Article
Biochemical Research Methods
Peiqiang Liu, Chang Liu, Yanyan Mao, Junhong Guo, Fanshu Liu, Wangmin Cai, Feng Zhao
Summary: This paper proposes a method called CTF to identify essential proteins based on edge features and fusion of multiple-source information. The CTF method outperforms state-of-the-art methods in identifying essential proteins, and the fusion of other biological information improves the accuracy of identification.
BMC BIOINFORMATICS
(2023)
Article
Mathematical & Computational Biology
Tushar Ranjan Sahoo, Swati Vipsita, Sabyasachi Patra
Summary: Researchers propose a method to detect protein complexes using dense neighborhoods in an interaction graph, which can discover functional modules, reveal unknown protein functions, and demonstrate high efficiency and good predictive performance in experiments.
INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES
(2023)
Article
Veterinary Sciences
Nicola Palmieri, Ilias Apostolakos, Surya Paudel, Michael Hess
Summary: This study identified gene variations and SNPs associated with APEC pathogenicity, suggesting the involvement of multiple regulated pathways. The findings also suggest the importance of nutrient uptake and defense from the host immune system in APEC pathogenicity.
FRONTIERS IN VETERINARY SCIENCE
(2023)
Article
Multidisciplinary Sciences
Francois Bertaux, Sebastian Sosa-Carrillo, Viktoriia Gross, Achille Fraisse, Chetan Aditya, Mariela Furstenheim, Gregory Batt
Summary: Small-scale, low-cost bioreactors are gaining popularity in quantitative systems and synthetic biology. In this study, the authors present ReacSight, a strategy that enhances bioreactor arrays by connecting them with sensitive measurement devices using low-cost pipetting robots. They demonstrate the capabilities of ReacSight in yeast, including real-time optogenetic control of gene expression, exploration of nutrient scarcity effects on fitness and cellular stress, and dynamic control of a two-strain consortium's composition.
NATURE COMMUNICATIONS
(2022)
Article
Genetics & Heredity
Zixuan Meng, Linai Kuang, Zhiping Chen, Zhen Zhang, Yihong Tan, Xueyong Li, Lei Wang
Summary: A prediction model called WPDINM is proposed in this study to detect key proteins based on a novel weighted protein-domain interaction network. Experimental results show that WPDINM achieves significantly higher predictive accuracy for key protein identification compared to traditional competing measures.
FRONTIERS IN GENETICS
(2021)
Article
Computer Science, Artificial Intelligence
Nahla Mohamed Ahmed, Ling Chen, Bin Li, Wei Liu, Caiyan Dai
Summary: This paper presents a random walk-based method named EPD-RW to identify essential proteins by integrating network topology and biological information. Experimental results demonstrate that EPD-RW can achieve the best performance among all tested methods on yeast PPI datasets. The biological features greatly enhance the performance of essential protein detection.
Article
Biochemical Research Methods
Yi Yue, Chen Ye, Pei-Yun Peng, Hui-Xin Zhai, Iftikhar Ahmad, Chuan Xia, Yun-Zhi Wu, You-Hua Zhang
Summary: This study proposes a deep learning framework to predict essential proteins by integrating features from protein-protein interaction networks, subcellular localization, and gene expression profiles. Experimental results show that the model outperforms traditional centrality methods and machine learning methods, and the processing strategy of multiple biological information is preferable.
BMC BIOINFORMATICS
(2022)
Article
Chemistry, Analytical
Sheng-Yan Chen, Yan Zhang, Renjie Li, Baojun Wang, Bang-Ce Ye
Summary: This study improves the performance of whole-cell biosensors for arsenic contamination by optimizing the promoter design. The arsenic-responsive system from Escherichia coli is used as the sensing element, and a genetic circuit is constructed to characterize the refactored promoters. A novel promoter with maximal repression efficiency and optimal fold change is discovered, and high sensitivity fluorescence and colorimetric sensors are developed for quantifying arsenic levels in groundwater.
ANALYTICAL CHEMISTRY
(2022)
Article
Biochemical Research Methods
Min Zeng, Min Li, Zhihui Fei, Fang-Xiang Wu, Yaohang Li, Yi Pan, Jianxin Wang
Summary: A deep learning framework is proposed to automatically learn biological features, which enhances the identification of essential proteins by utilizing techniques and features at different levels, and outperforms traditional centrality methods and existing machine learning-based methods according to experimental results.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2021)
Article
Genetics & Heredity
Xiao-Hong Xin, Ying-Ying Zhang, Chu-Qiao Gao, Hui Min, Likun Wang, Pu-Feng Du
Summary: Long noncoding RNAs (lncRNAs) play important roles in biological processes and identifying essential lncRNAs is crucial for disease diagnosis and treatment. Experimental methods for identification are costly and time consuming, thus computational methods can be an alternative approach. This study proposes a method that combines network centrality measures and lncRNA sequence information to identify essential lncRNAs and finds that network information significantly improves the predictive performance of sequence-based methods.
FRONTIERS IN GENETICS
(2022)
Article
Biochemistry & Molecular Biology
Weikang Gong, Aysam Guerler, Chengxin Zhang, Elisa Warner, Chunhua Li, Yang Zhang
Summary: The study introduced a uniform pipeline called Threpp, which effectively addresses the issue of genome-wide protein-protein interaction determination with increased accuracy. Experimental results on the Escherichia coli genome showed that Threpp generated a greater number of accurate PPIs, which are crucial for the survival and evolution of E. coli.
JOURNAL OF MOLECULAR BIOLOGY
(2021)
Article
Biochemical Research Methods
Houwang Zhang, Zhenan Feng, Chong Wu
Summary: The study aimed to reconstruct the protein-protein interaction network and proposed a method to refine the original network based on subcellular localization data, protein complex data, and gene expression data. The results showed that the method greatly improved the accuracy of identifying essential proteins.
CURRENT BIOINFORMATICS
(2023)
Article
Cell Biology
Martijn Wehrens, Laurens H. J. Krah, Benjamin D. Towbin, Rutger Hermsen, Sander J. Tans
Summary: This study reveals that catabolic enzyme expression in E. coli cells continuously responds to metabolic fluctuations, which is regulated by the cyclic AMP (cAMP) and cAMP receptor protein (CRP) system. The study uses single-cell microscopy, genetic constructs, and mathematical modeling to show how fluctuations circulate through the metabolic and genetic network at sub-cell-cycle timescales. The findings suggest that the cAMP-CRP system may have evolved to control both internal metabolic fluctuations and external growth conditions.
Article
Multidisciplinary Sciences
Yuanxi Xiao, Zhichao Jiang, Mengqi Zhang, Xuemei Zhang, Qi Gan, Yunfeng Yang, Pengju Wu, Xu Feng, Jinfeng Ni, Xiuzhu Dong, Qunxin She, Qihong Huang, Yulong Shen
Summary: This study clarifies the function of archaeal canonical SSBs, which are not essential for cell viability but play a role in melting dsRNA or DNA/RNA hybrids.
Article
Chemistry, Multidisciplinary
Charles Burridge, Christopher A. Waudby, Tomasz Wlodarski, Anais M. E. Cassaignau, Lisa D. Cabrita, John Christodoulou
Summary: This study used solution-state NMR spectroscopy to measure transverse proton relaxation rates for methyl groups in folded ribosome-nascent chain complexes, revealing interactions between the nascent chain and ribosome surface driven predominantly by electrostatics. By observing changes in these interactions as subsequent domain emerges, the impact on free energy landscapes associated with co-translational folding process can be deduced.
Article
Biochemistry & Molecular Biology
Richard Kuan-Lin Lee, Tian-Neng Li, Sui-Yuan Chang, Tai-Ling Chao, Chun-Hsien Kuo, Max Yu-Chen Pan, Yu-Ting Chiou, Kuan-Ju Liao, Yi Yang, Yi-Hsuan Wu, Chen-Hao Huang, Hsueh-Fen Juan, Hsing-Pang Hsieh, Lily Hui-Ching Wang
Summary: This study developed a new method to detect the molecular interaction between the receptor-binding domain (RBD) of SARS-CoV-2 and the ACE2 receptor, and identified two drugs, Etravirine and Dolutegravir, as effective entry inhibitors against SARS-CoV-2. These drugs showed similar neutralizing activities against different variants of the virus.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Kai-Pu Chen, Chia-Lang Hsu, Yen-Jen Oyang, Hsuan-Cheng Huang, Hsueh-Fen Juan
Summary: Microbial communities are abundant in the human body and dysbiosis is associated with various diseases. This study used miRNA sequencing data from the TCGA database to evaluate bacterial abundance in 32 types of cancer and developed the BIC database to provide information on cancer-associated bacteria.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Biochemical Research Methods
Yueh-Hua Tu, Hsueh-Fen Juan, Hsuan-Cheng Huang
Summary: Gene regulatory networks play a crucial role in various biological phenomena. Single-cell techniques provide higher resolution for studying gene expression, but constructing comprehensive gene regulatory networks across different cell types remains a challenge.
BRIEFINGS IN BIOINFORMATICS
(2023)
Article
Chemistry, Multidisciplinary
Hsueh-Fen Juan, Hsuan-Cheng Huang
Summary: The study of multiple omes is widely used in biomedical research to gain a comprehensive perspective on biological systems. The generation of high-dimensional multiomics data through high-throughput techniques is enabled, but the quantitative analysis and integration of different types of omics data pose challenges. This article provides an up-to-date review on the methods used for quantification and integration of omics data, focusing on transcriptomics, proteomics, and batch effects reduction. The potential of network analysis in understanding biological systems and the current trends in extending quantitative omics data analysis to biological networks are also discussed.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE
(2023)
Article
Biology
Tyng-An Zhou, Hsuan-Po Hsu, Yueh-Hua Tu, Hui-Kuei Cheng, Chih-Yu Lin, Nien-Jung Chen, Jin-Wu Tsai, Ellen A. Robey, Hsuan-Cheng Huang, Chia-Lin Hsu, Ivan L. Dzhagalov, Xiaoyu Hu
Summary: Tissue-resident macrophages in the thymus play a crucial role in organ homeostasis and engulfing apoptotic cells. This study characterized the phenotype, origin, and diversity of these macrophages, revealing two distinct populations with different origins and aging effects.
Article
Biochemistry & Molecular Biology
Chiao-Yu Hsieh, Jian-Hung Wen, Shih-Ming Lin, Tzu-Yang Tseng, Jia-Hsin Huang, Hsuan-Cheng Huang, Hsueh-Fen Juan
Summary: Single-cell RNA sequencing (scRNA-seq) technology is a powerful tool for investigating cellular components and interactions in the tumor microenvironment. It has also been used to study the association between tumor microenvironmental patterns and clinical outcomes, and to analyze the effects of drug treatment on specific cell populations. Recent advances in scRNA-seq have led to the discovery of biomarkers and therapeutic targets. The scDrug bioinformatics workflow provides a one-step pipeline for scRNA-seq data analysis and drug prediction, facilitating the exploration of scRNA-seq data and drug repurposing.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biochemistry & Molecular Biology
Chi -Chun Chen, Yu -Wei Huang, Hsuan-Cheng Huang, Wei-Cheng Lo, Ping -Chiang Lyu
Summary: Circular permutation (CP) is a protein sequence rearrangement that creates different positions for the termini of a protein along an imaginary circularized sequence. CP detection algorithms mainly rely on structural information, which limits their application to proteins with known structures. The development of a sequence-based CP search method is essential for identifying more CP pairs and advancing protein research.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2023)
Article
Biology
Yi-Chun Kao, Yi-Wen Chang, Charles P. Lai, Nai-Wen Chang, Chen-Hao Huang, Chien-Sheng Chen, Hsuan-Cheng Huang, Hsueh-Fen Juan
Summary: This study reveals that cancer cells express higher levels of eATP synthase under starvation stress, leading to increased production of EVs. The eATP synthase generates extracellular ATP to stimulate EV secretion by enhancing P2X(7) receptor-triggered Ca2+ influx. Surprisingly, eATP synthase is also found on the surface of tumor-secreted EVs. The eATP synthase-coated EVs increase uptake by immune cells and inhibit their proliferation and cytokine release.
COMMUNICATIONS BIOLOGY
(2023)
Article
Biology
Yi-Wen Chang, T. Tony Yang, Min-Chun Chen, Y-geh Liaw, Chieh-Fan Yin, Xiu-Qi Lin-Yan, Ting-Yu Huang, Jen-Tzu Hou, Yi-Hsuan Hung, Chia-Lang Hsu, Hsuan-Cheng Huang, Hsueh-Fen Juan
Summary: The ectopic ATP synthase complex, which is located on the surface of cancer cells, plays a role in generating ATP in the extracellular environment and has potential as a target for cancer therapy. Through various proteomics and transcriptomics analyses, researchers have discovered that the ATP synthase complex is first assembled in mitochondria and then transported to the cell surface via microtubules and dynamin-related protein 1 (DRP1) and kinesin family member 5B (KIF5B) interactions. The fusion of mitochondrial membrane to the plasma membrane anchors the ATP synthase on the cell surface, as demonstrated by super-resolution imaging and real-time fusion assays in live cells. These findings provide insight into the trafficking of ectopic ATP synthase and contribute to our understanding of tumor progression dynamics.
COMMUNICATIONS BIOLOGY
(2023)
Article
Physics, Multidisciplinary
Matthew Bravo, Jen-Tsung Hsiang, Bei-Lok Hu
Summary: In this paper, the authors investigate the feasibility of using quantum field memories to decipher information about the early universe. They simulate a statically-bounded universe by subjecting a massless quantum field to a parametric process. The results show that it is possible to identify squeezing by measuring the constant radiation energy density at late times.
Article
Astronomy & Astrophysics
Jen-Tsung Hsiang, Bei-Lok Hu
Summary: This study reexamines the motion of a point charge emitting radiation in an electromagnetic field from the perspective of non-Markovian dynamics. By casting the problem as the non-Markovian dynamics of a Brownian oscillator in a supra-Ohmic environment, it is found that there is no need for a second derivative initial condition and no preacceleration.
