15: Cell Cycle - Biology

15: Cell Cycle - Biology

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Cells, whether prokaryotic or eukaryotic, eventually reproduce or die.

  • 15.1: The Prokaryotic Cell Cycle
    For prokaryotes, the mechanism of reproduction is relatively simple, since there are no internal organelles. The process consists of three distinct but short phases: first, a growth phase in which the mass of the cell is increased, then the chromosomal replication phase, and finally the chromosomes are separated and the cells are physically split into two independent new cells. In bacteria, these are referred to as the B, C, and D periods, respectively.
  • 15.2: The Eukaryotic Cell Cycle
    Most eukaryotic cells undergo a reproductive cycle to generate either another copy of themselves or to generate gametes (sex cells), and in doing so require a complex mechanism to govern the safe and accurate replication of their much larger (than prokaryote) genomes. Immediately following mitosis, the newly created cells are in the G1 phase. This is largely a growth phase, during which there is a lot of biosynthesis of proteins, lipids, and carbohydrates.
  • 15.3: Controlling the Cell Cycle
    There are three major checkpoints for cell cycle control
  • 15.4: Activation and inactivation of the cyclin-cdk complex
  • 15.5: Pre-mitotic Phases
  • 15.6: Mitosis
    Mitosis consists of prophase, metaphase, anaphase, and telophase, with distinct cellular activities characterizing each phase. This completes the duplication of the nucleus, and is followed by cytokinesis, in which the cell divides to produce two daughter cells.
  • 15.7: Cell Death
    A cell may die either intentionally (usually referred to as apoptosis or programmed cell death, though also once known also as “cellular suicide”), or unintentionally (necrosis). The microscopic observation of these two processes shows strikingly different mechanisms at work. In apoptosis, the cell begins to shrink and lose shape as the cytoskeleton is degraded, then the organelles appear to pack together, except for the nucleus.
  • 15.8: Meiosis
    To maintain the proper number of chromosomes in each generation, the gametes each contribute one set of chromosomes, so that the fertilized egg and all other cells in the organism have two sets of chromosomes — one from each parent. The purpose of meiosis, and its primary difference with mitosis, is not generating daughter cells that are exact replicates, but generating daughter cells that only have half the amount of genetic material as the original cell.

Thumbnail: Life cycle of the cell. (CC BY-SA 4.0; BruceBlaus).

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We used scRNA-seq profiling and functional genomics screens to understand a fundamental difference between the in vitro self-renewal pattern of hNSCs and hGSCs. NSCs display a slower doubling rate due to a slower and variable length transit through G0/G1 even though hNSCs and hGSCs are isolated and grown in the same defined culture conditions. The rest of the cell cycle timing is uniform (as shown in the cell cycle phase time analysis of Fig 6B). By contrast, the GSCs have a uniform transit time through each phase of the cell cycle, including G0/G1, which results in a faster doubling rate. This result is perhaps not surprising given the known roles of oncogenic drivers to effect entry into the cell cycle (Hanahan & Weinberg, 2000 , 2011 ). However, we probed this difference by transcriptionally resolving the NSC cell cycle into seven phases using scRNA-seq: G1, Late G1, S, S/G2, G2/M, M/Early G1, and a quiescence-like state Neural G0. We found that Neural G0 is highly enriched for markers of adult NSC quiescence. Through phenotypic assays and identification of fast growing "G0-skip" mutants, we determined that it is NSCs' ingress into and variable egress out of Neural G0 that determines the length of their cell cycle. Thus, Neural G0 is a transient quiescent state, which is diminished in GSCs in vitro (i.e., grade IV glioma isolates).

The scRNA-seq profiling of NSCs demonstrated that the current gold standard scRNA-seq cell cycle classifier (i.e., ccSeraut) did not adequately account for our de novo cell clusters including, Neural G0. Therefore, we created a new ccAF cell cycle classifier using a neural network-based approach. We validated the classifier by accurately classifying gold standard studies for Neural G0, S, and M phases of the cell cycle. The new classifier better accounts for our hNSCs cell cycle phases as judged by RNA velocity, gene expression vectors, and cyclin/CDK expression. It also better represents cell cycle phases in non-neuroepithelial-derived cell types, including HeLa and 293T cells, where Neural G0 subpopulations are absent. Moreover, ccAF accurately resolved populations of quiescent and activated adult NSCs from scRNA-seq data. The classifier also identified candidate Neural G0 populations among neural progenitors during fetal brain development, which generally diminish during differentiation. Finally, we have made the ccAF classifier available in a variety of useful forms (see Data Availability). Thus, ccAF is a useful tool for scRNA-seq classification of neuroepithelial- and non-neuroepithelial-derived cell types and for identifying novel subpopulations in a variety of biological contexts in actively dividing cell populations.

Application of ccAF to human glioma single-cell and bulk transcriptome profiles also revealed exciting insights into the structure of low- and high-grade glioma tumor populations. First, we again observed that ccAF does a better job at classifying cell cycle subpopulations for glioma than ccSeraut. The ccAF can classify G0/G1 populations into Neural G0, G1, and M/Early G1 across different developmental subtypes. Second, ccAF and Neural G0 expression patterns revealed a general trend that less aggressive grade II and III tumors have higher proportions of Neural G0 categorized cells than grade IV GBMs. Moreover, increased expression of Neural G0 genes was associated with better patient prognosis, negatively correlated with the proliferative state in gliomas, and was independent of tumor grade and IDH1/2 mutation status. Additionally, the Neural G0 state was shown to account for survival variance that is independent from active cell cycling, which means that the Neural G0 state is not simply the antithesis of active cell cycle states. Instead, the Neural G0 state has novel biological mechanisms regulating flow into and out of the G0 state that go beyond the biology of the active cell cycle. These results are consistent with Neural G0 acting as a barrier to progression in low-grade gliomas by promoting a longer pause between cell cycles, which is overcome in secondary gliomas.

In GBM tumors, the Neural G0 subpopulation contained putative glioma stem-like cells (as revealed by the scheme derived from Bhaduri et al, 2020 ), which represent 9.6% of the total tumor population. The mesenchymal subpopulation had the fewest Neural G0 classified cells (

40%), which is still a significant portion. These results are consistent with Neural G0 cells acting as a stem cell reservoir for non-mesenchymal subtypes, while mesenchymal/Neural G0 co-classified cells may capture cells that are in the process of undergoing proneural-to-mesenchymal transitions (Bhat et al, 2013 Halliday et al, 2014 Segerman et al, 2016 ). Future studies are warranted to determine whether the Neural G0 classified subpopulation contains terminally differentiated neoplastic cells, as it is difficult to assess given that tumor driver genes tend to interfere with lineage commitment.

The Neural G0 state is not exclusive to the neuroepithelial lineage (i.e., astrocytes, OPCs, RGs, and glioma cells). Instead, each Neural G0 cell is enriched for a portion, but not all, of the 158 genes present in the hNSCs' Neural G0, which helps distinguish it from G1 and other cell cycle phases. Thus, Neural G0 represents a mixed state that incorporates elements of qNSC and other neural progenitors, which likely results from the multipotency of fetal hNSCs combined with the effects of their ex vivo culture environment. G0-like states for non-neuroectoderm cells might be identified using an alternative set of developmental markers (e.g., Mesoderm G0).

With regard to the function, one possibility is that Neural G0 provides a compartment for the maintenance of neurodevelopmental potential. That is, it could allow time for reinforcing transcriptional and epigenetic programs associated with neurodevelopment gene expression. Consistent with this possibility, Neural G0 genes are up-regulated in quiescent NSCs in vivo and diminished during neural differentiation programs during corticogenesis or by KO of G0-skip genes in CDT + NSCs. Moreover, multiple Neural G0 genes significantly enriched in NSCs and glioma Neural G0 cells are known to help maintain "stemness". For example, HEY1 and TTYH1, are both key players in the Notch signaling pathway in NSCs and help maintain the NSC identity in vivo (Kim et al, 2018 Than-Trong et al, 2018 ). PTN and its target PTPRZ1 also may help promote stemness, signaling, and proliferation of neural progenitors and glioma tumor cells (Fujikawa et al, 2016 , 2017 Zhang et al, 2016b ). Moreover, FABP7 expression and activity have been associated with lipid metabolism in slow-cycling GBM tumor cells (Hoang-Minh et al, 2018 ), consistent with Neural G0 state. Other functions for Neural G0 could include time for repair of DNA lesions that persist from the previous cell cycle (Arora et al, 2017 Barr et al, 2017 ), oxidative stress/mitochondrial maintenance (Mohrin & Chen, 2016 ), or regulation of structural RNAs (e.g., rRNAs, tRNAs) (Roche et al, 2017 ). Future studies will be required to address these and other possibilities.

Lastly, we found that KO of five genes, CREBBP, NF2, PTPN14, TAOK1, or TP53, diminish Neural G0 in vitro in hNSCs. Gene expression changes in G0/G1 populations of KOs confirmed a reduction of Neural G0 genes and characteristic gene expression changes associated with the p53 transcriptional network, Hippo-YAP targets, cell cycle gene regulation, and many novel targets and pathways, including those downstream of CREBBP and TAOK1. Interestingly, in glioma, Hippo-Yap pathway activity has been shown to significantly increase with grade and is associated with shortened patient survival (Orr et al, 2011 Zhang et al, 2016a ). Moreover, proneural tumors exhibit the lower Hippo-Yap pathway activity while mesenchymal tumors, the highest (Orr et al, 2011 Guichet et al, 2018 ). These data fit well with this pathway diminishing Neural G0 gene expression to promote a mesenchymal transition in more aggressive GBM cells (Bhat et al, 2013 Halliday et al, 2014 Segerman et al, 2016 ). However, it is less clear whether p53 would have a similar role in promoting G0-like states in tumors. TP53 is among the most frequently altered genes in lower grade gliomas (26–74%) and in GBM (

30%) tumors (TCGA data cbioportal). There are many examples of p53-independent pathways that regulate G0 ingress/egress in tumor contexts (e.g., Chen et al, 2012 Brown et al, 2017 ). Consistent with this possibility, p27, but not p53-inducible p21, expression is significantly associated with longer-term survival in gliomas (Kirla et al, 2003 ). Thus, in in vitro hNSCs, low-level cellular stresses or DNA damage may trigger partial p53 activation and a transient p21-dependent G0-like state via CDK2 inhibition, as has been reported for other cell types (Spencer et al, 2013 ). Regardless of whether p53 functions in this capacity in vivo, other pathways affecting G0 ingress/egress (e.g., microenvironmental signaling and transcriptional gene network pathways) will ultimately converge on the same set of regulatory events affecting cell cycle engine activity (e.g., raising or lowering CyclinE/A/CDK2 activity). Thus, our results have relevance as a model of G0-like states and Neural G0 gene expression. Further, other G0-skip genes CREBBP, NF2, PTPN14, and TAOK1 function independently of p53 (since they do not affect p53 target genes) and, thus, when mutated attenuate G0 through other mechanisms, including affecting transcription of key cell cycle targets (e.g., CCNA2, CCND1, CDKN2C, and MYC). Future studies will be required to address how these genes and pathways might affect G0-like states in NSCs and tumors.

Collectively, our data reveal Neural G0 is a cellular state shared by multiple neural epithelial-derived stem and progenitor cell types, which likely plays key roles in neurogenesis and glioma tumor development and recurrence.

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