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Barishman, A.

Publications and source records attributed to Barishman, A..

3 recordsLinked to original sources

Female iPSC X-chromosome inactivation (XCI) erosion and its transcriptomic effects during CRISPR gene editing and neural differentiation

Human induced pluripotent stem cells (hiPSC) and iPSC-differentiated neural cells, in combination with CRISPR editing, are commonly used for studying neurodevelopmental and other brain disorders. Female iPSCs undergo random X-chromosome inactivation (XCI) via epigenetic silencing by noncoding X inactive specific transcript (XIST). It is known that female iPSCs may lose XIST expression, leading to XCI erosion that affects both X-linked and autosomal gene expression. However, the effects of CRSIPR editing and neural differentiation on XCI erosion in iPSC-derived neurons and how this may confound a real-world transcriptomic analysis of differentially expressed genes (DEGs) are poorly understood. Here, leveraging bulk RNA-seq of hundreds of CRISPR-edited female iPSC lines from four donor lines for 66 genes and single-cell RNA-seq of iPSC-derived neurons of a subset of 42 edited genes, we investigated the effects of XCI erosion during CRISPR editing and in iPSC-derived neurons. We found that XCI erosion was variable in CRISPR-edited female iPSCs and largely preserved in iPSC-derived neurons. Like in iPSCs, XIST in neurons predominately influenced the expression of X-linked genes; however, its effect on autosomal genes was more pronounced in single neurons. Mechanistically, XIST epigenetically causes allelic imbalance of both X-linked and autosomal genes, with the former showing stronger allele-specific expression (ASE) bias. Notably, XIST-induced ASE bias exhibited a conserved positional pattern at loci affecting neurodevelopmental genes across different female lines and cell types. Finally, we demonstrated a confounding effect of XCI erosion on DEG analyses in iPSC-derived neurons. These results have significant implications in hiPSC modeling of neurodevelopmental and other brain disorders.

genomics↗

A fast, muscle-actuated biohybrid swimming robot

The integration of biological actuators with soft scaffolds has led to biohybrid robots including microscale flagellate-like swimmers which generate thrust by waving their flagella-like tails. However, they achieve swimming speeds of only 0.014 body lengths per minute, Reynolds number (Re) [~] 10-3, which is much slower than natural flagellates (O(102 - 103) body lengths per minute). To investigate this, we applied theoretical and experimental methods, including fabrication of a swimmer that converts muscle contractions into large angular tail displacements, reaching swimming speeds of 86.8 m/s (0.58 body lengths per minute), surpassing low-Re predictions. Swimming dynamics sharply transition from a low-Re ([~] 10-3) to an intermediate-Re ([~] 0.1) regime when the actuation angle exceeded 4{degrees}. We used the swimmer to study the ability of muscle to adapt to mechanical stiffness and the beneficial effects of neuromuscular coculture on muscle development. These insights into mechanical and chemical cues will help optimize future biobots. TeaserHow are biological flagellate swimmers like E. coli and sperm cells so fast? We have built a new biohybrid robot to explore the theory.

bioengineering↗

Synapses without tension fail to fire in an in vitro network of hippocampal neurons.

Neurons in the brain communicate with each other at their synapses. It has long been understood that this communication occurs through biochemical processes. Here, we reveal a previously unrecognized paradigm wherein mechanical tension in neurons is essential for communication. Using in vitro rat hippocampal neurons, we find that (1) neurons become tout/tensed after forming synapses resulting in a contractile neural network, and (2) without this contractility, neurons fail to fire. To measure time evolution of network contractility in 3D (not 2D) extracellular matrix, we developed an ultra-sensitive force sensor with 1 nN resolution. We employed Multi-Electrode Array (MEA) and iGluSnFR, a glutamate sensor, to quantify neuronal firing at the network and at the single synapse scale, respectively. When neuron contractility is relaxed, both techniques show significantly reduced firing. Firing resumes when contractility is restored. Neural contractility may play a crucial role in memory, learning, cognition, and various neuropathologies.

neuroscience↗