Biology subjects

Tassy, O.

Publications and source records attributed to Tassy, O..

5 recordsLinked to original sources

bioRxiv2025

RNA polymerase II initiation factors show different dynamic behaviour upon induced transcription in live cells

Transcription by RNA polymerase II (Pol II) requires the ordered action of general transcription factors (GTFs) forming the pre-initiation complex (PIC). How these events unfold kinetically remains unclear. Upon transcription activation, we observe coordinated recruitment of Pol II and GTFs together with chromatin decompaction. Pol II and its Ser5-phosphorylated form accumulate and persist at promoters, whereas TFIIB and TFIIF engage transiently, revealing distinct dynamic regimes. We find specific residence kinetics consistent with rapid exchange of GTFs and a more stable initiating Pol II population. A quantitative kinetic model recapitulates the temporal ordering and relative amplitudes of factor recruitment, predicts recruitment times, and links transient GTF engagement to sustained Pol II occupancy. Steady state measurements and transcription inhibition corroborate model predictions. These results uncover a dynamic hierarchy in human PIC assembly and establish a quantitative framework that connects factor exchange kinetics to the regulation of Pol II activity in living cells.

molecular biology↗

bioRxiv2025

Spatiotemporal regulation of cell cycle states within the complex tumor microenvironment

Tumor growth and resistance arise from the interplay between cell-cycle dysregulation and the spatial organization of the tumor microenvironment (TME). While spatial transcriptomics now enables molecular profiling of intact tissues, it captures only static molecular states, making it challenging to reconstruct dynamic processes such as proliferation. Here, we develop SpaceCycle, a computational framework that infers the continuous cell-cycle phase and associated oscillatory gene expression dynamics from spatial transcriptomic data. Using human melanoma, breast, and lung tumors, we map both discrete and continuous cell-cycle states across entire tissue sections to reveal how proliferative activity is spatially structured within the TME. We find that cycling and non-cycling cells form distinct spatial niches reflecting differences in vascularization, immune composition, and cellular density. Continuous-phase inference further exposes tumor-specific variations in cell cycle phase durations and uncovers oscillatory programs. Together, our results provide a spatiotemporal view of cell-cycle organization in human tumors and establish a general framework for detecting dynamic transcriptional programs and spatial proliferation patterns from static tissue data.

systems biology↗

bioRxiv2024

Unraveling the oscillatory dynamics of mRNA metabolism and chromatin accessibility during the cell cycle through integration of single-cell multiomic data

The cell cycle is a tightly regulated process that requires precise temporal expression of hundreds of cell cycledependent genes. However, the genome-wide dynamics of mRNA metabolism throughout the cell cycle remain uncharacterized. Here, we combined single-cell multiome sequencing, biophysical modeling, and deep learning to quantify rates of mRNA transcription, splicing, nuclear export, and degradation. Our approach revealed that both transcriptional and post-transcriptional processes exhibit distinct oscillatory waves at specific cell cycle phases, with post-transcriptional regulation playing a prominent role in shaping mRNA accumulation. We also observed dynamic changes in chromatin accessibility and transcription factor binding footprints, identifying key regulators underlying the oscillatory dynamics of mRNA. Taken together, our approach uncovered a high-resolution map of RNA metabolism dynamics and chromatin accessibility, offering new insights into the temporal control of gene expression in proliferating cells. HighlightsO_LIFourierCycle combines single-cell multiome sequencing, deep learning, and biophysical modeling to quantify gene-specific rates of mRNA metabolism during the cell cycle C_LIO_LIRates of mRNA transcription, nuclear export, and degradation show gene-specific oscillatory waves at distinct cell cycle phases. C_LIO_LIPost-transcriptional regulation, including mRNA degradation and nuclear export, plays a prominent role in shaping mRNA accumulation during the cell cycle C_LIO_LIDynamics of chromatin accessibility and transcription factor binding footprints uncover key regulators underlying the transcriptional control of gene expression C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/575159v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@1d2d315org.highwire.dtl.DTLVardef@2031aaorg.highwire.dtl.DTLVardef@19cc54eorg.highwire.dtl.DTLVardef@15d9105_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗

bioRxiv2017

Multiple inputs ensure yeast cell size homeostasis during cell cycle progression

Coordination of cell growth and division is essential for proper cell function. In budding yeast, although some molecular mechanisms responsible for cell size control during G1 have been elucidated, the mechanism by which cell size homeostasis is established and maintained throughout the cell cycle remains to be discovered. Here, we developed a new technique based on quantification of histone levels to monitor cell cycle progression in individual yeast cells with unprecedented accuracy. Our analysis establishes the existence of a strong mechanism controlling bud size in G2/M that prevents premature entry into mitosis, and contributes significantly to the overall control of size variability during the cell cycle. While most G1/S regulation mutants do not display any strongly impaired size homeostasis, mutants in which B-type cyclin regulation is altered display large cell-to-cell size variability. Our study thus demonstrates that size homeostasis is not controlled by a G1-specific mechanism but is likely to be an emergent property resulting from the integration of several mechanisms, including the control of cyclin B-Cdk activity, that coordinate cell and bud growth with division.

cell biology↗

bioRxiv2017

Recapitulating Early Development Of Mouse Musculoskeletal Precursors Of The Paraxial Mesoderm In Vitro

In vertebrates, body skeletal muscles and axial skeleton derive from the paraxial mesoderm which flanks the neural tube and notochord. The paraxial mesoderm forms in the posterior region of the embryo as presomitic mesoderm (PSM), which generates the embryonic segments called somites. Here, we characterized gene signatures identified using microarray series from the mouse PSM and compared the PSM transcriptome dynamics to that of the developing neural tube. In contrast to the PSM where an abrupt transcriptome reorganisation occurs at the level of the determination front, we show that transcriptome changes are progressive during parallel stages of neural tube differentiation. We show that these early differentiation stages of the paraxial mesoderm can be efficiently recapitulated in monolayer culture in vitro using murine Embryonic Stem (ES) cells. We describe a serum-containing protocol which parallels in vivo tissue maturation allowing differentiation of ES cells towards a paraxial mesoderm fate. We show that R-spondin treatment or Wnt activation alone can induce posterior PSM markers in both mouse and human ES/iPS cells but acquisition of a committed posterior PSM fate requires BMP inhibition to prevent induced cells to drift to a lateral plate mesoderm identity. We show that posterior PSM-like cells induced from mouse ES cells can be further differentiated in vitro to acquire an anterior PSM Pax3-positive identity. When grafted into injured adult muscle, these induced PSM-like precursors generated large numbers of immature muscle fibers. We further show that exposing ES-derived PSM-like cells to a brief FGF inhibition step followed by culture in horse serum-containing medium allows efficient recapitulation of the myogenic program. Differentiating ES cells first produce mononucleated embryonic myocytes and subsequently multinucleated myotubes, as well as Pax7-positive cells. The protocol described here results in improved differentiation and maturation of mouse muscle fibers differentiated in vitro over serum-free protocols. It provides an efficient system for the study of myogenic processes otherwise difficult to study in vivo such as fusion or satellite cell differentiation.

developmental biology↗