of targeted therapy and immunotherapy. In the second part of this review, we focus on the application of scRNA-seq in solid tumors, and summarize the findings and achievements in tumor research afforded by its use. ScRNA-seq holds promise for improving our understanding of the molecular characteristics of cancer, and potentially contributing to improved diagnosis, prognosis, and therapeutics.

A New Insight for the Identification of Oncogenic Variants in Breast and Prostate Cancers in Diverse Human Populations, With a Focus on Latinos

Background: Breast cancer (BRCA) and prostate cancer (PRCA) are the most commonly diagnosed cancer types in Latin American women and men, respectively. Although in recent years large-scale efforts from international consortia have focused on improving precision oncology, a better understanding of genomic features of BRCA and PRCA in developing regions and racial/ethnic minority populations is still required.

Methods: To fill in this gap, we performed integrated in silico analyses to elucidate oncogenic variants from BRCA and PRCA driver genes; to calculate their deleteriousness scores and allele frequencies from seven human populations worldwide, including Latinos; and to propose the most effective therapeutic strategies based on precision oncology.

Results: We analyzed 339,100 variants belonging to 99 BRCA and 82 PRCA driver genes and identified 18,512 and 15,648 known/predicted oncogenic variants, respectively. Regarding known oncogenic variants, we prioritized the most frequent and deleterious variants of BRCA (n = 230) and PRCA (n = 167) from Latino, African, Ashkenazi Jewish, East Asian, South Asian, European Finnish, and European non-Finnish populations, to incorporate them into pharmacogenomics testing. Lastly, we identified which oncogenic variants may shape the response to anti-cancer therapies, detailing the current status of pharmacogenomics guidelines and clinical trials involved in BRCA and PRCA cancer driver proteins.

Conclusion: It is imperative to unify efforts where developing countries might invest in obtaining databases of genomic profiles of their populations, and developed countries might incorporate racial/ethnic minority populations in future clinical trials and cancer researches with the overall objective of fomenting pharmacogenomics in clinical practice and public health policies.

Unraveling Heterogeneity of Tumor Cells and Microenvironment and Its Clinical Implications for Triple Negative Breast Cancer

Objective: Triple negative breast cancer (TNBC) is an aggressive subtype of breast cancer, characterized by extensive intratumoral heterogeneity. We aimed to systematically characterize the tumor heterogeneity of TNBC. Methods: Single-cell RNA sequencing (scRNA-seq) of TNBC cells were obtained from the GSE118389 and GSE75688 datasets. After integration of the two datasets, cell clustering analysis was performed using the Seurat package. According to the marker genes of cell cycle, cell cycle of each cell cluster was determined. Then, function enrichment analysis of marker genes in each cell cluster was performed, followed by ligand-receptor signaling network analysis. CIBERSORT was used to estimate the proportion of 22 immune cells in each sample based on RNA-seq data of 58 normal adjacent tissues and 101 TNBC tissues. After that, prognostic value of immune cells was assessed. Results: In the integrated datasets, five cells types including B cells, myeloid cells, stromal cells, T cells, and tumor cells were clustered. Functional enrichment analysis revealed the functional heterogeneity of genes in each cell. Intercellular communication networks were conducted based on ligand-receptor pairs. The heterogeneity in the fractions of 22 immune cells was found in TNBC tissues. Furthermore, there was a significant difference in the fractions of these immune cells between adjacent normal tissues and TNBC tissues. Among them, M2 macrophages and neutrophils were significantly associated with clinical outcomes of TNBC. Moreover, the fractions of T cells CD4 memory resting, monocytes, neutrophils, M1 macrophages, and T cells CD4 memory activated were significantly correlated with clinical characteristics of TNBC. As shown in PCA results, these immune cells could significantly distinguish TNBC tissues into adjacent normal tissues. Conclusion: Our findings characterized the tumor heterogeneity of TNBC, which deepened the understanding of the complex interactions between tumor cells and their microenvironment, especially immune cells.

GENAVOS: A New Tool for Modelling and Analyzing Cancer Gene Regulatory Networks Using Delayed Nonlinear Variable Order Fractional System

Gene regulatory networks (GRN) are one of the etiologies associated with cancer. Their dysregulation can be associated with cancer formation and asymmetric cellular functions in cancer stem cells, leading to disease persistence and resistance to treatment. Systems that model the complex dynamics of these networks along with adapting to partially known real omics data are closer to reality and may be useful to understand the mechanisms underlying neoplastic phenomena. In this paper, for the first time, modelling of GRNs is performed using delayed nonlinear variable order fractional (VOF) systems in the state space by a new tool called GENAVOS. Although the tool uses gene expression time series data to identify and optimize system parameters, it also models possible epigenetic signals, and the results show that the nonlinear VOF systems have very good flexibility in adapting to real data. We found that GRNs in cancer cells actually have a larger delay parameter than in normal cells. It is also possible to create weak chaotic, periodic, and quasi-periodic oscillations by changing the parameters. Chaos can be associated with the onset of cancer. Our findings indicate a profound effect of time-varying orders on these networks, which may be related to a type of cellular epigenetic memory. By changing the delay parameter and the variable order functions (possible epigenetics signals) for a normal cell system, its behaviour becomes quite similar to the behaviour of a cancer cell. This work confirms the effective role of the miR-17-92 cluster as an epigenetic factor in the cancer cell cycle.

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.

Sirtuin 5 Is Regulated by the SCFCyclin F Ubiquitin Ligase and Is Involved in Cell Cycle Control

The ubiquitin-proteasome system is essential for cell cycle progression. Cyclin F is a cell cycle-regulated substrate adapter F-box protein for the Skp1, CUL1, and F-box protein (SCF) family of E3 ubiquitin ligases. Despite its importance in cell cycle progression, identifying cyclin F-bound SCF complex (SCF^{Cyclin F}) substrates has remained challenging. Since cyclin F overexpression rescues a yeast mutant in the cdc4 gene, we considered the possibility that other genes that genetically modify cdc4 mutant lethality could also encode cyclin F substrates. We identified the mitochondrial and cytosolic deacylating enzyme sirtuin 5 (SIRT5) as a novel cyclin F substrate. SIRT5 has been implicated in metabolic processes, but its connection to the cell cycle is not known. We show that cyclin F interacts with and controls the ubiquitination, abundance, and stability of SIRT5. We show SIRT5 knockout results in a diminished G₁ population and a subsequent increase in both S and G₂/M. Global proteomic analyses reveal cyclin-dependent kinase (CDK) signaling changes congruent with the cell cycle changes in SIRT5 knockout cells. Together, these data demonstrate that SIRT5 is regulated by cyclin F and suggest a connection between SIRT5, cell cycle regulation, and metabolism.

Manipulation of the human tRNA pool reveals distinct tRNA sets that act in cellular proliferation or cell cycle arrest

Different subsets of the tRNA pool in human cells are expressed in different cellular conditions. The 'proliferation-tRNAs' are induced upon normal and cancerous cell division, while the 'differentiation-tRNAs' are active in non-dividing, differentiated cells. Here we examine the essentiality of the various tRNAs upon cellular growth and arrest. We established a CRISPR-based editing procedure with sgRNAs that each target a tRNA family. We measured tRNA essentiality for cellular growth and found that most proliferation-tRNAs are essential compared to differentiation- tRNAs in rapidly growing cell lines. Yet in more slowly dividing lines, the differentiation-tRNAs were more essential. In addition, we measured the essentiality of each tRNA family upon response to cell cycle arresting signals. Here we detected a more complex behavior with both proliferation-tRNAs and differentiation tRNAs showing various levels of essentiality. These results provide the so-far most comprehensive functional characterization of human tRNAs with intricate roles in various cellular states.

In silico APC/C substrate discovery reveals cell cycle-dependent degradation of UHRF1 and other chromatin regulators

The anaphase-promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase and critical regulator of cell cycle progression. Despite its vital role, it has remained challenging to globally map APC/C substrates. By combining orthogonal features of known substrates, we predicted APC/C substrates in silico. This analysis identified many known substrates and suggested numerous candidates. Unexpectedly, chromatin regulatory proteins are enriched among putative substrates, and we show experimentally that several chromatin proteins bind APC/C, oscillate during the cell cycle, and are degraded following APC/C activation, consistent with being direct APC/C substrates. Additional analysis revealed detailed mechanisms of ubiquitylation for UHRF1, a key chromatin regulator involved in histone ubiquitylation and DNA methylation maintenance. Disrupting UHRF1 degradation at mitotic exit accelerates G1-phase cell cycle progression and perturbs global DNA methylation patterning in the genome. We conclude that APC/C coordinates crosstalk between cell cycle and chromatin regulatory proteins. This has potential consequences in normal cell physiology, where the chromatin environment changes depending on proliferative state, as well as in disease.

Why Great Mitotic Inhibitors Make Poor Cancer Drugs

Chemotherapy is central to oncology, perceived to operate only on prolific cancerous tissue. Yet, many non-neoplastic tissues are more prolific compared with typical tumors. Chemotherapies achieve sufficient therapeutic windows to exert antineoplastic activity because they are prodrugs that are bioactivated in cancer-specific environments. The advent of precision medicine has obscured this concept, favoring the development of high-potency kinase inhibitors. Inhibitors of essential mitotic kinases exemplify this paradigm shift, but intolerable on-target toxicities in more prolific normal tissues have led to repeated failures in the clinic. Proliferation rates alone cannot be used to achieve cancer specificity. Here, we discuss integrating the cancer specificity of prodrugs from classical chemotherapeutics and the potency of mitotic kinase inhibitors to generate a class of high-precision cancer therapeutics.

Complex Cartography: Regulation of E2F Transcription Factors by Cyclin F and Ubiquitin

The E2F family of transcriptional regulators sits at the center of cell cycle gene expression and plays vital roles in normal and cancer cell cycles. Whereas control of E2Fs by the retinoblastoma family of proteins is well established, much less is known about their regulation by ubiquitin pathways. Recent studies placed the Skp1-Cul1-F-box-protein (SCF) family of E3 ubiquitin ligases with the F-box protein Cyclin F at the center of E2F regulation, demonstrating temporal proteolysis of both activator and atypical repressor E2Fs. Importantly, these E2F members, in particular activator E2F1 and repressors E2F7 and E2F8, form a feedback circuit at the crossroads of cell cycle and cell death. Moreover, Cyclin F functions in a reciprocal circuit with the cell cycle E3 ligase anaphase-promoting complex/cyclosome (APC/C), which also controls E2F7 and E2F8. This review focuses on the complex contours of feedback within this circuit, highlighting the deep crosstalk between E2F, SCF-Cyclin F, and APC/C in regulating the oscillator underlying human cell cycles.

Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks

Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the prediction of proteins involved in this disease is a trending topic in drug design. This work is proposing accurate prediction classifier for BC proteins using six sets of protein sequence descriptors and 13 machine-learning methods. After using a univariate feature selection for the mix of five descriptor families, the best classifier was obtained using multilayer perceptron method (artificial neural network) and 300 features. The performance of the model is demonstrated by the area under the receiver operating characteristics (AUROC) of 0.980 ± 0.0037, and accuracy of 0.936 ± 0.0056 (3-fold cross-validation). Regarding the prediction of 4,504 cancer-associated proteins using this model, the best ranked cancer immunotherapy proteins related to BC were RPS27, SUPT4H1, CLPSL2, POLR2K, RPL38, AKT3, CDK3, RPS20, RASL11A and UBTD1; the best ranked metastasis driver proteins related to BC were S100A9, DDA1, TXN, PRNP, RPS27, S100A14, S100A7, MAPK1, AGR3 and NDUFA13; and the best ranked RNA-binding proteins related to BC were S100A9, TXN, RPS27L, RPS27, RPS27A, RPL38, MRPL54, PPAN, RPS20 and CSRP1. This powerful model predicts several BC-related proteins that should be deeply studied to find new biomarkers and better therapeutic targets. Scripts can be downloaded at https://github.com/muntisa/neural-networks-for-breast-cancer-proteins.

OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

Breast cancer (BC) is the leading cause of cancer-related death among women and the most commonly diagnosed cancer worldwide. Although in recent years large-scale efforts have focused on identifying new therapeutic targets, a better understanding of BC molecular processes is required. Here we focused on elucidating the molecular hallmarks of BC heterogeneity and the oncogenic mutations involved in precision medicine that remains poorly defined. To fill this gap, we established an OncoOmics strategy that consists of analyzing genomic alterations, signaling pathways, protein-protein interactome network, protein expression, dependency maps in cell lines and patient-derived xenografts in 230 previously prioritized genes to reveal essential genes in breast cancer. As results, the OncoOmics BC essential genes were rationally filtered to 140. mRNA up-regulation was the most prevalent genomic alteration. The most altered signaling pathways were associated with basal-like and Her2-enriched molecular subtypes. RAC1, AKT1, CCND1, PIK3CA, ERBB2, CDH1, MAPK14, TP53, MAPK1, SRC, RAC3, BCL2, CTNNB1, EGFR, CDK2, GRB2, MED1 and GATA3 were essential genes in at least three OncoOmics approaches. Drugs with the highest amount of clinical trials in phases 3 and 4 were paclitaxel, docetaxel, trastuzumab, tamoxifen and doxorubicin. Lastly, we collected ~3,500 somatic and germline oncogenic variants associated with 50 essential genes, which in turn had therapeutic connectivity with 73 drugs. In conclusion, the OncoOmics strategy reveals essential genes capable of accelerating the development of targeted therapies for precision oncology.

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.

Single-stranded DNA damage: Protecting the single-stranded DNA from chemical attack

Cellular processes, such as DNA replication, recombination and transcription, require DNA strands separation and single-stranded DNA is formation. The single-stranded DNA is promptly wrapped by human single-stranded DNA binding proteins, replication protein A (RPA) complex. RPA binding not only prevent nuclease degradation and annealing, but it also coordinates cell-cycle checkpoint activation and DNA repair. However, RPA binding offers little protection against the chemical modification of DNA bases. This review focuses on the type of DNA base damage that occurs in single-stranded DNA and how the damage is rectified in human cells. The discovery of DNA repair proteins, such as ALKBH3, AGT, UNG2, NEIL3, being able to repair the damaged base in the single-stranded DNA, renewed the interest to study single-stranded DNA repair. These mechanistically different proteins work independently from each other with the overarching goal of increasing fidelity of recombination and promoting error-free replication.

Short- and Long-Term Effects of CDK4/6 Inhibition on Early-Stage Breast Cancer

CDK4/6 inhibitors are used in the treatment of advanced estrogen receptor (ER)(+) breast cancer. Their efficacy in ER(-) and early-stage breast cancer is currently under investigation. Here, we show that palbociclib, a CDK4/6 inhibitor, can inhibit both progression of ductal carcinoma in situ (DCIS) and growth of invasive disease in both an ER(-) basal breast cancer model (MCFDCIS) and an ER(+) luminal model (MCF7 intraductal injection). In MCFDCIS cells, palbociclib repressed cell-cycle gene expression, inhibited proliferation, induced senescence, and normalized tumorspheres formed in Matrigel while the formation of acini by normal mammary epithelial cells (MCF10A) was not affected. Palbociclib treatment of mice with MCFDCIS tumors inhibited their malignant progression and reduced proliferation of invasive lesions. Transcriptomic analysis of the tumor and stromal cell compartments showed that cell cycle and senescence genes, and MUC16, an ovarian cancer biomarker gene, were repressed during treatment. Knockdown of MUC16 in MCFDCIS cells inhibited proliferation of invasive lesions but not progression of DCIS. After cessation of palbociclib treatment genes associated with differentiation, for example, P63, inflammation, IFNγ response, and antigen processing and presentation remained suppressed in the tumor and surrounding stroma. We conclude that palbociclib can prevent progression of DCIS and is antiproliferative in ER(-) invasive disease mediated in part via MUC16. Lasting effects of CDK4/6 inhibition after drug withdrawal on differentiation and the immune response could impact the approach to treatment of early-stage ER(-) breast cancer.

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.

Computational deconvolution of transcriptomics data from mixed cell populations

Summary

Gene expression analyses of bulk tissues often ignore cell type composition as an important confounding factor, resulting in a loss of signal from lowly abundant cell types. In this review, we highlight the importance and value of computational deconvolution methods to infer the abundance of different cell types and/or cell type-specific expression profiles in heterogeneous samples without performing physical cell sorting. We also explain the various deconvolution scenarios, the mathematical approaches used to solve them and the effect of data processing and different confounding factors on the accuracy of the deconvolution results.

Contact

katleen.depreter@ugent.be.

Supplementary information

Supplementary data are available at Bioinformatics online.

Vitamin B12 , folate, and the methionine remethylation cycle-biochemistry, pathways, and regulation

Vitamin B₁₂ (cobalamin, Cbl) is a nutrient essential to human health. Due to its complex structure and dual cofactor forms, Cbl undergoes a complicated series of absorptive and processing steps before serving as cofactor for the enzymes methylmalonyl-CoA mutase and methionine synthase. Methylmalonyl-CoA mutase is required for the catabolism of certain (branched-chain) amino acids into an anaplerotic substrate in the mitochondrion, and dysfunction of the enzyme itself or in production of its cofactor adenosyl-Cbl result in an inability to successfully undergo protein catabolism with concomitant mitochondrial energy disruption. Methionine synthase catalyzes the methyl-Cbl dependent (re)methylation of homocysteine to methionine within the methionine cycle; a reaction required to produce this essential amino acid and generate S-adenosylmethionine, the most important cellular methyl-donor. Disruption of methionine synthase has wide-ranging implications for all methylation-dependent reactions, including epigenetic modification, but also for the intracellular folate pathway, since methionine synthase uses 5-methyltetrahydrofolate as a one-carbon donor. Folate-bound one-carbon units are also required for deoxythymidine monophosphate and de novo purine synthesis; therefore, the flow of single carbon units to each of these pathways must be regulated based on cellular needs. This review provides an overview on Cbl metabolism with a brief description of absorption and intracellular metabolic pathways. It also provides a description of folate-mediated one-carbon metabolism and its intersection with Cbl at the methionine cycle. Finally, a summary of recent advances in understanding of how both pathways are regulated is presented.

Unbiased Boolean analysis of public gene expression data for cell cycle gene identification

Cell proliferation is essential for the development and maintenance of all organisms and is dysregulated in cancer. Using synchronized cells progressing through the cell cycle, pioneering microarray studies defined cell cycle genes based on cyclic variation in their expression. However, the concordance of the small number of synchronized cell studies has been limited, leading to discrepancies in definition of the transcriptionally regulated set of cell cycle genes within and between species. Here we present an informatics approach based on Boolean logic to identify cell cycle genes. This approach used the vast array of publicly available gene expression data sets to query similarity to CCNB1, which encodes the cyclin subunit of the Cdk1-cyclin B complex that triggers the G2-to-M transition. In addition to highlighting conservation of cell cycle genes across large evolutionary distances, this approach identified contexts where well-studied genes known to act during the cell cycle are expressed and potentially acting in nondivision contexts. An accessible web platform enables a detailed exploration of the cell cycle gene lists generated using the Boolean logic approach. The methods employed are straightforward to extend to processes other than the cell cycle.

Cell Cycle-Regulated Transcription of CENP-A by the MBF Complex Ensures Optimal Level of CENP-A for Centromere Formation

The centromere plays an essential role in chromosome segregation. In most eukaryotes, centromeres are epigenetically defined by the conserved histone H3 variant CENP-A. Proper centromere assembly is dependent upon the tight regulation of CENP-A level. Cell cycle regulation of CENP-A transcription appears to be a universal feature across eukaryotes, but the molecular mechanism underlying the temporal control of CENP-A transcription and how such regulation contributes to centromere function remains elusive. CENP-A in fission yeast has been shown to be transcribed before S phase. Using various synchronization methods, we confirmed that CENP-A transcription occurs at G1, leading to an almost twofold increase of the protein during S phase. Through a genetic screen, we identified the MBF (MluI box-binding factors) complex as a key regulator of temporal control of CENP-A transcription. The periodic transcription of CENP-A is lost in MBF mutants, resulting in CENP-A mislocalization and chromosome segregation defects. We identified the MCB (MluI cell cycle box) motif in the CENP-A promoter, and further showed that the MBF complex binds to the motif to restrict CENP-A transcription to G1. Mutations of the MCB motif cause constitutive CENP-A expression and deleterious effects on cell survival. Using promoters driving transcription to different cell cycle stages, we found that timing of CENP-A transcription is dispensable for its centromeric localization. Our data instead indicate that cell cycle-regulated CENP-A transcription is a key step to ensure that a proper amount of CENP-A is generated across generations. This study provides mechanistic insights into the regulation of cell cycle-dependent CENP-A transcription, as well as its importance on centromere function.

Classification of Single-Cell Gene Expression Trajectories from Incomplete and Noisy Data

This paper studies classification of gene-expression trajectories coming from two classes, healthy and mutated (cancerous) using Boolean networks with perturbation (BNps) to model the dynamics of each class at the state level. Each class has its own BNp, which is partially known based on gene pathways. We employ a Gaussian model at the observation level to show the expression values of the genes given the hidden binary states at each time point. We use expectation maximization (EM) to learn the BNps and the unknown model parameters, derive closed-form updates for the parameters, and propose a learning algorithm. After learning, a plug-in Bayes classifier is used to classify unlabeled trajectories, which can have missing data. Measuring gene expressions at different times yields trajectories only when measurements come from a single cell. In multiple-cell scenarios, the expression values are averages over many cells with possibly different states. Via the central-limit theorem, we propose another model for expression data in multiple-cell scenarios. Simulations demonstrate that single-cell trajectory data can outperform multiple-cell average expression data relative to classification error, especially in high-noise situations. We also consider data generated via a mammalian cell-cycle network, both the wild-type and with a common mutation affecting p27.

Who guards the guardian? Mechanisms that restrain APC/C during the cell cycle

The cell cycle is principally controlled by Cyclin Dependent Kinases (CDKs), whose oscillating activities are determined by binding to Cyclin coactivators. Cyclins exhibit dynamic changes in abundance as cells pass through the cell cycle. The sequential, timed accumulation and degradation of Cyclins, as well as many other proteins, imposes order on the cell cycle and contributes to genome maintenance. The destruction of many cell cycle regulated proteins, including Cyclins A and B, is controlled by a large, multi-subunit E3 ubiquitin ligase termed the Anaphase Promoting Complex/Cyclosome (APC/C). APC/C activity is tightly regulated during the cell cycle. Its activation state increases dramatically in mid-mitosis and it remains active until the end of G1 phase. Following its mandatory inactivation at the G1/S boundary, APC/C activity remains low until the subsequent mitosis. Due to its role in guarding against the inappropriate or untimely accumulation of Cyclins, the APC/C is a core component of the cell cycle oscillator. In addition to the regulation of Cyclins, APC/C controls the degradation of many other substrates. Therefore, it is vital that the activity of APC/C itself be tightly guarded. The APC/C is most well studied for its role and regulation during mitosis. However, the APC/C also plays a similarly important and conserved role in the maintenance of G1 phase. Here we review the diverse mechanisms counteracting APC/C activity throughout the cell cycle and the importance of their coordinated actions on cell growth, proliferation, and disease.

Contributions of regulated transcription and mRNA decay to the dynamics of gene expression

Organisms have acquired sophisticated regulatory networks that control gene expression in response to cellular perturbations. Understanding of the mechanisms underlying the coordinated changes in gene expression in response to external and internal stimuli is a fundamental issue in biology. Recent advances in high-throughput technologies have enabled the measurement of diverse biological information, including gene expression levels, kinetics of gene expression, and interactions among gene expression regulatory molecules. By coupling these technologies with quantitative modeling, we can now uncover the biological roles and mechanisms of gene regulation at the system level. This review consists of two parts. First, we focus on the methods using uridine analogs that measure synthesis and decay rates of RNAs, which demonstrate how cells dynamically change the regulation of gene expression in response to both internal and external cues. Second, we discuss the underlying mechanisms of these changes in kinetics, including the functions of transcription factors and RNA-binding proteins. Overall, this review will help to clarify a system-level view of gene expression programs in cells. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Turnover and Surveillance > Regulation of RNA Stability RNA Methods > RNA Analyses in vitro and In Silico.

Study of mitotic chromatin supports a model of bookmarking by histone modifications and reveals nucleosome deposition patterns

Mitosis encompasses key molecular changes including chromatin condensation, nuclear envelope breakdown, and reduced transcription levels. Immediately after mitosis, the interphase chromatin structure is reestablished and transcription resumes. The reestablishment of the interphase chromatin is probably achieved by "bookmarking," i.e., the retention of at least partial information during mitosis. To gain a deeper understanding of the contribution of histone modifications to the mitotic bookmarking process, we merged proteomics, immunofluorescence, and ChIP-seq approaches. We focused on key histone modifications and employed HeLa-S3 cells as a model system. Generally, in spite of the general hypoacetylation observed during mitosis, we observed a global concordance between the genomic organization of histone modifications in interphase and mitosis, suggesting that the epigenomic landscape may serve as a component of the mitotic bookmarking process. Next, we investigated the nucleosome that enters nucleosome depleted regions (NDRs) during mitosis. We observed that in ∼60% of the NDRs, the entering nucleosome is distinct from the surrounding highly acetylated nucleosomes and appears to have either low levels of acetylation or high levels of phosphorylation in adjacent residues (since adjacent phosphorylation may interfere with the ability to detect acetylation). Inhibition of histone deacetylases (HDACs) by the small molecule TSA reverts this pattern, suggesting that these nucleosomes are specifically deacetylated during mitosis. Altogether, by merging multiple approaches, our study provides evidence to support a model where histone modifications may play a role in mitotic bookmarking and uncovers new insights into the deposition of nucleosomes during mitosis.

Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken

Background

The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues.

Results

Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development.

Conclusion

Expression profiles obtained from public RNA-seq datasets – despite being generated by different laboratories using different methodologies – can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4972-7) contains supplementary material, which is available to authorized users.

Cezanne/OTUD7B is a cell cycle-regulated deubiquitinase that antagonizes the degradation of APC/C substrates

The anaphase-promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase and key regulator of cell cycle progression. Since APC/C promotes the degradation of mitotic cyclins, it controls cell cycle-dependent oscillations in cyclin-dependent kinase (CDK) activity. Both CDKs and APC/C control a large number of substrates and are regulated by analogous mechanisms, including cofactor-dependent activation. However, whereas substrate dephosphorylation is known to counteract CDK, it remains largely unknown whether deubiquitinating enzymes (DUBs) antagonize APC/C substrate ubiquitination during mitosis. Here, we demonstrate that Cezanne/OTUD7B is a cell cycle-regulated DUB that opposes the ubiquitination of APC/C targets. Cezanne is remarkably specific for K11-linked ubiquitin chains, which are formed by APC/C in mitosis. Accordingly, Cezanne binds established APC/C substrates and reverses their APC/C-mediated ubiquitination. Cezanne depletion accelerates APC/C substrate degradation and causes errors in mitotic progression and formation of micronuclei. These data highlight the importance of tempered APC/C substrate destruction in maintaining chromosome stability. Furthermore, Cezanne is recurrently amplified and overexpressed in numerous malignancies, suggesting a potential role in genome maintenance and cancer cell proliferation.

Human foreskin fibroblasts: from waste bag to important biomedical applications

Circumcision is one of the most performed surgical procedures worldwide, and it is estimated that one in three men worldwide is circumcised, which makes the preputial skin removed after surgery an abundant material for possible applications. In particular, it is possible efficiently to isolate the cells of the foreskin, with fibroblasts being the most abundant cells of the dermis and the most used in biomedical research. This work aimed to review the knowledge and obtain a broad view of the main applications of human foreskin fibroblast cell culture. A literature search was conducted, including clinical trials, preclinical basic research studies, reviews and experimental studies. Several medical and laboratory applications of human foreskin fibroblast cell culture have been described, especially when it comes to the use of human foreskin fibroblasts as feeder cells for the cultivation of human embryonic stem cells, in addition to co-culture with other cell types. The culture of foreskin fibroblasts has also been used to: obtain induced pluripotent stem cells; the diagnosis of Clostridium difficile; to test the toxicity and effect of substances on normal cells, especially the toxicity of possible antineoplastic drugs; in viral culture, mainly of the human cytomegalovirus, study of the pathogenesis of other microorganisms; varied studies of cellular physiology and cellular interactions. Fibroblasts are important for cell models for varied application cultures, demonstrating how the preputial material can be reused, making possible new applications.

Level of evidence: Not applicable for this multicentre audit.

The evolution of a G1/S transcriptional network in yeasts

The G1-to-S cell cycle transition is promoted by the periodic expression of a large set of genes. In Saccharomyces cerevisiae G1/S gene expression is regulated by two transcription factor (TF) complexes, the MBF and SBF, which bind to specific DNA sequences, the MCB and SCB, respectively. Despite extensive research little is known regarding the evolution of the G1/S transcription regulation including the co-evolution of the DNA binding domains with their respective DNA binding sequences. We have recently examined the co-evolution of the G1/S TF specificity through the systematic generation and examination of chimeric Mbp1/Swi4 TFs containing different orthologue DNA binding domains in S. cerevisiae (Hendler et al. in PLoS Genet 13:e1006778. doi: 10.1371/journal.pgen.1006778 , 2017). Here, we review the co-evolution of G1/S transcriptional network and discuss the evolutionary dynamics and specificity of the MBF-MCB and SBF-SCB interactions in different fungal species.

Classification of State Trajectories in Gene Regulatory Networks

Gene-expression-based phenotype classification is used for disease diagnosis and prognosis relating to treatment strategies. The present paper considers classification based on sequential measurements of multiple genes using gene regulatory network (GRN) modeling. There are two networks, original and mutated, and observations consist of trajectories of network states. The problem is to classify an observation trajectory as coming from either the original or mutated network. GRNs are modeled via probabilistic Boolean networks, which incorporate stochasticity at both the gene and network levels. Mutation affects the regulatory logic. Classification is based upon observing a trajectory of states of some given length. We characterize the Bayes classifier and find the Bayes error for a general PBN and the special case of a single Boolean network affected by random perturbations (BNp). The Bayes error is related to network sensitivity, meaning the extent of alteration in the steady-state distribution of the original network owing to mutation. Using standard methods to calculate steady-state distributions is cumbersome and sometimes impossible, so we provide an efficient algorithm and approximations. Extensive simulations are performed to study the effects of various factors, including approximation accuracy. We apply the classification procedure to a p53 BNp and a mammalian cell cycle PBN.

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

The Human Cell Atlas

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community.

Loss of NEIL3 DNA glycosylase markedly increases replication associated double strand breaks and enhances sensitivity to ATR inhibitor in glioblastoma cells

DNA endonuclease eight-like glycosylase 3 (NEIL3) is one of the DNA glycosylases that removes oxidized DNA base lesions from single-stranded DNA (ssDNA) and non-B DNA structures. Approximately seven percent of human tumors have an altered NEIL3 gene. However, the role of NEIL3 in replication-associated repair and its impact on modulating treatment response is not known. Here, we report that NEIL3 is localized at the DNA double-strand break (DSB) sites during oxidative DNA damage and replication stress. Loss of NEIL3 significantly increased spontaneous replication-associated DSBs and recruitment of replication protein A (RPA). In contrast, we observed a marked decrease in Rad51 on nascent DNA strands at the replication fork, suggesting that HR-dependent repair is compromised in NEIL3-deficient cells. Interestingly, NEIL3-deficient cells were sensitive to ataxia–telangiectasia and Rad3 related protein (ATR) inhibitor alone or in combination with PARP1 inhibitor. This study elucidates the mechanism by which NEIL3 is critical to overcome oxidative and replication-associated genotoxic stress. Our findings may have important clinical implications to utilize ATR and PARP1 inhibitors to enhance cytotoxicity in tumors that carry altered levels of NEIL3.

MicroRNA-874-mediated inhibition of the major G1/S phase cyclin, CCNE1, is lost in osteosarcomas

The tumor microenvironment is characterized by nutrient-deprived conditions in which the cancer cells have to adapt for survival. Serum starvation resembles the growth factor deprivation characteristic of the poorly vascularized tumor microenvironment and has aided in the discovery of key growth regulatory genes and microRNAs (miRNAs) that have a role in the oncogenic transformation. We report here that miR-874 down-regulates the major G₁/S phase cyclin, cyclin E1 (CCNE1), during serum starvation. Because the adaptation of cancer cells to the tumor microenvironment is vital for subsequent oncogenesis, we tested for miR-874 and CCNE1 interdependence in osteosarcoma cells. We observed that miR-874 inhibits CCNE1 expression in primary osteoblasts, but in aggressive osteosarcomas, miR-874 is down-regulated, leading to elevated CCNE1 expression and appearance of cancer-associated phenotypes. We established that loss of miR-874-mediated control of cyclin E1 is a general feature of osteosarcomas. The down-regulation of CCNE1 by miR-874 is independent of E2F transcription factors. Restoration of miR-874 expression impeded S phase progression, suppressing aggressive growth phenotypes, such as cell invasion, migration, and xenograft tumors, in nude mice. In summary, we report that miR-874 inhibits CCNE1 expression during growth factor deprivation and that miR-874 down-regulation in osteosarcomas leads to CCNE1 up-regulation and more aggressive growth phenotypes.