Partitioning of crystalline and amorphous phases during freezing of simulated Enceladus ocean fluids

This work was supported by The Leverhulme Trust (grant number RPG‐2016‐153).Saturn's ice‐covered moon Enceladus may contain the requisite conditions for life. Its potentially habitable subsurface ocean is vented into space as large cryovolcanic plumes that can be sampled by spacecraft, acting as a window to the ocean below. However, little is known about how Enceladus’ ocean fluids evolve as they freeze. Using cryo‐imaging techniques, we investigated solid phases produced by freezing simulated Enceladean ocean fluids at endmember cooling rates. Our results show that under flash‐freezing conditions (>10 K s−1), Enceladus‐relevant fluids undergo segregation, whereby the precipitation of ice templates the formation of brine vein networks. The high solute concentrations and confined nature of these brine veins means that salt crystallization is kinetically inhibited and glass formation (vitrification) can occur at lower cooling rates than typically required for vitrification of a bulk solution. Crystalline salts also form if flash‐frozen fluids are re‐warmed. The 10 µm‐scale distribution of salt phases produced by this mechanism differs markedly from that of gradually cooled (∼1 K min−1) fluids, showing that they inherit a textural signature of their formation conditions. The mineralogy of cryogenic carbonates can be used as a probe for cooling rate and parent fluid pH. Our findings reveal possible endmember routes for solid phase production from Enceladus’ ocean fluids and mechanisms for generating compositional heterogeneity within ice particles on a sub‐10 µm scale. This has implications for understanding how Enceladus' ocean constituents are incorporated into icy particles and delivered to space.Publisher PDFPeer reviewe

A scalable SCENIC workflow for single-cell gene regulatory network analysis

SCENIC is a computational pipeline to predict cell-type-specific transcription factors through network inference and motif enrichment. Here the authors describe a detailed protocol for pySCENIC: a faster, container-based implementation in Python. This protocol explains how to perform a fast SCENIC analysis alongside standard best practices steps on single-cell RNA-sequencing data using software containers and Nextflow pipelines. SCENIC reconstructs regulons (i.e., transcription factors and their target genes) assesses the activity of these discovered regulons in individual cells and uses these cellular activity patterns to find meaningful clusters of cells. Here we present an improved version of SCENIC with several advances. SCENIC has been refactored and reimplemented in Python (pySCENIC), resulting in a tenfold increase in speed, and has been packaged into containers for ease of use. It is now also possible to use epigenomic track databases, as well as motifs, to refine regulons. In this protocol, we explain the different steps of SCENIC: the workflow starts from the count matrix depicting the gene abundances for all cells and consists of three stages. First, coexpression modules are inferred using a regression per-target approach (GRNBoost2). Next, the indirect targets are pruned from these modules using cis-regulatory motif discovery (cisTarget). Lastly, the activity of these regulons is quantified via an enrichment score for the regulon's target genes (AUCell). Nonlinear projection methods can be used to display visual groupings of cells based on the cellular activity patterns of these regulons. The results can be exported as a loom file and visualized in the SCope web application. This protocol is illustrated on two use cases: a peripheral blood mononuclear cell data set and a panel of single-cell RNA-sequencing cancer experiments. For a data set of 10,000 genes and 50,000 cells, the pipeline runs in <2 h

Cohesin loss alters adult hematopoietic stem cell homeostasis, leading to myeloproliferative neoplasms

The cohesin complex (consisting of Rad21, Smc1a, Smc3, and Stag2 proteins) is critically important for proper sister chromatid separation during mitosis. Mutations in the cohesin complex were recently identified in a variety of human malignancies including acute myeloid leukemia (AML). To address the potential tumor-suppressive function of cohesin in vivo, we generated a series of shRNA mouse models in which endogenous cohesin can be silenced inducibly. Notably, silencing of cohesin complex members did not have a deleterious effect on cell viability. Furthermore, knockdown of cohesin led to gain of replating capacity of mouse hematopoietic progenitor cells. However, cohesin silencing in vivo rapidly altered stem cells homeostasis and myelopoiesis. Likewise, we found widespread changes in chromatin accessibility and expression of genes involved in myelomonocytic maturation and differentiation. Finally, aged cohesin knockdown mice developed a clinical picture closely resembling myeloproliferative disorders/neoplasms (MPNs), including varying degrees of extramedullary hematopoiesis (myeloid metaplasia) and splenomegaly. Our results represent the first successful demonstration of a tumor suppressor function for the cohesin complex, while also confirming that cohesin mutations occur as an early event in leukemogenesis, facilitating the potential development of a myeloid malignancy