Biology subjects

Hsu, C.-T.

Publications and source records attributed to Hsu, C.-T..

5 recordsLinked to original sources

bioRxiv2022

Enhanced Mirror Neuron Network Activity and Effective Connectivity during Live Interaction

Facial expressions are indispensable in daily human communication. Previous neuroimaging studies investigating facial expression processing have presented pre-recorded stimuli and lacked live face-to-face interaction. Our paradigm alternated between presentations of real-time model performance and pre-recorded videos of dynamic facial expressions to participants. Simultaneous functional magnetic resonance imaging (fMRI) and facial electromyography activity recordings, as well as post-scan valence and arousal ratings were acquired from 44 female participants. Live facial expressions enhanced the subjective valence and arousal ratings as well as facial muscular responses. Live performances showed greater engagement of the right posterior superior temporal sulcus (pSTS), right inferior frontal gyrus (IFG), right amygdala and right fusiform gyrus, and modulated the effective connectivity within the right mirror neuron system (IFG, pSTS, and right inferior parietal lobule). A support vector machine algorithm could classify multivoxel activation patterns in brain regions involved in dynamic facial expression processing in the mentalizing networks (anterior and posterior cingulate cortex). These results indicate that live social interaction modulates the activity and connectivity of the right mirror neuron system and enhances spontaneous mimicry, further facilitating emotional contagion. HighlightsO_LIWe alternately presented real-time and pre-recorded dynamic facial expressions. C_LIO_LILive facial expressions enhanced emotion contagion and spontaneous facial mimicry. C_LIO_LILive conditions modulated mirror neuron system activity and effective connectivity. C_LIO_LIThe mentalizing network showed distinctive multivoxel patterns in live conditions. C_LIO_LIThe results support the validity of second-person design in social neuroscience. C_LI

neuroscience↗

bioRxiv2021

DNA-free CRISPR-Cas9 gene editing of tetraploid tomatoes using protoplast regeneration

Wild tomatoes are important genomic resources for tomato research and breeding. Development of a foreign DNA-free CRISPR-Cas delivery system has potential to mitigate public concern about genetically modified organisms. Here, we established a DNA-free protoplast regeneration and CRISPR-Cas9 genome editing system for Solanum peruvianum, an important resource for tomato introgression breeding. We generated mutants for genes involved in small interfering RNAs (siRNA) biogenesis, RNA-DEPENDENT RNA POLYMERASE 6 (SpRDR6) and SUPPRESSOR OF GENE SILENCING 3 (SpSGS3); pathogen-related peptide precursors, PATHOGENESIS-RELATED PROTEIN-1 (SpPR-1) and PROSYSTEMIN (SpProsys); and fungal resistance (MILDEW RESISTANT LOCUS O, SpMlo1) using diploid or tetraploid protoplasts derived from in vitro-grown shoots. The ploidy level of these regenerants was not affected by PEG-calcium-mediated transfection, CRISPR reagents, or the target genes. By karyotyping and whole genome sequencing analysis, we confirmed that CRISPR-Cas9 editing did not introduce chromosomal changes or unintended genome editing sites. All mutated genes in both diploid and tetraploid regenerants were heritable in the next generation. spsgs3 null T0 regenerants and sprdr6 null T1 progeny had wiry, sterile phenotypes in both diploid and tetraploid lines. The sterility of the spsgs3 null mutant was partially rescued, and fruits were obtained by grafting to wild-type stock and pollination with wild-type pollen. The resulting seeds contained the mutated alleles. Tomato yellow leaf curl virus proliferated at higher levels in spsgs3 and sprdr6 mutants than in the wild type. Therefore, this protoplast regeneration technique should greatly facilitate tomato polyploidization and enable the use of CRISPR-Cas for S. peruvianum domestication and tomato breeding. One-sentence summaryDNA-free CRISPR-Cas9 genome editing in wild tomatoes creates stable and inheritable diploid and tetraploid regenerants.

plant biology↗

bioRxiv2021

A New Protocol for Targeted insertion using CRISPR-Cas9, Oligo Single-Stranded DNA and Protoplast Regeneration

Versatile genome editing can be facilitated by the insertion of DNA sequences into specific locations. Current protocols involving clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins rely on low efficiency homology-directed repair or non-homologous end joining with modified double-stranded DNA oligonucleotides as donors. Our simple protocol eliminates the need for expensive equipment, chemical and enzymatic donor DNA modification or plasmid construction by using polyethylene glycol-calcium to deliver non-modified single-stranded DNA oligonucleotides and CRISPR-Cas9 ribonucleoprotein into protoplasts. Plants regenerated via edited protoplasts achieved targeted insertion frequencies of up to 50.0% in Nicotiana benthamiana and 13.6% in rapid cycling Brassica oleracea without antibiotic selection. Using a 60-nt donor containing 27 nt in each homologous arm, 6 of 22 regenerated N. benthamiana plants showed targeted insertions, and one contained a precise insertion of a 6-bp HindIII site. The inserted sequences were transmitted to the next generation and invite the possibility of future exploration of versatile genome editing by targeted DNA insertion in plants.

plant biology↗

bioRxiv2020

Cytoplasm Biophysical Properties Madolute Microtubule Dynamics

The cytoplasm is a crowded, visco-elastic environment whose physical properties change according to physiological or developmental states. How the physical properties of the cytoplasm impact cellular functions in vivo remain poorly understood. Here, we probed the effects of cytoplasmic concentration on microtubules by applying osmotic shifts to fission yeast, moss, and mammalian cells. We show that both the rates of microtubule polymerization and depolymerization scale linearly and inversely with cytoplasmic concentration; an increase in cytoplasmic concentration decreases the rates of microtubule polymerization and depolymerization proportionally, while a decrease in cytoplasmic concentration leads to the opposite. Numerous lines of evidence indicate that these effects are due to changes in cytoplasmic viscosity rather than cellular stress responses or macromolecular crowding per se. We reconstituted these effects on microtubules in vitro by tuning viscosity. Our findings indicate that, even in normal conditions, the viscosity of cytoplasm modulates the reactions underlying microtubule dynamic behaviors.

cell biology↗

bioRxiv2018

Numerical parameter space compression and its application to microtubule dynamic instability

Physical models of biological systems can become difficult to interpret when they have a large number of parameters. But the models themselves actually depend on (i.e. are sensitive to) only a subset of those parameters. Rigorously identifying this subset of \"stiff\" parameters has been made possible by the development of parameter space compression (PSC). However, PSC has only been applied to analytically-solvable physical models. We have generalized this powerful method by developing a numerical approach to PSC that can be applied to any computational model. We validated our method against analytically-solvable models of random walk with drift and protein production and degradation. We then applied our method to an active area of biophysics research, namely to a simple computational model of microtubule dynamic instability. Such models have become increasingly complex, perhaps unnecessarily. By adding two new parameters that account for prominent structural features of microtubules, we identify one that can be \"compressed away\" (the \"seam\" in the microtubule) and another that is essential to model performance (the \"tapering\" of microtubule ends). Furthermore, we show that the microtubule model has an underlying, low-dimensional structure that explains the vast majority of our experimental data. We argue that numerical PSC can identify the low-dimensional structure of any computational model in biophysics. The low-dimensional structure of a model is easier to interpret and identifies the mechanisms and experiments that best characterize the system.

biophysics↗