Biology subjects

Lenz, M.

Publications and source records attributed to Lenz, M..

5 recordsLinked to original sources

bioRxiv2018

Adipose tissue in health and disease through the lens of its building blocks

BackgroundHighly specialized cells work in synergy forming tissues to perform functions required for the survival of organisms. Understanding this tissue-specific cellular heterogeneity and homeostasis is essential to comprehend the development of diseases within the tissue and also for developing regenerative therapies. Cellular subpopulations in the adipose tissue have been related to disease development, but efforts towards characterizing the adipose tissue cell type composition are limited due to lack of robust cell surface markers, limited access to tissue samples, and the labor-intensive process required to identify them.\n\nResultsWe propose a framework, identifying cellular heterogeneity while providing state-of-the-art cellular markers for each cell type present in tissues using transcriptomics level analysis. We validate our approach with an independent dataset and present the most comprehensive study of adipose tissue cell type composition to date, determining the relative amounts of 21 different cell types in 779 adipose tissue samples detailing differences across four adipose tissue depots, between genders, across ranges of BMI and in different stages of type-2 diabetes. We also highlight the heterogeneity in reported marker-based studies of adipose tissue cell type composition and provide novel cellular markers to distinguish different cell types within the adipose tissue.\n\nConclusionsOur study provides a systematic framework for studying cell type composition in a given tissue and valuable insights into adipose tissue cell type heterogeneity in health and disease.

systems biology↗

bioRxiv2018

A direct proof that sole actin dynamics drive membrane deformations

Cell membrane deformations are crucial for proper cell function. Specialized protein assemblies initiate inward or outward membrane deformations that turn into, for example, filopodia or endocytic intermediates. Actin dynamics and actin-binding proteins are involved in this process, although their detailed role remains controversial. We show here that a dynamic, branched actin network is sufficient, in absence of any membrane-associated proteins, to initiate both inward and outward membrane deformation. With actin polymerization triggered at the membrane of liposomes, we produce inward filopodia-like structures at low tension, while outward endocytosis-like structures are robustly generated regardless of tension. Our results are reminiscent of endocytosis in mammalian cells, where actin polymerization forces are required when membrane tension is increased, and in yeast, where they are always required to overcome the opposing turgor pressure. By combining experimental observations with physical modeling, we propose a mechanism for actin-driven endocytosis under high tension or high pressure conditions.

biophysics↗

bioRxiv2017

Modulation of formin processivity by profilin and mechanical tension

Formins are major regulators of actin networks. They enhance actin filament dynamics by remaining processively bound to filament barbed ends. How biochemical and mechanical factors affect formin processivity are open questions. Monitoring individual actin filaments in a microfluidic flow, we report that formin mDia1 dissociates faster under higher ionic strength and when actin concentration is increased. Profilin, known to increase the elongation rate of formin-associated filaments, surprisingly decreases the formin dissociation rate, by bringing formin FH1 domains in transient contact with the barbed end. In contrast, piconewton tensile forces applied to actin filaments accelerate formin dissociation by orders of magnitude, largely overcoming profilin-mediated stabilization. We developed a model of formin conformations and its confrontation to our data indicates the existence of two different dissociation pathways, with force favoring one over the other. How cells limit formin dissociation under tension is now a key question for future studies.

biophysics↗

bioRxiv2017

Leukocyte counts based on site-specific DNA methylation analysis

The composition of white blood cells is usually assessed by histomorphological parameters or flow cytometric measurements. Alternatively, leukocyte differential counts (LDCs) can be estimated by deconvolution algorithms for genome-wide DNA methylation (DNAm) profiles. We identified cell-type specific CG dinucleotides (CpGs) that facilitate relative quantification of leukocyte subsets. Site-specific analysis of DNAm levels by pyrosequencing provides similar precision of LDCs as conventional methods, whereas it is also applicable to frozen samples and requires only very small volumes of blood. Furthermore, we describe a new approach for absolute quantification of cell numbers based on a non-methylated reference DNA. Our \"Epi-Blood-Count\" facilitates robust and cost effective analysis of blood counts for clinical application.

molecular biology↗

bioRxiv2017

Stem cell differentiation is a stochastic process with memory

Pluripotent stem cells are able to self-renew indefinitely in culture and differentiate into all somatic cell types in vivo. While much is known about the molecular basis of pluripotency, the molecular mechanisms of lineage commitment are complex and only partially understood. Here, using a combination of single cell profiling and mathematical modeling, we examine the differentiation dynamics of individual mouse embryonic stem cells (ESCs) as they progress from the ground state of pluripotency along the neuronal lineage. In accordance with previous reports we find that cells do not transit directly from the pluripotent state to the neuronal state, but rather first stochastically permeate an intermediate primed pluripotent state, similar to that found in the maturing epiblast in development. However, analysis of rate at which individual cells enter and exit this intermediate metastable state using a hidden Markov model reveals that the observed ESC and epiblast-like macrostates conceal a chain of unobserved cellular microstates, which individual cells transit through stochastically in sequence. These hidden microstates ensure that individual cells spend well-defined periods of time in each functional macrostate and encode a simple form of epigenetic memory that allows individual cells to record their position on the differentiation trajectory. To examine the generality of this model we also consider the differentiation of mouse hematopoietic stem cells along the myeloid lineage and observe remarkably similar dynamics, suggesting a general underlying process. Based upon these results we suggest a statistical mechanics view of cellular identities that distinguishes between functionally-distinct macrostates and the many functionally-similar molecular microstates associated with each macrostate. Taken together these results indicate that differentiation is a discrete stochastic process amenable to analysis using the tools of statistical mechanics.

systems biology↗