ShapeMetrics: A 3D Cell Segmentation Pipeline for Single-Cell Spatial Morphometric Analysis.

There is a growing need for single-cell level data analysis in correlation with the advancements of microscopy techniques. Morphology-based statistics gathered from individual cells are essential for detection and quantification of even subtle changes within the complex tissues, yet the information available from high-resolution imaging is oftentimes sub-optimally utilized due to the lack of proper computational analysis software. Here we present ShapeMetrics, a 3D cell segmentation pipeline that we have developed to identify, analyze, and quantify single cells in an image. This MATLAB-based script enables users to extract morphological parameters, such as ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. We have specifically invested in creating a user-friendly pipeline, aimed for biologists with a limited computational background. Our pipeline is presented with detailed stepwise instructions, starting from the establishment of machine learning-based prediction files of immuno-labeled cell membranes followed by the application of 3D cell segmentation and parameter extraction script, leading to the morphometric analysis and spatial visualization of cell clusters defined by their morphometric features.

Maintenance of pluripotency-like signature in the entire ectoderm leads to neural crest stem cell potential.

The ability of the pluripotent epiblast to contribute progeny to all three germ layers is thought to be lost after gastrulation. The later-forming neural crest (NC) rises from ectoderm and it remains poorly understood how its exceptionally high stem-cell potential to generate mesodermal- and endodermal-like derivatives is obtained. Here, we monitor transcriptional changes from gastrulation to neurulation using single-cell-Multiplex-Spatial-Transcriptomics (scMST) complemented with RNA-sequencing. We show maintenance of pluripotency-like signature (Nanog, Oct4/PouV, Klf4-positive) in undecided pan-ectodermal stem-cells spanning the entire ectoderm late during neurulation with ectodermal patterning completed only at the end of neurulation when the pluripotency-like signature becomes restricted to NC, challenging our understanding of gastrulation. Furthermore, broad ectodermal pluripotency-like signature is found at multiple axial levels unrelated to the NC lineage the cells later commit to, suggesting a general role in stemness enhancement and proposing a mechanism by which the NC acquires its ability to form derivatives beyond "ectodermal-capacity" in chick and mouse embryos.

Maintenance of pluripotency in the entire ectoderm enables neural crest formation.

The ability of the pluripotent epiblast to contribute progeny to all three germ layers is thought to be lost after gastrulation. The later-forming neural crest (NC) rises from ectoderm and it remains poorly understood how its exceptionally high stem-cell potential to generate mesodermal- and endodermal-like cells is obtained. We monitored transcriptional changes from gastrulation to neurulation using single-cell-Multiplex-Spatial-Transcriptomics (scMST) complemented with RNA-sequencing. Unexpectedly, we find maintenance of undecided Nanog/Oct4-PouV/Klf4-positive pluripotent-like pan-ectodermal stem-cells spanning the entire ectoderm late in the neurulation process with ectodermal patterning completed only at the end of neurulation when pluripotency becomes restricted to NC, challenging our understanding of gastrulation. Furthermore, broad ectodermal pluripotency is found at all axial levels unrelated to the NC lineage the cells later commit to, suggesting a general role in stemness enhancement and proposing a mechanism by which the NC acquires its ability to form derivatives beyond "ectodermal-capacity" in chick and mouse embryos.

PGC-1α Signaling Increases GABA(A) Receptor Subunit α2 Expression, GABAergic Neurotransmission and Anxiety-Like Behavior in Mice.

Peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is a master regulator of mitochondria biogenesis and cell stress playing a role in metabolic and degenerative diseases. In the brain PGC-1α expression has been localized mainly to GABAergic interneurons but its overall role is not fully understood. We observed here that the protein levels of γ-aminobutyric acid (GABA) type A receptor-α2 subunit (GABARα2) were increased in hippocampus and brain cortex in transgenic (Tg) mice overexpressing PGC-1α in neurons. Along with this, GABARα2 expression was enhanced in the hippocampus of the PGC-1α Tg mice, as shown by quantitative PCR. Double immunostaining revealed that GABARα2 co-localized with the synaptic protein gephyrin in higher amounts in the striatum radiatum layer of the hippocampal CA1 region in the Tg compared with Wt mice. Electrophysiology revealed that the frequency of spontaneous and miniature inhibitory postsynaptic currents (mIPSCs) was increased in the CA1 region in the Tg mice, indicative of an augmented GABAergic transmission. Behavioral tests revealed an increase for anxiety-like behavior in the PGC-1α Tg mice compared with controls. To study whether drugs acting on PPARγ can affect GABARα2, we employed pioglitazone that elevated GABARα2 expression in primary cultured neurons. Similar results were obtained using the specific PPARγ agonist, N-(2-benzoylphenyl)-O-[2-(methyl-2-pyridinylamino) ethyl]-L-tyrosine hydrate (GW1929). These results demonstrate that PGC-1α regulates GABARα2 subunits and GABAergic neurotransmission in the hippocampus with behavioral consequences. This indicates further that drugs like pioglitazone, widely used in the treatment of type 2 diabetes, can influence GABARα2 expression via the PPARγ/PGC-1α system.

ShapeMetrics: A userfriendly pipeline for 3D cell segmentation and spatial tissue analysis.

The demand for single-cell level data is constantly increasing within life sciences. In order to meet this demand, robust cell segmentation methods that can tackle challenging in vivo tissues with complex morphology are required. However, currently available cell segmentation and volumetric analysis methods perform poorly on 3D images. Here, we generated ShapeMetrics, a MATLAB-based script that segments cells in 3D and, by performing unbiased clustering using a heatmap, separates the cells into subgroups according to their volumetric and morphological differences. The cells can be accurately segregated according to different biologically meaningful features such as cell ellipticity, longest axis, cell elongation, or the ratio between cell volume and surface area. Our machine learning based script enables dissection of a large amount of novel data from microscope images in addition to the traditional information based on fluorescent biomarkers. Furthermore, the cells in different subgroups can be spatially mapped back to their original locations in the tissue image to help elucidate their roles in their respective morphological contexts. In order to facilitate the transition from bulk analysis to single-cell level accuracy, we emphasize the user-friendliness of our method by providing detailed step-by-step instructions through the pipeline hence aiming to reach users with less experience in computational biology.

Caspase-2 and p75 neurotrophin receptor (p75NTR) are involved in the regulation of SREBP and lipid genes in hepatocyte cells.

Lipid-induced toxicity is part of several human diseases, but the mechanisms involved are not fully understood. Fatty liver is characterized by the expression of different growth and tissue factors. The neurotrophin, nerve growth factor (NGF) and its pro-form, pro-NGF, are present in fatty liver together with p75 neurotrophin receptor (p75NTR). Stimulation of human Huh7 hepatocyte cells with NGF and pro-NGF induced Sterol-regulator-element-binding protein-2 (SREBP2) activation and increased Low-Density Lipoprotein Receptor (LDLR) expression. We observed that phosphorylation of caspase-2 by p38 MAPK was essential for this regulation involving a caspase-3-mediated cleavage of SREBP2. RNA sequencing showed that several genes involved in lipid metabolism were altered in p75NTR-deficient mouse liver. The same lipogenic genes were downregulated in p75NTR gene-engineered human Huh7 cells and reciprocally upregulated by stimulation of p75NTRs. In the knock-out mice the serum cholesterol and triglyceride levels were reduced, suggesting a physiological role of p75NTRs in whole-body lipid metabolism. Taken together, this study shows that p75NTR signaling influences a network of genes involved in lipid metabolism in liver and hepatocyte cells. Modulation of p75NTR signaling may be a target to consider in various metabolic disorders accompanied by increased lipid accumulation.

Neurotrophin receptor Ntrk2b function in the maintenance of dopamine and serotonin neurons in zebrafish.

Neurotrophins and their receptors have highly conserved evolutionary lineage in vertebrates including zebrafish. The NTRK2 receptor has two isoforms in zebrafish, Ntrk2a and Ntrk2b. The spatio-temporal expression pattern of bdnf and ntrk2b in the zebrafish brain was studied using in situ hybridization. The robust and corresponding expression pattern of ntrk2b to bdnf suggests that ntrk2b is the key receptor for bdnf in the zebrafish brain, unlike its duplicate isoform ntrk2a. To study ntrk2b function, two different genetic strategies, the TILLING mutant and morpholino oligonucleotides (MO), were used. Specific subsets of the dopaminergic and serotonergic neuronal populations were affected in the mutants and morphants. The mutant showed anxiety- like behavior both in larval and adult stages. Our results consistently indicate that BDNF/NTRK2 signaling has a significant role in the development and maintenance of aminergic neuronal populations. Therefore, the ntrk2b-deficient zebrafish is well suited to study mechanisms relevant for psychiatric disorders attributed to a dysfunctional monoaminergic system.