Article
Biology
Xiaoming Fu, Heta P. Patel, Stefano Coppola, Libin Xu, Zhixing Cao, Tineke L. Lenstra, Ramon Grima, Anna Akhmanova
Summary: This study compares transcriptional parameters with and without correction for cell cycle phases and post-transcriptional noise in yeast cells using smFISH, finding that corrections can significantly reduce errors in parameter estimation. The study also outlines how to adjust for measurement noise in smFISH effectively.
Article
Biochemical Research Methods
Mark Jayson Cortez, Hyukpyo Hong, Boseung Choi, Jae Kyoung Kim, Kresimir Josic
Summary: This study proposes a non-Markovian, hierarchical Bayesian inference framework for quantifying the variability of cellular processes within and across cells in a population. By using a delayed birth-death process, the proposed hierarchical framework is shown to be robust and leads to improved estimates compared to its non-hierarchical counterpart when applied to in silico and experimental data. The mean delays in protein production are reported to be larger than previously thought, with a coefficient of variation of around 0.2 across the population, and not strongly correlated with protein production or growth rates.
Review
Plant Sciences
William Agbemafle, Min May Wong, Diane C. Bassham
Summary: This review summarizes key regulatory mechanisms for modulating autophagy through post-translational modification or transcriptional regulation. Plants activate cellular responses to adapt to changing environmental conditions, one of which is autophagy, where cellular components are delivered to the vacuole for degradation. Autophagy is activated by various conditions, and the pathways controlling its activation are being elucidated. However, there is still much to discover regarding how these factors work together to properly modulate autophagy in response to specific signals.
JOURNAL OF EXPERIMENTAL BOTANY
(2023)
Article
Biology
Alberto Giaretta
Summary: This study aims to theoretically study and complete the knowledge about a general basic open loop and linear modeling scheme of gene expression via alternative splicing and its connection with transcription and translation. The study shows the pivotal role of the splicing conversion rates in regulating stochastic noise and the stochastic bursts, autocorrelation, and noise power spectra in gene expression.
Review
Biotechnology & Applied Microbiology
Chenyi Li, Tian Jiang, Michelle Li, Yusong Zou, Yajun Yan
Summary: This review focuses on recent advances in fine-tuning gene expression at the DNA, RNA, and protein levels to improve microbial biosynthesis of natural products. Commonly used regulatory toolsets in each level are discussed, and perspectives for future direction in this area are provided.
BIOTECHNOLOGY ADVANCES
(2022)
Article
Biotechnology & Applied Microbiology
Soonkyu Hwang, Namil Lee, Donghui Choe, Yongjae Lee, Woori Kim, Ji Hun Kim, Gahyeon Kim, Hyeseong Kim, Neung-Ho Ahn, Byoung-Hee Lee, Bernhard O. Palsson, Byung-Kwan Cho
Summary: In this study, the regulatory elements of transcription and translation in Streptomyces griseus were analyzed using multiple "omics" datasets. Several important regulators and elements were identified, providing a foundation for genetic engineering to improve secondary metabolite production in Streptomyces.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Franziska Hildebrandt, Alma Andersson, Sami Saarenpaa, Ludvig Larsson, Noemi Van Hul, Sachie Kanatani, Jan Masek, Ewa Ellis, Antonio Barragan, Annelie Mollbrink, Emma R. Andersson, Joakim Lundeberg, Johan Ankarklev
Summary: Global transcriptional differences across lobular units in the liver remain unknown. Here the authors perform spatial transcriptomics of liver tissue to delineate transcriptional differences in physical space, confirm lobular zonation along transcriptional gradients and suggest the presence of previously uncharacterized structures within liver tissue.
NATURE COMMUNICATIONS
(2021)
Article
Biochemistry & Molecular Biology
Yizhao Luan, Nan Tang, Jiaqi Yang, Shuting Liu, Chichi Cheng, Yan Wang, Congying Chen, Ya-nan Guo, Hongwei Wang, Wenxue Zhao, Qian Zhao, Wei Li, Mengqing Xiang, Rong Ju, Zhi Xie
Summary: This study characterized the transcriptional and translational changes after knocking down 75 individual human ribosomal proteins (RPs). The results showed that the deficiency of individual RPs perturbed the expression of specific subsets of genes, enriched in eight major functional classes, such as cell cycle and development. The RPs were subjected to co-translational regulation under ribosomal stress, with opposite effects of 60S and 40S subunits. Additionally, the study revealed the functional and regulatory roles of RPL11 and RPL15 in retina development and angiogenesis, respectively.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Biotechnology & Applied Microbiology
Qiang Tang, Fulei Nie, Juanjuan Kang, Wei Chen
Summary: An innovative method called mRNALocater was proposed to detect the subcellular localization of eukaryotic mRNA by adopting a model fusion strategy. The method utilizes electron-ion interaction pseudopotential and pseudo k-tuple nucleotide composition to encode sequences and employs correlation coefficient filtering algorithm and feature forward search technology to mine hidden feature information, improving prediction accuracy. Results from independent dataset tests show promising performances for predicting eukaryotic mRNA sub-cellular localizations, making mRNALocater a powerful tool in practical applications.
Article
Biotechnology & Applied Microbiology
Rabea Ghandour, Yang Gao, Josephin Laskowski, Rouhollah Barahimipour, Stephanie Ruf, Ralph Bock, Reimo Zoschke
Summary: In plant biotechnology, the expression of transgenes in chloroplasts is common practice. However, the potential unintended effects on native chloroplast genes are often overlooked. This study examined the expression of the chloroplast genome in transplastomic tobacco plants and found that transgene insertion can lead to overexpression of downstream genes and interfere with the transcription and translation of nearby genes. The study suggests strategies to minimize unintended consequences of transgene expression on native chloroplast genes.
PLANT BIOTECHNOLOGY JOURNAL
(2023)
Article
Biology
John S. Favate, Shun Liang, Alexander L. Cope, Srujana S. Yadavalli, Premal Shah
Summary: Understanding the molecular mechanisms behind complex adaptations is challenging due to redundancy at the genetic level. In this study, the Escherichia coli long-term evolution experiment was used to characterize the transcriptional and translational changes in evolving populations. The results show that despite few shared mutations at the genetic level, clones from replicate populations exhibit remarkably similar gene expression patterns at both the transcriptional and translational levels.
Article
Multidisciplinary Sciences
Yoshika Janapala, Katrina Woodward, Jiwon Lee, Melanie Rug, Thomas Preiss, Nikolay E. Shirokikh
Summary: Rapid mRNA redistribution and alterations in translation are crucial for cell homeostatic adjustments. RNA-seq-based ribosome profiling experiments provide valuable data for translation control, but may be biased in fast cellular responses.
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
(2021)
Article
Genetics & Heredity
Simon Aube, Lou Nielly-Thibault, Christian R. Landry
Summary: The contribution of changes in transcription, translation, and degradation to the differences in protein abundance among genes is not fully understood. This study reveals that transcriptional divergence is more prominent than translational divergence in yeast paralogous genes and identifies two potential mechanisms for this pattern: an evolutionary trade-off between gene expression precision and economy, and a larger mutational target size for transcription. Simulations using a minimal model of post-duplication evolution support both mechanisms. These findings emphasize the importance of characterizing mutational effects on transcription and translation and highlight the evolutionary impacts of cellular trade-offs and mutation bias.
Review
Cell Biology
Zaur M. Kachaev, Sergey D. Ivashchenko, Eugene N. Kozlov, Lyubov A. Lebedeva, Yulii V. Shidlovskii
Summary: Components of the translation apparatus, including ribosomal proteins, play crucial roles in cell nucleus, involving in nuclear processes and regulation of gene expression. These components control intranuclear trafficking, regulate protein activity, and participate in cellular response to stimulation and stress.
Article
Biology
Asli Azizoglu, Roger Brent, Fabian Rudolf
Summary: The study introduces a new gene expression controller, WTC846, for precise and graded gene expression in Saccharomyces cerevisiae, independent of growth conditions. This controller allows for adjustable protein expression across a range of cellular abundances with limited variation.
Article
Biochemical Research Methods
Xinnan Dai, Fan Xu, Shike Wang, Piyushkumar A. Mundra, Jie Zheng
Summary: The study introduces a new method named PIKE-R2P, which significantly improves the prediction performance of protein abundances at the single-cell level by incorporating protein-protein interactions and prior knowledge into graph neural networks.
BMC BIOINFORMATICS
(2021)
Article
Engineering, Environmental
Min Liu, Jie Jiang, Jie Zheng, Tao Huan, Bei Gao, Xunchang Fei, Yulan Wang, Mingliang Fang
Summary: The study aims to develop a platform for identifying unknown abiotic or biotransformation products for reactive compounds. Using stable isotope-labeling metabolomics, researchers have developed a reactive compound transformation profiler (RTP) that can automatically analyze high-resolution mass spectrometry data sets to uncover probable transformation products.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Guang-Lei Ma, Hartono Candra, Li Mei Pang, Juan Xiong, Yichen Ding, Hoa Thi Tran, Zhen Jie Low, Hong Ye, Min Liu, Jie Zheng, Mingliang Fang, Bin Cao, Zhao-Xun Liang
Summary: Naturally occurring hydrazones are rare, but widely used in the synthesis of organic compounds and functional materials. In this study, a novel family of microbial metabolites, tasikamides, was discovered. These tasikamides have a unique cyclic pentapeptide scaffold and contain a hydrazone group. The biosynthesis of tasikamides was found to require two gene clusters, one for the cyclic peptide scaffold and another for the synthesis of alkyl 5-hydroxylanthranilate. The findings revealed a novel mechanism for the formation of specialized metabolites through the coupling of two biosynthetic pathways.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2022)
Article
Biochemical Research Methods
Ke Zhang, Chenxi Wang, Liping Sun, Jie Zheng
Summary: HiCoEx is an end-to-end framework for explainable prediction of gene co-expression from Hi-C data, utilizing a graph neural network. It applies a graph attention mechanism to a gene contact network inferred from Hi-C data in order to learn gene representations for supervised prediction of co-expression in a task-specific manner. The model is able to automatically learn gene representations from 3D genomics signals and capture meaningful biological patterns to improve prediction accuracy.
Review
Cell Biology
Subhendu K. Das, Brian A. Lewis, David Levens
Summary: The MYC protooncogene acts as a universal transcription amplifier by interacting with various factors and complexes that regulate almost every cellular process. However, a comprehensive model that explains the interactions and dynamics of components of the transcription and replication machinery is still lacking. This article reviews the oncogenic potential of MYC and proposes a 'hand-over model' for the differential distribution and trafficking of unstructured MYC via interactions with different gene-regulatory complexes and factors. Additionally, it discusses how unstructured MYC energetically modulates the energy landscape of the transcription cycle.
TRENDS IN CELL BIOLOGY
(2023)
Article
Biochemical Research Methods
Xin Liu, Jiale Yu, Siyu Tao, Beiyuan Yang, Shike Wang, Lin Wang, Fang Bai, Jie Zheng
Summary: Synthetic lethality (SL) is a genetic interaction that can expand the range of anti-cancer therapeutic targets. To predict SL, we propose a graph neural network that learns the interaction between two genes. Experimental results show that our method outperforms others and provides an explanation of SL mechanisms through weighted paths in graphs.
Article
Biochemical Research Methods
Shike Wang, Yimiao Feng, Xin Liu, Yong Liu, Min Wu, Jie Zheng
Summary: The study finds that contrastive learning methods can predict synthetic lethality with great potential in cancer drug development. By establishing a model that does not require negative samples, it effectively captures the characteristics of synthetic lethality samples. The successful application of contrastive learning methods provides a new direction for discovering novel synthetic lethality.
Article
Biochemistry & Molecular Biology
Yoo-Ah Kim, Ermin Hodzic, Bayarbaatar Amgalan, Ariella Saslafsky, Damian Wojtowicz, Teresa M. Przytycka
Summary: This paper explores the use of mutational signatures to study environment-induced changes in gene expression in control lung tissues from lung adenocarcinoma samples. The analysis shows the combined impact of smoking and tumor-related micro-environments on gene expression and cell-type composition in non-neoplastic lung tissue. The study provides evidence for the utility of mutational signatures as sensors of environmental exposures and demonstrates the valuable information that can be obtained from cancer databases for non-cancer lung tissue research.
Article
Engineering, Environmental
Junjie Yang, Fanrong Zhao, Jie Zheng, Yulan Wang, Xunchang Fei, Yongjun Xiao, Mingliang Fang
Summary: Identification of harmful environmental pollutants is commonly done using liquid chromatography with high-resolution mass spectrometry. Prioritization of candidates is important yet challenging due to the large number of candidates. This study aimed to prioritize candidates based on their toxicity and identification evidence. An R package, NTAprioritization.R, was developed for fast prioritization of suspect lists.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Genetics & Heredity
Bayarbaatar Amgalan, Damian Wojtowicz, Yoo-Ah Kim, Teresa M. Przytycka
Summary: In recent years, the study of mutagenic processes has been enhanced through the analysis of mutational signatures. However, the links between mutagens and observed mutation patterns, as well as their interactions with molecular pathways, are not fully understood. To address this, we developed a network-based method called GeneSigNet, which reveals the relationships between genes and mutational signatures. By applying GeneSigNet to cancer datasets, we identified important connections between mutational signatures and cellular processes, providing insights into cancer-related mechanisms.
Article
Biochemical Research Methods
Ke Zhang, Min Wu, Yong Liu, Yimiao Feng, Jie Zheng
Summary: The study proposes a model named KR4SL to predict synthetic lethality (SL) partners for a given primary gene. This model captures the structural semantics of a knowledge graph (KG) by efficiently constructing and learning from relational digraphs in the KG. It encodes the semantic information of the relational digraphs by fusing textual semantics of entities into propagated messages and enhancing the sequential semantics of paths using a recurrent neural network. Extensive experiments show that KR4SL outperforms all the baselines and provides explanatory subgraphs for the predicted gene pairs, unveiling the prediction process and mechanisms underlying synthetic lethality. The improved predictive power and interpretability indicate the practical usefulness of deep learning in SL-based cancer drug target discovery.
Article
Multidisciplinary Sciences
Brian A. Lewis, Subhendu Kumar Das, Rajiv Kumar Jha, David Levens
Summary: This study reveals the existence of dense and transcriptionally active biomolecular condensates (BMCs) in the nucleus, which can represent the physiological nuclear environment. This finding is crucial for further understanding transcriptional regulation mechanisms.
Article
Biochemical Research Methods
Soumitra Pal, Brian Oliver, Teresa M. Przytycka
Summary: This study developed a computationally efficient method called EvoGeneX based on the OU process for modeling gene expression evolution and tested its performance through extensive simulations. A formal measure of evolutionary expression divergence was also introduced for comparative analysis. The results showed that genes with adaptive expression evolution tend to be body-part specific, while genes with constrained evolution are shared across body-parts.
JOURNAL OF COMPUTATIONAL BIOLOGY
(2023)
Article
Mathematical & Computational Biology
Jie Wang, Min Wu, Xuhui Huang, Li Wang, Sophia Zhang, Hui Liu, Jie Zheng
Summary: The new version of SynLethDB database includes newly identified synthetic lethal relationships through CRISPR screening, expands the knowledge graph and functionality related to synthetic lethality, and provides more query and browsing capabilities, making it easier for researchers to discover clinically relevant synthetic lethal relationships.
DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION
(2022)
Article
Biochemistry & Molecular Biology
Subhendu K. Das, Vladislav Kuzin, Donald P. Cameron, Suzanne Sanford, Rajiv Kumar Jha, Zuqin Nie, Marta Trullols Rosello, Ronald Holewinski, Thorkell Andresson, Jan Wisniewski, Toyoaki Natsume, David H. Price, Brian A. Lewis, Fedor Kouzine, David Levens, Laura Baranello
Summary: MYC is directly associated with topoisomerase 1 (TOP1) and TOP2, and it stimulates their activities, leading to increased levels of these enzymes on DNA and promotion of genome function.