Biology subjects

Huang, S.-Y.

Publications and source records attributed to Huang, S.-Y..

4 recordsLinked to original sources

bioRxiv2020

Topoisomerase 3B (TOP3B) DNA and RNA Cleavage Complexes and Pathway to Repair TOP3B-linked RNA and DNA Breaks

Genetic inactivation of TOP3B is linked with schizophrenia, autism, intellectual disability and cancer. The present study demonstrates that in vivo TOP3B forms both RNA and DNA cleavage complexes (TOP3Bccs) and reveals a pathway for repairing TOP3Bccs. For detecting cellular TOP3Bccs, we engineered a "self-trapping" mutant of TOP3B (R338W TOP3B) and to determine how human cells repair TOP3Bccs, we depleted tyrosyl-DNA phosphodiesterases (TDP1 and TDP2). TDP2-deficient cells produced elevated TOP3Bccs both in DNA and RNA. Conversely, overexpression of TDP2 lowered cellular TOP3Bccs. Using recombinant human TDP2, we demonstrate that TDP2 cannot excise the native form of TOP3Bccs. Hypothesizing that TDP2 cannot access phosphotyrosyl linkage unless TOP3B is either proteolyzed or denatured, we found that cellular TOP3Bccs are ubiquitinated by the E3 Ubiquitin Ligase TRIM41 before undergoing proteasomal degradation and excision by TDP2. HIGHLIGHTSO_LIMethod for in vivo detection of TOP3B cleavage complexes (TOP3Bccs) formed both in DNA and RNA, using a religation defective "self-trapping" R338W TOP3B mutant. C_LIO_LIFirst evidence that TDP2 excises TOPccs produced by a type IA topoisomerase. C_LIO_LITDP2 processes both RNA and DNA TOP3Bccs following their ubiquitylation and proteasomal degradation inside cell. C_LIO_LITRIM41 is the first reported E3 ubiquitin ligase for TOP3Bcc ubiquitylation and proteasomal degradation. C_LI

cell biology↗

bioRxiv2020

Molecular mechanism of evolution and human infection with the novel coronavirus (2019-nCoV)

Since December, 2019, an outbreak of pneumonia caused by the new coronavirus (2019-nCoV) has hit the city of Wuhan in the Hubei Province. With the continuous development of the epidemic, it has become a national public health crisis and calls for urgent antiviral treatments or vaccines. The spike protein on the coronavirus envelope is critical for host cell infection and virus vitality. Previous studies showed that 2019-nCoV is highly homologous to human SARS-CoV and attaches host cells though the binding of the spike receptor binding domain (RBD) domain to the angiotensin-converting enzyme II (ACE2). However, the molecular mechanisms of 2019-nCoV binding to human ACE2 and evolution of 2019-nCoV remain unclear. In this study, we have extensively studied the RBD-ACE2 complex, spike protein, and free RBD systems of 2019-nCoV and SARS-CoV using protein-protein docking and molecular dynamics (MD) simulations. It was shown that the RBD-ACE2 binding free energy for 2019-nCoV is significantly lower than that for SARS-CoV, which is consistent with the fact that 2019-nCoV is much more infectious than SARS-CoV. In addition, the spike protein of 2019-nCoV shows a significantly lower free energy than that of SARS-CoV, suggesting that 2019-nCoV is more stable and able to survive a higher temperature than SARS-CoV. This may also provide insights into the evolution of 2019-nCoV because SARS-like coronaviruses are thought to have originated in bats that are known to have a higher body-temperature than humans. It was also revealed that the RBD of 2019-nCoV is much more flexible especially near the binding site and thus will have a higher entropy penalty upon binding ACE2, compared to the RBD of SARS-CoV. That means that 2019-nCoV will be much more temperature-sensitive in terms of human infection than SARS-CoV. With the rising temperature, 2019-nCoV is expected to decrease its infection ability much faster than SARS-CoV, and get controlled more easily. The present findings are expected to be helpful for the disease prevention and control as well as drug and vaccine development of 2019-nCoV.

microbiology↗

bioRxiv2020

Alteration of Power Law Scaling of Spontaneous Brain Activity in Schizophrenia

Nonlinear dynamical analysis has been used to quantify the complexity of brain signal at temporal scales. Power law scaling is a well-validated method in physics that has been used to describe the complex nature of a system across different time scales. In this research, we investigated the change of power-law characteristics in a large-scale resting-state fMRI data of schizophrenia (N = 200) and healthy participants (N = 200) derived from Taiwan Aging and Mental Illness cohort. Fourier transform was used to determine the power spectral density (PSD) of resting-state fMRI signal. We estimated the power law scaling of PSD of resting-state fMRI signal by determining the slope of the regression line fitting to the log-log plot of PSD. The power law scaling represents the dynamical properties of resting-state fMRI signal ranging from noisy oscillation (e.g., white noise) to complex fluctuations (e.g., slope approaches -1). Linear regression model was used to assess the statistical difference in power law scaling between schizophrenia and healthy participants. The significant differences in power law scaling were found in six brain regions. Schizophrenia patients has significantly more positive power law scaling (i.e., frequency components become more homogenous) at four brain regions: left precuneus, left medial dorsal nucleus, right inferior frontal gyrus, and right middle temporal gyrus, compared with healthy participants. Additionally, schizophrenia exhibited less positive power law scaling (i.e., frequency components are more dominant at lower frequency range) in bilateral putamen. Significant correlations of power law scaling with the severity of psychosis were found in these identified brain areas in schizophrenia. These findings suggest that schizophrenia has abnormal brain signal complexity toward random patterns, which is linked to psychotic symptoms. The power law scaling analysis may serve as a novel functional brain imaging marker for evaluating patients with mental illness.

neuroscience↗

bioRxiv2019

BAMscale: quantification of DNA sequencing peaks and generation of scaled coverage tracks

BAMscale is a one-step tool that processes DNA sequencing datasets from chromatin binding (ChIP-seq) and chromatin state changes (ATAC-seq, END-seq) experiments to DNA replication data (OK-seq, NS-seq and replication timing). The outputs include normalized peak scores in text format and scaled coverage tracks (BigWig) which are directly accessible to data visualization programs. BAMscale (available at https://github.com/ncbi/BAMscale) effectively processes large sequencing datasets (~100Gb size) in minutes, outperforming currently available tools.

bioinformatics↗