Functional consequences of a p53-MDM2-p21 incoherent feedforward loop.

Genetically identical cells can respond heterogeneously to cancer therapy, with a subpopulation of cells often entering a temporarily arrested treatment-tolerant state before repopulating the tumor. To investigate how heterogeneity in the cell cycle arrest protein p21 arises, we imaged the dynamics of p21 transcription and protein expression along with those of p53, its transcriptional regulator, in single cells using live cell fluorescence microscopy. Surprisingly, we found that the rate of p21 transcription depends on the change in p53 rather than its absolute level. Through combined theoretical and experimental modeling, we determined that p21 transcription is governed by an incoherent feedforward loop mediated by MDM2. This network architecture facilitates rapid induction of p21 expression and variability in p21 transcription. Abrogating the feedforward loop overcomes rapid S-phase p21 degradation, with cells transitioning into a quiescent state that transcriptionally resembles a treatment-tolerant persister state. Our findings have important implications for therapeutic strategies based on activating p53.

MSModDetector: a tool for detecting mass shifts and post-translational modifications in individual ion mass spectrometry data.

MOTIVATION: Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs on the same protein molecule, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even PTMs at distant sites to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. RESULTS: We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/marjanfaizi/MSModDetector.

Comparison of TP53 Mutations in Myelodysplasia and Acute Leukemia Suggests Divergent Roles in Initiation and Progression.

TP53 mutation predicts adverse prognosis in many cancers, including myeloid neoplasms, but the mechanisms by which specific mutations impact disease biology, and whether they differ between disease categories, remain unknown. We analyzed TP53 mutations in four myeloid neoplasm subtypes (MDS, AML, AML with myelodysplasia-related changes (AML-MRC), and therapy-related acute myeloid leukemia (tAML)), and identified differences in mutation types, spectrum, and hotspots between disease categories and compared to solid tumors. Missense mutations in the DNA-binding domain were most common across all categories, whereas inactivating mutations and mutations outside the DNA binding domain were more common in AML-MRC compared to MDS. TP53 mutations in MDS were more likely to retain transcriptional activity, and co-mutation profiles were distinct between disease categories and mutation types. Our findings suggest that mutated TP53 contributes to initiation and progression of neoplasia via distinct mechanisms, and support the utility of specific identification of TP53 mutations in myeloid malignancies.

The mammalian midbody and midbody remnant are assembly sites for RNA and localized translation.

Long ignored as a vestigial remnant of cytokinesis, the mammalian midbody (MB) is released post-abscission inside large extracellular vesicles called MB remnants (MBRs). Recent evidence suggests that MBRs can modulate cell proliferation and cell fate decisions. Here, we demonstrate that the MB matrix is the site of ribonucleoprotein assembly and is enriched in mRNAs that encode proteins involved in cell fate, oncogenesis, and pluripotency, which we are calling the MB granule. Both MBs and post-abscission MBRs are sites of spatiotemporally regulated translation, which is initiated when nascent daughter cells re-enter G1 and continues after extracellular release. MKLP1 and ARC are necessary for the localization and translation of RNA in the MB dark zone, whereas ESCRT-III is necessary to maintain translation levels in the MB. Our work reveals a unique translation event that occurs during abscission and within a large extracellular vesicle.

MSModDetector: A Tool for Detecting Mass Shifts and Post-Translational Modifications in Individual Ion Mass Spectrometry Data.

Motivation: Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even widely separated PTMs to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. Results: We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I MS) data. I MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I MS data and experimental I MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. Availability: The source code is available at https://github.com/marjanfaizi/MSModDetector together with the scripts used for analyses and to generate the figures presented in this study.

Multi-range ERK responses shape the proliferative trajectory of single cells following oncogene induction.

Oncogene-induced senescence is a phenomenon in which aberrant oncogene expression causes non-transformed cells to enter a non-proliferative state. Cells undergoing oncogenic induction display phenotypic heterogeneity, with some cells senescing and others remaining proliferative. The causes of heterogeneity remain unclear. We studied the sources of heterogeneity in the responses of human epithelial cells to oncogenic BRAFV600E expression. We found that a narrow expression range of BRAFV600E generated a wide range of activities of its downstream effector ERK. In population-level and single-cell assays, ERK activity displayed a non-monotonic relationship to proliferation, with intermediate ERK activities leading to maximal proliferation. We profiled gene expression across a range of ERK activities over time and characterized four distinct ERK response classes, which we propose act in concert to generate the ERK-proliferation response. Altogether, our studies map the input-output relationships between ERK activity and proliferation, elucidating how heterogeneity can be generated during oncogene induction.

Principles, mechanisms and functions of entrainment in biological oscillators.

Entrainment is a phenomenon in which two oscillators interact with each other, typically through physical or chemical means, to synchronize their oscillations. This phenomenon occurs in biology to coordinate processes from the molecular to organismal scale. Biological oscillators can be entrained within a single cell, between cells or to an external input. Using six illustrative examples of entrainable biological oscillators, we discuss the distinctions between entrainment and synchrony and explore features that contribute to a system's propensity to entrain. Entrainment can either enhance or reduce the heterogeneity of oscillations within a cell population, and we provide examples and mechanisms of each case. Finally, we discuss the known functions of entrainment and discuss potential functions from an evolutionary perspective.

Louder for longer: Myc amplifies gene expression by extended transcriptional bursting.

Transcription is a complex, dynamic process. Using live single-cell measurements, Patange et al. show, in a recent issue of Cell Reports, that elevated levels of the transcription factor MYC enhance target gene RNA production by increasing the duration but not frequency of transcriptional bursts.

Time-series transcriptomics and proteomics reveal alternative modes to decode p53 oscillations.

The cell stress-responsive transcription factor p53 influences the expression of its target genes and subsequent cellular responses based in part on its dynamics (changes in level over time). The mechanisms decoding p53 dynamics into subsequent target mRNA and protein dynamics remain unclear. We systematically quantified p53 target mRNA and protein expression over time under two p53 dynamical regimes, oscillatory and rising, using RNA-sequencing and TMT mass spectrometry. Oscillatory dynamics allowed for a greater variety of dynamical patterns for both mRNAs and proteins. Mathematical modeling of empirical data revealed three distinct mechanisms that decode p53 dynamics. Specific combinations of these mechanisms at the transcriptional and post-transcriptional levels enabled exclusive induction of proteins under particular dynamics. In addition, rising induction of p53 led to higher induction of proteins regardless of their functional class, including proteins promoting arrest of proliferation, the primary cellular outcome under rising p53. Our results highlight the diverse mechanisms cells employ to distinguish complex transcription factor dynamics to regulate gene expression.

Chromatin-state barriers enforce an irreversible mammalian cell fate decision.

Stem and progenitor cells have the capacity to balance self-renewal and differentiation. Hematopoietic myeloid progenitors replenish more than 25 billion terminally differentiated neutrophils every day under homeostatic conditions and can increase this output in response to stress or infection. At what point along the spectrum of maturation do progenitors lose capacity for self-renewal and become irreversibly committed to differentiation? Using a system of conditional myeloid development that can be toggled between self-renewal and differentiation, we interrogate determinants of this "point of no return" in differentiation commitment. Irreversible commitment is due primarily to loss of open regulatory site access and disruption of a positive feedback transcription factor activation loop. Restoration of the transcription factor feedback loop extends the window of cell plasticity and alters the point of no return. These findings demonstrate how the chromatin state enforces and perpetuates cell fate and identify potential avenues for manipulating cell identity.

Combined epigenetic and metabolic treatments overcome differentiation blockade in acute myeloid leukemia.

A hallmark of acute myeloid leukemia (AML) is the inability of self-renewing malignant cells to mature into a non-dividing terminally differentiated state. This differentiation block has been linked to dysregulation of multiple cellular processes, including transcriptional, chromatin, and metabolic regulation. The transcription factor HOXA9 and the histone demethylase LSD1 are examples of such regulators that promote differentiation blockade in AML. To identify metabolic targets that interact with LSD1 inhibition to promote myeloid maturation, we screened a small molecule library to identify druggable substrates. We found that differentiation caused by LSD1 inhibition is enhanced by combined perturbation of purine nucleotide salvage and de novo lipogenesis pathways, and identified multiple lines of evidence to support the specificity of these pathways and suggest a potential basis of how perturbation of these pathways may interact synergistically to promote myeloid differentiation. In sum, these findings suggest potential drug combination strategies in the treatment of AML.

p53 dynamics vary between tissues and are linked with radiation sensitivity.

Radiation sensitivity varies greatly between tissues. The transcription factor p53 mediates the response to radiation; however, the abundance of p53 protein does not correlate well with the extent of radiosensitivity across tissues. Given recent studies showing that the temporal dynamics of p53 influence the fate of cultured cells in response to irradiation, we set out to determine the dynamic behavior of p53 and its impact on radiation sensitivity in vivo. We find that radiosensitive tissues show prolonged p53 signaling after radiation, while more resistant tissues show transient p53 activation. Sustaining p53 using a small molecule (NMI801) that inhibits Mdm2, a negative regulator of p53, reduced viability in cell culture and suppressed tumor growth. Our work proposes a mechanism for the control of radiation sensitivity and suggests tools to alter the dynamics of p53 to enhance tumor clearance. Similar approaches can be used to enhance killing of cancer cells or reduce toxicity in normal tissues following genotoxic therapies.

Connecting Timescales in Biology: Can Early Dynamical Measurements Predict Long-Term Outcomes?

Prediction of long-term outcomes from short-term measurements remains a fundamental challenge. Quantitative assessment of signaling dynamics, and the resulting transcriptomic and proteomic responses, has yielded fundamental insights into cellular outcomes. However, the utility of these measurements is limited by their short timescale (hours to days), while the consequences of these events frequently unfold over longer timescales. Here, we discuss the predictive power of static and dynamic measurements, drawing examples from fields that have harnessed the predictive capabilities of such measurements. We then explore potential approaches to close this timescale gap using complementary measurements and computational approaches, focusing on the example of dynamic measurements of signaling factors and their impacts on cellular outcomes.

A Switch in p53 Dynamics Marks Cells That Escape from DSB-Induced Cell Cycle Arrest.

Cellular responses to stimuli can evolve over time, resulting in distinct early and late phases in response to a single signal. DNA damage induces a complex response that is largely orchestrated by the transcription factor p53, whose dynamics influence whether a damaged cell will arrest and repair the damage or will initiate cell death. How p53 responses and cellular outcomes evolve in the presence of continuous DNA damage remains unknown. Here, we have found that a subset of cells switches from oscillating to sustained p53 dynamics several days after undergoing damage. The switch results from cell cycle progression in the presence of damaged DNA, which activates the caspase-2-PIDDosome, a complex that stabilizes p53 by inactivating its negative regulator MDM2. This work defines a molecular pathway that is activated if the canonical checkpoints fail to halt mitosis in the presence of damaged DNA.

Quantifying the Central Dogma in the p53 Pathway in Live Single Cells.

Transcription factors (TFs) integrate signals to regulate target gene expression, but we generally lack a quantitative understanding of how changes in TF levels regulate mRNA and protein production. Here, we established a system to simultaneously monitor the levels of p53, a TF that shows oscillations following DNA damage, and the transcription and protein levels of its target p21 in individual cells. p21 transcription tracked p53 dynamics, while p21 protein steadily accumulated. p21 transcriptional activation showed bursts of mRNA production, with p53 levels regulating the probability but not magnitude of activation. Variations in p53 levels between cells contributed to heterogeneous p21 transcription while independent p21 alleles exhibited highly correlated behaviors. Pharmacologically elevating p53 increased the probability of p21 transcription with minor effects on its magnitude, leading to a strong increase in p21 protein levels. Our results reveal quantitative mechanisms by which TF dynamics can regulate protein levels of its targets. A record of this paper's transparent peer review process is included in the Supplemental Information.

The effects of proliferation status and cell cycle phase on the responses of single cells to chemotherapy.

DNA-damaging chemotherapeutics are widely used in cancer treatments, but for solid tumors they often leave a residual tumor-cell population. Here we investigated how cellular states might affect the response of individual cells in a clonal population to cisplatin, a DNA-damaging chemotherapeutic agent. Using a live-cell reporter of cell cycle phase and long-term imaging, we monitored single-cell proliferation before, at the time of, and after treatment. We found that in response to cisplatin, cells either arrested or died, and the ratio of these outcomes depended on the dose. While we found that the cell cycle phase at the time of cisplatin addition was not predictive of outcome, the proliferative history of the cell was: highly proliferative cells were more likely to arrest than to die, whereas slowly proliferating cells showed a higher probability of death. Information theory analysis revealed that the dose of cisplatin had the greatest influence on the cells' decisions to arrest or die, and that the proliferation status interacted with the cisplatin dose to further guide this decision. These results show an unexpected effect of proliferation status in regulating responses to cisplatin and suggest that slowly proliferating cells within tumors may be acutely vulnerable to chemotherapy.

Author Correction: Roles and regulation of histone methylation in animal development.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.