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Molina, N.

Publications and source records attributed to Molina, N..

At least 19 recordsLinked to original sources

Comparison of cell-cycle gene expression dynamics and mRNA kinetics across mouse and human pluripotent systems

Cell-cycle remodeling is fundamental to pluripotency and lineage commitment, yet whether its transcriptional and post-transcriptional architecture is conserved across species and developmental states has remained unresolved. Here we introduce Ciclopes, a biology-informed deep-learning framework that resolves continuous cell-cycle phase and phase-dependent mRNA transcription and degradation directly from single-cell RNA sequencing. Applying Ciclopes across six mouse and human pluripotent stem-cell systems spanning naive and primed states, we uncover striking divergence in transcriptional complexity and oscillatory control: mouse systems sustain elevated baseline expression of core cell-cycle regulators, while human systems trade higher baseline expression for larger oscillatory amplitude. Strikingly, mRNA degradation timing remain far more conserved across systems than transcription timing, exposing post-transcriptional regulation as a stable evolutionary backbone. As human iPSCs differentiate into definitive endoderm, cells progressively exit the cell cycle, cell-cycle-coupled gene networks contract, and surviving regulators oscillate with larger amplitude. Ciclopes establishes a general framework for dissecting how pluripotent cells tune proliferation across evolutionary and developmental transitions.

systems biology↗

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↗

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↗

Single-Molecule DNA Footprinting and Transcription Imaging Reveal the Molecular Mechanisms of Promoter Dynamics

Live cell RNA imaging revealed that transcription levels are encoded by the intrinsic dynamics of promoters. However, capturing both kinetic and molecular aspects of promoter fluctuations has been challenging. Here, we resolve this key issue by combining Single Molecule DNA footprinting (SMF) with live transcription imaging. Using HIV-1 as a model, SMF reveals that the promoter functions in two modes depending on the viral transactivator Tat. Without Tat, a nucleosome occupies the core promoter and prevents assembly of the pre-initiation complex. With Tat, this nucleosome is absent while TBP and initiating polymerases are frequently detected. Combining live imaging with SMF provides a mechanistic model of promoter dynamics, which estimates the rates of deposition and removal of promoter nucleosomes (0.7 h-1), TBP binding (0.04 min-1) and polymerase loading (seconds). The data further reveal a kinetic proofreading mechanism of initiating polymerases, which enables Tat to indirectly control promoter nucleosomes by promoting elongation.

molecular biology↗

Androgen receptor imprints satellite cells stemness and preserves their reservoir for lifelong regeneration and optimal repair

Skeletal muscle stem cells (MuSC) are the guardians of muscle regeneration, sustaining tissue integrity through a delicate balance of quiescence, activation, and lineage commitment. While numerous molecular cues have been implicated in regulating these processes, the influence of androgen receptor (AR) signaling, an essential hormonal pathway for male muscle physiology, has remained largely unexplored. Here, we show that AR expression defines quiescent MuSC and acts as a safeguard of their dormancy. Integrated multi-omic analyses reveal a redistribution of AR binding from quiescence-maintenance loci to regulatory elements driving activation and metabolic reprogramming during repair. Loss of AR in young adult mice disrupts this balance, precipitating premature cell-cycle entry, skewed division modalities, depletion of the stem cell reservoir, and destabilization of the niche. These defects converge with hallmarks of aging-associated androgen decline, while androgen supplementation restores regenerative competence. Together, our findings establish AR signaling as a pivotal determinant of MuSC fate and a cornerstone of skeletal muscle homeostasis.

developmental biology↗

Single-molecule chromosome tracing reveals a diversity of megabase heterochromatin domains

Chromosomes fold into distinct domains that regulate transcription, replication, and repair. Beyond well-characterized TADs and compartments, the diversity of heterochromatin domains remains poorly defined at the sequence level. Using single-molecule tracing of nascent heterochromatin in C. elegans, we identify three classes of megabase-scale domains: (i) sharp-boundary, Condensin I-dependent Topological Associating Domain-like domains (TADLs); (ii) similarly sized, but Condensin-independent, elegans Condensin-Independent Domains (elCIDs); and (iii) weaker, diffuse structures that are abundant in the population. TADLs arise early in development, preceding elCIDs, and both become progressively compacted through H3K9 methylation, which promotes intra- and inter-domain proximity. Condensin mutations disrupt TADLs, yet single molecules can still form domain-like structures, as recapitulated by free polymer simulations. However, these differ markedly in boundary positioning and biophysical properties. Our results uncover previously unrecognized heterochromatin architectures and demonstrate that single-molecule analysis and mutational dissection provide valuable approaches for distinguishing between domain types.

genomics↗

Terrigenous inputs link nutrient dynamics to microbial communities in a tropical lagoon

Nutrient availability drives community structure and ecosystem processes, especially in tropical lagoons that are typically oligotrophic but often receive allochthonous inputs from land. Terrestrially-derived nutrients are introduced to tropical lagoons by surface runoff and submarine groundwater discharge, which are influenced by seasonal precipitation. Lagoon habitats are distributed along an onshore-offshore gradient; terrigenous inputs presumably diminish along the same continuum. We characterized nutrient enrichment in the lagoons of a tropical high island, Moorea, French Polynesia, using spatially distributed measurements of nitrogen content in the tissues of a widespread macroalga during the rainy season over four years. We used synoptic water column sampling to identify associations among macroalgal nutrient content and the composition of inorganic macronutrients, dissolved organic matter, and microbial communities. We paired these data with quantifications of land use in nearby watersheds to uncover links between terrestrial factors, aquatic chemistry, and microbial communities. Algal N content was highest near shore and near large, human-impacted watersheds, and lower at offshore sites. Sites with high algal N had water columns with high nitrite + nitrate, silicate, and increased humic organic matter (based on a fluorescence humification index), especially following rain. Microbial communities were differentiated among nearshore habitats and covaried with algal N and water chemistry, supporting the hypothesis that terrigenous nutrient enrichment shapes microbial dynamics in otherwise oligotrophic tropical lagoons. This study reveals that land-sea connections create nutrient subsidies that are important for lagoon biogeochemistry and microbiology, indicating that changes in land use or precipitation will modify ecosystem processes in tropical lagoons.

ecology↗

Biophysical Modeling Uncovers Transcription Factor and Nucleosome Binding on Single DNA Molecules

Gene regulation in eukaryotes emerges from a dynamic interplay between transcription factors (TFs), nucleosomes, and RNA Polymerase II (Pol II), whose competitive and cooperative binding shapes DNA accessibility and transcriptional output. Single-molecule footprinting (SMF) and long-read chromatin accessibility assays such as Fiber-seq now capture these interactions at nucleotide resolution on individual DNA molecules. However, existing computational tools remain insufficient to decode complex binding events from sparse methylation data. Here, we introduce HiddenFoot, a probabilistic modeling framework based on statistical mechanics that quantitatively infers TF, nucleosome, and Pol II occupancy profiles on single DNA molecules by systematically evaluating all thermodynamically plausible binding configurations. Applying HiddenFoot to SMF and Fiber-seq data from mouse, Drosophila, and human cells, we recovered known TF footprints, precisely resolved Pol II pausing, and identified extensive heterogeneity in nucleosome positioning driven by TF binding. HiddenFoot further distinguishes direct TF-TF cooperativity from nucleosome-mediated co-dependency by estimating pairwise interaction energies and comparing to null models under equilibrium. By integrating biophysical modeling with high-resolution single-molecule data, HiddenFoot offers a general, interpretable framework for dissecting regulatory logic in native chromatin with base-pair precision. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=149 SRC="FIGDIR/small/653852v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@46f3b5org.highwire.dtl.DTLVardef@2a2cbdorg.highwire.dtl.DTLVardef@df42f2org.highwire.dtl.DTLVardef@1a4205d_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

Unraveling Enteroendocrine Cell lineage dynamics and associated gene regulatory networks during intestinal development

Enteroendocrine cells (EECs) are rare intestinal epithelial cells producing multiple hormones that regulate essential aspects of digestion and energy. EEC subtypes, their hormone repertoire and differentiation mechanisms from intestinal stem cells have been characterized in the adult intestine. However, although EECs need to be functional from birth, as their absence causes severe intestinal malabsorption in newborns, the mechanisms underlying EEC subtype specification during development are largely unknown. We used mouse embryos, human pluripotent stem cell derived intestinal organoid models and single-cell transcriptomics to characterize EEC lineages and dynamics during development. Our findings demonstrate that in both mice and humans, the majority of EECs are specified during development through similar differentiation trajectories as observed in the adult intestine. This suggests that EEC subtypes specification occurs independently of fully organized crypt-villus structures and stimulation by diet or microbiota. However, the emergence of certain EEC subtypes depends on tissue maturation. Finally, our integrative approach infers lineage-specific regulators dynamically, identifying new candidates controlling EEC differentiation in the developing human gut. HIGHLIGHTSO_LIMost enteroendocrine cells (EECs) are specified during development. C_LIO_LICrypt-villus organization, diet or microbiota are not essential for EEC formation. C_LIO_LIIn pluripotent stem cell derived human intestinal organoids (HIOs), EECs differentiate along 3 main trajectories, one driven by maturation processes. C_LIO_LINovel Gene Regulatory Networks are identified governing human EEC differentiation in HIOs. C_LI

developmental biology↗

Comprehensive 16S rRNA gene sequencing and meta-transcriptomic analyses in female reproductive tract microbiota: Two molecular profiles with different messages

In recent years, high-throughput sequencing technologies have revolutionised reproductive microbiome research. Our understanding of the endometrial microbiome is primarily based on DNA-based 16S rRNA gene profiling, but DNA detection does not imply alive microbe presence. While this method is cost-effective and widely used, it has notable limitations, including the underestimation of microbial diversity, abundance, and functionality, as well as limited species-level resolution. Meta-transcriptomic analysis, an RNA-based approach, addresses these shortcomings by capturing functional transcripts that are actively expressed in living microbes. This study aims to characterize the endometrial microbiota through a dual approach, by integrating 16S rRNA gene sequencing and meta-transcriptomic analyses. By simultaneously analysing microbial composition and gene expression within the female reproductive tract samples, we seek to provide a more comprehensive understanding of its microbiota and their functional potential. A total of 49 women, aged 27-42 years, were enrolled in the study. Vaginal swabs, endometrial brushings, and endometrial biopsy samples were collected from each participant during the mid-secretory menstrual cycle phase, 6-9 days post luteinizing hormone surge. Our findings suggest that in low-microbial-biomass environments like the endometrium, the correlation between 16S rRNA gene sequencing and meta-transcriptomics is relatively weak. This highlights the limitations of microbial analysis of low-microbial-biomass samples. Alternatively, it suggests that microbial functions and genome activity are tissue-specific and dependent on the host tissue environment. Moreover, RNA-based analysis provides higher resolution in detecting certain pathogens, even within the endometrium. In conclusion, our study underscores the need to integrate genomic and transcriptomic data in microbiota studies to better elucidate critical and health-related microbiota-host interactions.

genomics↗

Real-time capture of σN transcription initiation intermediates reveals mechanism of ATPase-driven activation by limited unfolding

Bacterial {sigma} factors bind RNA polymerase (E) to form holoenzyme (E{sigma}), conferring promoter specificity to E and playing a key role in transcription bubble formation. {sigma}N is unique among {sigma} factors in its structure and functional mechanism, requiring activation by specialized AAA+ ATPases. E{sigma}N forms an inactive promoter complex where the N-terminal {sigma}N region I ({sigma}N-RI) threads through a small DNA bubble. On the opposite side of the DNA, the ATPase engages {sigma}N-RI within the pore of its hexameric ring. Here, we perform kinetics-guided structural analysis of de novo formed E{sigma}N initiation complexes and engineer a biochemical assay to measure ATPase-mediated {sigma}N-RI translocation during promoter melting. We show that the ATPase exerts mechanical action to translocate about 30 residues of {sigma}N-RI through the DNA bubble, disrupting inhibitory structures of {sigma}N to allow full transcription bubble formation. A local charge switch of {sigma}N-RI from positive to negative may help facilitate disengagement of the otherwise processive ATPase, allowing subsequent {sigma}N disentanglement from the DNA bubble.

biochemistry↗

Mammalian promoters are characterised by low occupancy and high turnover of RNA polymerase II

The general transcription machinery and its occupancy at promoters are highly conserved across metazoans. This contrasts with the kinetics of mRNA production that considerably differ between model species such as Drosophila and mouse. The molecular basis for these kinetic differences is currently unknown. Here, we used Single Molecule Footprinting to measure RNA Polymerase II (Pol II) occupancy, the fraction of DNA molecules bound, at promoters in mouse and Drosophila cell lines. Single molecule data reveals that Pol II occupancy is on average 3-5 times more frequent at transcriptionally active Drosophila promoters than active mouse promoters. Kinetic modelling of the occupancy states suggests that these differences in Pol II occupancy are determined by the ratio between the transcription initiation and Pol II turnover rates. We used chemical perturbation of transcription initiation to determine Pol II turnover rate in both species. Integration of these data into the model shows that infrequent Pol II occupancy in mammals is explained by the combination of high Pol II turnover and low transcription initiation rates.

genomics↗

Abundant clock proteins point to missing molecular regulation in the plant circadian clock

Understanding the biochemistry behind whole-organism traits such as flowering time is a longstanding challenge, where mathematical models are critical. Very few models of plant gene circuits use the absolute units required for comparison to biochemical data. We refactor two detailed models of the plant circadian clock from relative to absolute units. Using absolute RNA quantification, a simple model predicted abundant clock protein levels in Arabidopsis thaliana, up to 100,000 proteins per cell. NanoLUC reporter protein fusions validated the predicted levels of clock proteins in vivo. Recalibrating the detailed models to these protein levels estimated their DNA-binding dissociation constants (Kd). We estimate the same Kd from multiple results in vitro, extending the method to any promoter sequence. The detailed models simulated the Kd range estimated from LUX DNA-binding in vitro but departed from the data for CCA1 binding, pointing to further circadian mechanisms. Our analytical and experimental methods should transfer to understand other plant gene regulatory networks, potentially including the natural sequence variation that contributes to evolutionary adaptation.

systems biology↗

Early intermediates in bacterial RNA polymerase promoter melting visualized by time-resolved cryo-electron microscopy

During formation of the transcription-competent open complex (RPo) by bacterial RNA polymerases (RNAP), transient intermediates pile up before overcoming a rate-limiting step. Structural descriptions of these interconversions in real time are unavailable. To address this gap, time-resolved cryo-electron microscopy (cryo-EM) was used to capture four intermediates populated 120 or 500 milliseconds (ms) after mixing Escherichia coli {sigma}70-RNAP and the PR promoter. Cryo-EM snapshots revealed the upstream edge of the transcription bubble unpairs rapidly, followed by stepwise insertion of two conserved nontemplate strand (nt-strand) bases into RNAP pockets. As nt-strand "read-out" extends, the RNAP clamp closes, expelling an inhibitory {sigma}70 domain from the active-site cleft. The template strand is fully unpaired by 120 ms but remains dynamic, indicating yet unknown conformational changes load it in subsequent steps. Because these events likely describe DNA opening at many bacterial promoters, this study provides needed insights into how DNA sequence regulates steps of RPo formation.

biophysics↗

Gene-specific RNA homeostasis revealed by perturbation of the NuA4/Tip60 acetyltransferase complex

Transcript buffering entails the reciprocal modulation of mRNA synthesis and degradation rates to maintain stable RNA levels under varying cellular conditions. Current research supports a global, non-sequence-specific connection between mRNA synthesis and degradation, but the underlying mechanisms are still unclear. In this study, we investigated changes in RNA metabolism following acute depletion of TIP60/KAT5, the acetyltransferase subunit of the NuA4 transcriptional coactivator complex, in mouse embryonic stem cells. By combining RNA sequencing of nuclear, cytoplasmic, and newly synthesised transcript fractions with biophysical modelling, we demonstrate that TIP60 predominantly enhances transcription of numerous genes, while a smaller set of genes undergoes TIP60-dependent transcriptional repression. Surprisingly, transcription changes caused by TIP60 depletion were offset by corresponding changes in RNA nuclear export and cytoplasmic stability, indicating gene-specific buffering mechanisms. Similarly, disruption of the unrelated ATAC coactivator complex also resulted in gene-specific transcript buffering. These findings reveal that transcript buffering functions at a gene-specific level and suggest that cells dynamically adjust RNA splicing, export, and degradation in response to individual RNA synthesis alterations, thereby sustaining cellular homeostasis.

genomics↗

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↗

Competition between transcription and loop extrusion modulates promoter and enhancer dynamics

The spatiotemporal configuration of genes with distal regulatory elements, and the impact of chromatin mobility on transcription, remain unclear. Loop extrusion is an attractive model for bringing genetic elements together, but how this functionally interacts with transcription is also largely unknown. We combine live tracking of genomic loci and nascent transcripts with molecular dynamics simulations to assess the 4D arrangement of the Sox2 gene and its enhancer, in response to a battery of perturbations. We find that alterations in chromatin mobility, not promoter-enhancer distance, is more informative about transcriptional status. Active elements display more constrained mobility, consistent with confinement within specialized nuclear sites, and alterations in enhancer mobility distinguish poised from transcribing alleles. Strikingly, we find that whereas loop extrusion and transcription factor-mediated clustering contribute to promoter-enhancer proximity, they have antagonistic effects on chromatin dynamics. This provides an experimental framework for the underappreciated role of chromatin dynamics in genome regulation.

cell biology↗

Characterization of cell-fate decision landscapes by estimating transcription factor dynamics.

Modulation of gene expression during differentiation by transcription factors promotes cell diversity. Despite their role in cell fate decisions, no experimental assays estimate their regulatory activity in a high-throughput manner and at the single-cell resolution. We present FateCompass for identifying lineage-specific transcription factors across differentiation. It uses single-cell transcriptomics data to infer differentiation trajectories and transcription factor activities. We combined a probabilistic framework with RNA velocities or a differentiation potential to estimate transition probabilities and perform stochastic simulations. Also, we learned transcription factor activities using a linear model of gene regulation. Considering dynamic changes and correlations, we identified lineage-specific regulators. We applied FateCompass to an islet cell formation dataset from the mouse embryo, and we found known and novel potential cell-type drivers. Also, when applied to a differentiation protocol dataset towards beta-like cells, we pinpointed undescribed regulators of an off-target population, which were experimentally validated. Thus, as a framework for identifying lineage-specific transcription factors, FateCompass could have implications on hypothesis generation to increase the understanding of the gene regulatory networks driving cell fate choices. HighlightsO_LIWe developed FateCompass, a flexible pipeline to estimate transcription factor activities during cell-fate decision using single-cell RNA seq data. C_LIO_LIFateCompass outlines gene expression stochastic trajectories by infusing the direction of differentiation using RNA velocity or a differentiation potential when RNA velocity fails. C_LIO_LITranscription factor dynamics allow the identification of time-specific regulatory interactions. C_LIO_LIFateCompass predictions revealed known and novel cell-subtype-specific regulators of mouse pancreatic islet cell development. C_LIO_LIDifferential motif analysis predicts lineage-specific regulators of stem cell-derived human {beta}- cells and sheds light on the cellular heterogeneity of {beta}-cell differentiation protocols. C_LIO_LIExperimental validation supports the proposed GRN controlling SC-EC differentiation predicted by FateCompass. C_LI

systems biology↗