Multienzyme interactions of the de novo purine biosynthetic protein PAICS facilitate purinosome formation and metabolic channeling.

There is growing evidence that mammalian cells deploy a mitochondria-associated metabolon called the purinosome to perform channeled de novo purine biosynthesis (DNPB). However, the molecular mechanisms of this substrate-channeling pathway are not well defined. Here, we present molecular evidence of protein-protein interactions (PPIs) between the human bifunctional phosphoribosylaminoimidazole carboxylase/succinocarboxamide synthetase (PAICS) and other known DNPB enzymes. We employed two orthogonal approaches: bimolecular fluorescence complementation, to probe PPIs inside live, intact cells, and co-immunoprecipitation using StrepTag-labeled PAICS that was reintegrated into the genome of PAICS-knockout HeLa cells (crPAICS). With the exception of amidophosphoribosyltransferase, the first enzyme of the DNPB pathway, we discovered PAICS interacts with all other known DNPB enzymes and with MTHFD1, an enzyme which supplies the 10-formyltetrahydrofolate cofactor essential for DNPB. We show these interactions are present in cells grown in both purine-depleted and purine-rich conditions, suggesting at least a partial assembly of these enzymes may be present regardless of the activity of the DNPB pathway. We also demonstrate that tagging of PAICS on its C terminus disrupts these interactions and that this disruption is correlated with disturbed DNPB activity. Finally, we show that crPAICS cells with reintegrated N-terminally tagged PAICS regained effective DNPB with metabolic signatures of channeled synthesis, whereas crPAICS cells that reintegrated C-terminally tagged PAICS exhibit reduced DNPB intermediate pools and a perturbed partitioning of inosine monophosphate into AMP and GMP. Our results provide molecular evidence in support of purinosomes and suggest perturbing PPIs between DNPB enzymes negatively impact metabolite flux through this important pathway.

Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states.

The complexity of gene regulatory networks that lead multipotent cells to acquire different cell fates makes a quantitative understanding of differentiation challenging. Using a statistical framework to analyze single-cell transcriptomics data, we infer the gene expression dynamics of early mouse embryonic stem (mES) cell differentiation, uncovering discrete transitions across nine cell states. We validate the predicted transitions across discrete states using flow cytometry. Moreover, using live-cell microscopy, we show that individual cells undergo abrupt transitions from a naïve to primed pluripotent state. Using the inferred discrete cell states to build a probabilistic model for the underlying gene regulatory network, we further predict and experimentally verify that these states have unique response to perturbations, thus defining them functionally. Our study provides a framework to infer the dynamics of differentiation from single cell transcriptomics data and to build predictive models of the gene regulatory networks that drive the sequence of cell fate decisions during development.

Pluripotency factors in embryonic stem cells regulate differentiation into germ layers.

Cell fate decisions are fundamental for development, but we do not know how transcriptional networks reorganize during the transition from a pluripotent to a differentiated cell state. Here, we asked how mouse embryonic stem cells (ESCs) leave the pluripotent state and choose between germ layer fates. By analyzing the dynamics of the transcriptional circuit that maintains pluripotency, we found that Oct4 and Sox2, proteins that maintain ESC identity, also orchestrate germ layer fate selection. Oct4 suppresses neural ectodermal differentiation and promotes mesendodermal differentiation; Sox2 inhibits mesendodermal differentiation and promotes neural ectodermal differentiation. Differentiation signals continuously and asymmetrically modulate Oct4 and Sox2 protein levels, altering their binding pattern in the genome, and leading to cell fate choice. The same factors that maintain pluripotency thus also integrate external signals and control lineage selection. Our study provides a framework for understanding how complex transcription factor networks control cell fate decisions in progenitor cells.

Glassy dynamics in thermally activated list sorting.

Sorting the integers 1 through N into an ordered list is a simple task that can be done rapidly. However, using an algorithm based on the thermally activated pairwise exchanges of neighboring list elements, we find sorting can display many features of a glass, even for lists as small as N=5. This includes memory and rejuvenation effects during aging-two hallmarks of glassy dynamics that have been difficult to reproduce in standard glass simulations.

Spectral responses in granular compaction.

The slow compaction of a tapped granular packing is reminiscent of the low-temperature dynamics glasses. Here, I study the dynamics of granular compaction by means of a volumetric spectroscopy. While the specific packing volume v displays glassy aging and memory effects at low tapping amplitudes Gamma, the dynamic volumetric susceptibility chi(v)= partial differentialv/ partial differentialGamma displays minimal glassy effects, and its frequency spectrum gives no indication of a rapidly growing time scale. These features are contrast sharply with that found in the dielectric and magnetic susceptibilities of structural and spin glasses. Instead, chi(v) appears to exhibit the behavior of a dynamic configurational specific heat, such as that obtained from computer simulations of spin-glass models. This suggests that the glassy dynamics of granular compaction is controlled by statistically rare processes that diverge from the typical dynamics of the system. From modifications of the dynamical spectrum by finite system size, I suggest that these glassy processes derive from large-scale collective particle rearrangements.

The packing of granular polymer chains.

Rigid particles pack into structures, such as sand dunes on the beach, whose overall stability is determined by the average number of contacts between particles. However, when packing spatially extended objects with flexible shapes, additional concepts must be invoked to understand the stability of the resulting structure. Here, we examine the disordered packing of chains constructed out of flexibly connected hard spheres. Using x-ray tomography, we find that long chains pack into a low-density structure whose mechanical rigidity is mainly provided by the backbone. On compaction, randomly oriented, semi-rigid loops form along the chain, and the packing of chains can be understood as the jamming of these elements. Finally, we uncover close similarities between the packing of chains and the glass transition in polymers.

Myelin figures: the buckling and flow of wet soap.

Myelin figures are interfacial structures formed when certain surfactants swell in excess water. Here, I present data and model calculations suggesting the formation and growth of myelins is due to the fluid flow of surfactant, driven by the hydration gradient at the dry surfactant/water interface; a simple model based on this idea qualitatively reproduces various myelin growth behaviors observed in different experiments. From a detailed experimental observation of how myelins develop from a planar precursor structure, I identify a mechanical instability that may underlie myelin formation. These results indicate the mixed mechanical character of the surfactant lamellar structure, where fluid and elastic properties coexist, is what enables the formation and growth of myelins.

Stability and growth of single myelin figures.

Myelin figures are long thin cylindrical structures that typically grow as a dense tangle when water is added to the concentrated lamellar phase of certain surfactants. We show that, starting from a well-ordered initial state, single myelin figures can be produced in isolation thus allowing a detailed study of their growth and stability. These structures grow with their base at the exposed edges of bilayer stacks from which material is transported into the myelin. Myelins only form and grow in the presence of a driving stress; when the stress is removed, the myelins retract.