104 research outputs found
Mammalian gene expression variability is explained by underlying cell state.
Gene expression variability in mammalian systems plays an important role in physiological and pathophysiological conditions. This variability can come from differential regulation related to cell state (extrinsic) and allele-specific transcriptional bursting (intrinsic). Yet, the relative contribution of these two distinct sources is unknown. Here, we exploit the qualitative difference in the patterns of covariance between these two sources to quantify their relative contributions to expression variance in mammalian cells. Using multiplexed error robust RNA fluorescent in situ hybridization (MERFISH), we measured the multivariate gene expression distribution of 150 genes related to Ca2+ signaling coupled with the dynamic Ca2+ response of live cells to ATP. We show that after controlling for cellular phenotypic states such as size, cell cycle stage, and Ca2+ response to ATP, the remaining variability is effectively at the Poisson limit for most genes. These findings demonstrate that the majority of expression variability results from cell state differences and that the contribution of transcriptional bursting is relatively minimal
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Loci specific epigenetic drug sensitivity.
Therapeutic targeting of epigenetic modulators offers a novel approach to the treatment of multiple diseases. The cellular consequences of chemical compounds that target epigenetic regulators (epi-drugs) are complex. Epi-drugs affect global cellular phenotypes and cause local changes to gene expression due to alteration of a gene chromatin environment. Despite increasing use in the clinic, the mechanisms responsible for cellular changes are unclear. Specifically, to what degree the effects are a result of cell-wide changes or disease related locus specific effects is unknown. Here we developed a platform to systematically and simultaneously investigate the sensitivity of epi-drugs at hundreds of genomic locations by combining DNA barcoding, unique split-pool encoding, and single cell expression measurements. Internal controls are used to isolate locus specific effects separately from any global consequences these drugs have. Using this platform we discovered wide-spread loci specific sensitivities to epi-drugs for three distinct epi-drugs that target histone deacetylase, DNA methylation and bromodomain proteins. By leveraging ENCODE data on chromatin modification, we identified features of chromatin environments that are most likely to be affected by epi-drugs. The measurements of loci specific epi-drugs sensitivities will pave the way to the development of targeted therapy for personalized medicine
Quantitative Modeling in Cell Biology: What Is It Good for?
Recently, there has been a surge in the number of pioneering studies combining experiments with quantitative modeling to explain both relatively simple modules of molecular machinery of the cell and to achieve system-level understanding of cellular networks. Here we discuss the utility and methods of modeling and review several current models of cell signaling, cytoskeletal self-organization, nuclear transport, and the cell cycle. We discuss successes of and barriers to modeling in cell biology and its future directions, and we argue, using the field of bacterial chemotaxis as an example, that the closer the complete systematic understanding of cell behavior is, the more important modeling becomes and the more experiment and theory merge
QuasiMotiFinder: protein annotation by searching for evolutionarily conserved motif-like patterns
Sequence signature databases such as PROSITE, which include amino acid segments that are indicative of a protein's function, are useful for protein annotation. Lamentably, the annotation is not always accurate. A signature may be falsely detected in a protein that does not carry out the associated function (false positive prediction, FP) or may be overlooked in a protein that does carry out the function (false negative prediction, FN). A new approach has emerged in which a signature is replaced with a sequence profile, calculated based on multiple sequence alignment (MSA) of homologous proteins that share the same function. This approach, which is superior to the simple pattern search, essentially searches with the sequence of the query protein against an MSA library. We suggest here an alternative approach, implemented in the QuasiMotiFinder web server (), which is based on a search with an MSA of homologous query proteins against the original PROSITE signatures. The explicit use of the average evolutionary conservation of the signature in the query proteins significantly reduces the rate of FP prediction compared with the simple pattern search. QuasiMotiFinder also has a reduced rate of FN prediction compared with simple pattern searches, since the traditional search for precise signatures has been replaced by a permissive search for signature-like patterns that are physicochemically similar to known signatures. Overall, QuasiMotiFinder and the profile search are comparable to each other in terms of performance. They are also complementary to each other in that signatures that are falsely detected in (or overlooked by) one may be correctly detected by the other
Prometaphase spindle maintenance by an antagonistic motor-dependent force balance made robust by a disassembling lamin-B envelope
The lamin-B nuclear envelope stabilizes spindle microtubules by keeping the competitive motility of opposing-force kinesins in check
Reverse engineering of force integration during mitosis in the Drosophila embryo
The mitotic spindle is a complex macromolecular machine that coordinates accurate chromosome segregation. The spindle accomplishes its function using forces generated by microtubules (MTs) and multiple molecular motors, but how these forces are integrated remains unclear, since the temporal activation profiles and the mechanical characteristics of the relevant motors are largely unknown. Here, we developed a computational search algorithm that uses experimental measurements to ‘reverse engineer' molecular mechanical machines. Our algorithm uses measurements of length time series for wild-type and experimentally perturbed spindles to identify mechanistic models for coordination of the mitotic force generators in Drosophila embryo spindles. The search eliminated thousands of possible models and identified six distinct strategies for MT–motor integration that agree with available data. Many features of these six predicted strategies are conserved, including a persistent kinesin-5-driven sliding filament mechanism combined with the anaphase B-specific inhibition of a kinesin-13 MT depolymerase on spindle poles. Such conserved features allow predictions of force–velocity characteristics and activation–deactivation profiles of key mitotic motors. Identified differences among the six predicted strategies regarding the mechanisms of prometaphase and anaphase spindle elongation suggest future experiments
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Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages.
Macrophages sense pathogens and orchestrate specific immune responses. Stimulus specificity is thought to be achieved through combinatorial and dynamical coding by signaling pathways. While NFκB dynamics are known to encode stimulus information, dynamical coding in other signaling pathways and their combinatorial coordination remain unclear. Here, we established live-cell microscopy to investigate how NFκB and p38 dynamics interface in stimulated macrophages. Information theory and machine learning revealed that p38 dynamics distinguish cytokine TNF from pathogen-associated molecular patterns and high doses from low, but contributed little to information-rich NFκB dynamics when both pathways are considered. This suggests that immune response genes benefit from decoding immune signaling dynamics or combinatorics, but not both. We found that the heterogeneity of the two pathways is surprisingly uncorrelated. Mathematical modeling revealed potential sources of uncorrelated heterogeneity in the branched pathway network topology and predicted it to drive gene expression variability. Indeed, genes dependent on both p38 and NFκB showed high scRNAseq variability and bimodality. These results identify combinatorial signaling as a mechanism to restrict NFκB-AND-p38-responsive inflammatory cytokine expression to few cells
An incoherent feedforward loop interprets NFκB/RelA dynamics to determine TNF-induced necroptosis decisions
Balancing cell death is essential to maintain healthy tissue homeostasis and prevent disease. Tumor necrosis factor (TNF) not only activates nuclear factor κB (NFκB), which coordinates the cellular response to inflammation, but may also trigger necroptosis, a pro-inflammatory form of cell death. Whether TNF-induced NFκB affects the fate decision to undergo TNF-induced necroptosis is unclear. Live-cell microscopy and model-aided analysis of death kinetics identified a molecular circuit that interprets TNF-induced NFκB/RelA dynamics to control necroptosis decisions. Inducible expression of TNFAIP3/A20 forms an incoherent feedforward loop to interfere with the RIPK3-containing necrosome complex and protect a fraction of cells from transient, but not long-term TNF exposure. Furthermore, dysregulated NFκB dynamics often associated with disease diminish TNF-induced necroptosis. Our results suggest that TNF's dual roles in either coordinating cellular responses to inflammation, or further amplifying inflammation are determined by a dynamic NFκB-A20-RIPK3 circuit, that could be targeted to treat inflammation and cancer
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