The glomerular circadian clock temporally regulates basement membrane dynamics and the podocyte glucocorticoid response.

Kidney physiology shows diurnal variation, and a disrupted circadian rhythm is associated with kidney disease. However, it remains largely unknown whether glomeruli, the filtering units in the kidney, are under circadian control. Here, we investigated core circadian clock components in glomeruli, together with their rhythmic targets and modes of regulation.

Rapid functional impairment of natural killer cells following tumor entry limits anti-tumor immunity.

Immune cell dysfunction within the tumor microenvironment (TME) undermines the control of cancer progression. Established tumors contain phenotypically distinct, tumor-specific natural killer (NK) cells; however, the temporal dynamics, mechanistic underpinning and functional significance of the NK cell compartment remains incompletely understood. Here, we use photo-labeling, combined with longitudinal transcriptomic and cellular analyses, to interrogate the fate of intratumoral NK cells.

CD82 expression marks the endothelium to hematopoietic transition at the onset of blood specification in human.

During embryonic development, all blood progenitors are initially generated from endothelial cells that acquire a hemogenic potential. Blood progenitors emerge through an endothelial-to-hematopoietic transition regulated by the transcription factor RUNX1. To date, we still know very little about the molecular characteristics of hemogenic endothelium and the molecular changes underlying the transition from endothelium to hematopoiesis.

Pro- and anti-tumour activities of CD146/MCAM in breast cancer result from its heterogeneous expression and association with epithelial to mesenchymal transition.

CD146, also known as melanoma cell adhesion molecule (MCAM), is expressed in numerous cancers and has been implicated in the regulation of metastasis. We show that CD146 negatively regulates transendothelial migration (TEM) in breast cancer. This inhibitory activity is reflected by a reduction in MCAM gene expression and increased promoter methylation in tumour tissue compared to normal breast tissue.

Reciprocal transcription factor networks govern tissue-resident ILC3 subset function and identity.

Innate lymphoid cells (ILCs) are guardians of mucosal immunity, yet the transcriptional networks that support their function remain poorly understood. We used inducible combinatorial deletion of key transcription factors (TFs) required for ILC development (RORγt, RORα and T-bet) to determine their necessity in maintaining ILC3 identity and function. Both RORγt and RORα were required to preserve optimum effector functions; however, RORα was sufficient to support robust interleukin-22 production among the lymphoid tissue inducer (LTi)-like ILC3 subset, but not natural cytotoxicity receptor (NCR) ILC3s.

Murine AGM single-cell profiling identifies a continuum of hemogenic endothelium differentiation marked by ACE.

In vitro generation and expansion of hematopoietic stem cells (HSCs) holds great promise for the treatment of any ailment that relies on bone marrow or blood transplantation. To achieve this, it is essential to resolve the molecular and cellular pathways that govern HSC formation in the embryo. HSCs first emerge in the aorta-gonad-mesonephros (AGM) region, where a rare subset of endothelial cells, hemogenic endothelium (HE), undergoes an endothelial-to-hematopoietic transition (EHT).

Foxm1 regulates neural progenitor fate during spinal cord regeneration.

Xenopus tadpoles have the ability to regenerate their tails upon amputation. Although some of the molecular and cellular mechanisms that globally regulate tail regeneration have been characterised, tissue-specific response to injury remains poorly understood. Using a combination of bulk and single-cell RNA sequencing on isolated spinal cords before and after amputation, we identify a number of genes specifically expressed in the spinal cord during regeneration.

HOX paralogs selectively convert binding of ubiquitous transcription factors into tissue-specific patterns of enhancer activation.

Gene expression programs determine cell fate in embryonic development and their dysregulation results in disease. Transcription factors (TFs) control gene expression by binding to enhancers, but how TFs select and activate their target enhancers is still unclear. HOX TFs share conserved homeodomains with highly similar sequence recognition properties, yet they impart the identity of different animal body parts.

Chronic myelomonocytic leukaemia stem cell transcriptomes anticipate disease morphology and outcome.

Background: Chronic myelomonocytic leukaemia (CMML) is a clinically heterogeneous stem cell malignancy with overlapping features of myelodysplasia and myeloproliferation. Over 90% of patients carry mutations in epigenetic and/or splicing genes, typically detectable in the LinCD34CD38 immunophenotypic stem cell compartment in which the leukaemia-initiating cells reside. Transcriptional dysregulation at the stem cell level is likely fundamental to disease onset and progression.

Classifying cells with Scasat, a single-cell ATAC-seq analysis tool.

ATAC-seq is a recently developed method to identify the areas of open chromatin in a cell. These regions usually correspond to active regulatory elements and their location profile is unique to a given cell type. When done at single-cell resolution, ATAC-seq provides an insight into the cell-to-cell variability that emerges from otherwise identical DNA sequences by identifying the variability in the genomic location of open chromatin sites in each of the cells.

Targeting the IL33-NLRP3 axis improves therapy for experimental cerebral malaria.

Cerebral malaria (CM) is a serious neurological complication caused by infection. Currently, the only treatment for CM is the provision of antimalarial drugs; however, such treatment by itself often fails to prevent death or development of neurological sequelae. To identify potential improved treatments for CM, we performed a nonbiased whole-brain transcriptomic time-course analysis of antimalarial drug chemotherapy of murine experimental CM (ECM).

Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology.

Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology.

A unified framework for estimating parameters of kinetic biological models.

Background: Utilizing kinetic models of biological systems commonly require computational approaches to estimate parameters, posing a variety of challenges due to their highly non-linear and dynamic nature, which is further complicated by the issue of non-identifiability. We propose a novel parameter estimation framework by combining approaches for solving identifiability with a recently introduced filtering technique that can uniquely estimate parameters where conventional methods fail. This framework first conducts a thorough analysis to identify and classify the non-identifiable parameters and provides a guideline for solving them.

Unscented Kalman filter with parameter identifiability analysis for the estimation of multiple parameters in kinetic models.

In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis.

Comparison of different algorithms for simultaneous estimation of multiple parameters in kinetic metabolic models.

Computational models in systems biology are usually characterized by a lack of reliable parameter values. This is especially true for kinetic metabolic models. Experimental data can be used to estimate these missing parameters.