Transgenerational transcriptional heterogeneity from cytoplasmic chromatin

Transcriptional heterogeneity from plasticity of the epigenetic state of chromatin is thought to contribute to tumor evolution, metastasis, and drug resistance. However, the mechanisms leading to nongenetic cell-to-cell variation in gene expression remain poorly understood. Here we demonstrate that heritable transcriptional changes can result from the formation of micronuclei, aberrations of the nucleus that are common in cancer. Micronuclei have fragile nuclear envelopes (NE) that are prone to spontaneous rupture, which exposes chromosomes to the cytoplasm and disrupts many nuclear activities. Using a combination of long-term live-cell imaging and same-cell, single-cell RNA sequencing (Look-Seq2), we identified significant reduction of gene expression in micronuclei, both before and after NE rupture. Furthermore, chromosomes in micronuclei fail to normally recover histone 3 lysine 27 acetylation, a critical step for the reestablishment of normal transcription after mitosis. These transcription and chromatin defects can persist into the next generation in a subset of cells, even after these chromosomes are incorporated into normal daughter nuclei. Moreover, persistent transcriptional repression is strongly associated with, and may be explained by, surprisingly long-lived DNA damage to these reincorporated chromosomes. Therefore, heritable alterations in transcription can originate from aberrations of nuclear architecture.

Noise in a metabolic pathway leads to persister formation in Mycobacterium tuberculosis

Tuberculosis is difficult to treat due to dormant cells in hypoxic granulomas, and stochastically-formed persisters tolerant of antibiotics. Bactericidal antibiotics kill by corrupting their energy-dependent targets. We reasoned that noise in the expression of an energy-generating component will produce rare persister cells. In sorted low ATP M. tuberculosis grown on acetate there is considerable cell-to-cell variation in the level of mRNA coding for AckA, the acetate kinase. Quenching the noise by overexpressing ackA sharply decreases persisters, showing that it acts as the main persister gene under these conditions. This demonstrates that a low energy mechanism is responsible for the formation of M. tuberculosis persisters and suggests that the mechanism of their antibiotic tolerance is similar to that of dormant cells in a granuloma. Entrance into a low energy state driven by stochastic variation in expression of energy-producing enzymes is likely a general mechanism by which bacteria produce persisters.

A precisely adjustable, variation-suppressed eukaryotic transcriptional controller to enable genetic discovery

Conditional expression of genes and observation of phenotype remain central to biological discovery. Current methods enable either on/off or imprecisely controlled graded gene expression. We developed a 'well-tempered' controller, WTC846, for precisely adjustable, graded, growth condition independent expression of genes in Saccharomyces cerevisiae. Controlled genes are expressed from a strong semisynthetic promoter repressed by the prokaryotic TetR, which also represses its own synthesis; with basal expression abolished by a second, 'zeroing' repressor. The autorepression loop lowers cell-to-cell variation while enabling precise adjustment of protein expression by a chemical inducer. WTC846 allelic strains in which the controller replaced the native promoters recapitulated known null phenotypes (CDC42, TPI1), exhibited novel overexpression phenotypes (IPL1), showed protein dosage-dependent growth rates and morphological phenotypes (CDC28, TOR2, PMA1 and the hitherto uncharacterized PBR1), and enabled cell cycle synchronization (CDC20). WTC846 defines an 'expression clamp' allowing protein dosage to be adjusted by the experimenter across the range of cellular protein abundances, with limited variation around the setpoint.

Rapid signaling reactivation after targeted BRAF inhibition predicts the proliferation of individual melanoma cells from an isogenic population

Cancer cells within tumors display a high degree of phenotypic variability. This variability is thought to allow some of the cells to survive and persist after seemingly effective drug treatments. Studies on vemurafenib, a signaling inhibitor that targets an oncogenic BRAF mutation common in melanoma, suggested that cell-to-cell variation in drug resistance, measured by long-term proliferation, originates from epigenetic differences in gene expression that pre-exist treatment. However, it is still unknown whether reactivation of signaling downstream to the inhibited BRAF, thought to be a key step for resistance, is heterogeneous across cells. While previous studies established that signaling reactivation takes place many hours to days after treatment, they monitored reactivation with bulk-population assays unsuitable for detecting cell-to-cell heterogeneity. We hypothesized that signaling reactivation is heterogeneous and is almost instantaneous for a small subpopulation of resistant cells. We tested this hypothesis by monitoring signaling dynamics at a single-cell resolution and observed that despite highly uniform initial inhibition, roughly 15% of cells reactivated signaling within an hour of treatment. Moreover, by tracking cell lineages over multiple days, we established that these cells indeed proliferated more than neighboring cells, thus establishing that rapid signaling reactivation predicts long-term vemurafenib resistance.

Live-Cell Imaging of (p)ppGpp with RNA-based Fluorescent Sensors

Guanosine tetra- and pentaphosphate, (p)ppGpp, are important alarmone nucleotides that regulate bacterial survival in stressful environment. A direct detection of (p)ppGpp in living cells is critical for our understanding of the mechanism of bacterial stringent response. However, it is still challenging to directly image and measure cellular (p)ppGpp. Here, we report a type of RNA-based fluorescent sensors for live-cell imaging of (p)ppGpp. Our sensor is engineered by conjugating a recently identified (p)ppGpp-specific riboswitch with a fluorogenic RNA aptamer, Broccoli. These sensors can be genetically encoded and enable direct monitoring of cellular (p)ppGpp accumulation. Unprecedented information on cell-to-cell variation and cellular dynamics of (p)ppGpp levels can now be obtained under different nutritional conditions. We predict that these RNA-based sensors will be broadly adapted to study bacterial stringent response.

Delineating the heterogeneity of matrix-directed differentiation toward soft and stiff tissue lineages via single-cell profiling

Mesenchymal stromal/stem cells (MSCs) form a heterogeneous population of multipotent progenitors that contribute to tissue regeneration and homeostasis. MSCs assess extracellular elasticity by probing resistance to applied forces via adhesion, cytoskeletal, and nuclear mechanotransducers that direct differentiation toward soft or stiff tissue lineages. Even under controlled culture conditions, MSC differentiation exhibits substantial cell-to-cell variation that remains poorly characterized. By single-cell transcriptional profiling of nonconditioned, matrix-conditioned, and early differentiating cells, we identified distinct MSC subpopulations with distinct mechanosensitivities, differentiation capacities, and cell cycling. We show that soft matrices support adipogenesis of multipotent cells and early endochondral ossification of nonadipogenic cells, whereas intramembranous ossification and preosteoblast proliferation are directed by stiff matrices. Using diffusion pseudotime mapping, we outline hierarchical matrix-directed differentiation and perform whole-genome screening of mechanoresponsive genes. Specifically, top-ranked tropomyosin-1 is highly sensitive to stiffness cues both at RNA and protein levels, and changes in TPM1 expression determine the differentiation toward soft versus stiff tissue lineage. Consistent with actin stress fiber stabilization, tropomyosin-1 overexpression maintains YAP1 nuclear localization, activates YAP1 target genes, and directs osteogenic differentiation. Knockdown of tropomyosin-1 reversed YAP1 nuclear localization consistent with relaxation of cellular contractility, suppressed osteogenesis, activated early endochondral ossification genes after 3 d of culture in induction medium, and facilitated adipogenic differentiation after 1 wk. Our results delineate cell-to-cell variation of matrix-directed MSC differentiation and highlight tropomyosin-mediated matrix sensing.

Hematopoietic differentiation is characterized by a transient peak of cell-to-cell gene expression variability in normal and pathological conditions

Hematopoietic differentiation has been considered as a multistep process which is metaphorically represented as linear trajectories with discrete steps from hematopoietic stem cells to mature cells. While the transcriptional state of cells at the beginning or at the end of these trajectories are relatively well described from bulk analysis, what happens in the intermediate states has remained elusive until the use of single cell approaches allowed to capture the dynamic changes of transcriptomic states.Applying Shannon entropy to measure cell-to-cell variability among cells at the same stage of differentiation, we observed a transient peak of gene expression variability in all the hematopoietic differentiation pathways. Strikingly, genes with the highest entropy variation in a given differentiation pathway matched genes known as pathway-specific, whereas genes with the highest expression variation were common to all pathways. Finally, we showed that the level of cell-to-cell variation is increased in the most immature compartment of hematopoiesis in myelodysplastic syndromes.These data suggest that differentiation may not be as deterministic and linear as previously thought, but could be better conceptualized as a dynamical stochastic process with a transient stage of cellular indetermination.

Sphingolipid Control of Fibroblast Heterogeneity Revealed by Single-Cell Lipidomics

Human cells produce thousands of lipids that impact a wide range of biological processes in ways we are only starting to characterize. The cellular composition in lipids changes during differentiation events and also varies across individual cells of the same type. Yet, the precise differences in lipid composition that directly affect cell phenotypes remain unknown. Here we have measured the lipidomes and transcriptomes of individual human dermal fibroblasts by coupling high-resolution mass spectrometry imaging to single-cell transcriptomics. We found that the cell-to-cell variation of specific lipid metabolic pathways contributes to the establishment of cell states involved in wound repair and in skin cancer growth. Sphingolipid composition defined fibroblast subpopulations while sphingolipid metabolic rewiring drove cell state transitions. These data uncover a role for cell-to-cell lipid heterogeneity in the determination of cell states and reveal a new regulatory component to the homeostasis and self-organization of multicellular systems.