Article
Biochemistry & Molecular Biology
Yi Zhang, Jun Wang, Yi Xiao
Summary: The 3D structures of RNAs play a crucial role in understanding their biological functions, but the experimentally determined structures are limited. To overcome this, computational methods like 3dRNA have been proposed. In this study, the researchers extended the 3dRNA method to predict the 3D structures of circular RNAs and found that they exhibit distinct structures from linear RNAs. The predicted structures of circular RNAs also showed increased stability in ligand binding compared to their linear counterparts.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Jelke J. Fros, Imke Visser, Bing Tang, Kexin Yan, Eri Nakayama, Tessa M. Visser, Constantianus J. M. Koenraadt, Monique M. van Oers, Gorben P. Pijlman, Andreas Suhrbier, Peter Simmonds
Summary: Most vertebrate RNA viruses suppress CpG and UpA dinucleotides, while invertebrate mRNA and arthropod-specific RNA viruses do not show CpG suppression. Using a Zika virus model, it was found that CpG-suppressed mutants replicated less in vertebrate cells but more in mosquito cells. This suggests that the composition of arbo flaviviruses' genome plays a crucial role in balancing replication in vertebrate hosts and vectors.
Review
Cell Biology
Elena Rivas
Summary: Predicted RNA structures from single-sequence RNA folding programs may not indicate functional importance. Evolutionary signatures are needed to determine if an RNA structure is conserved. Covariation analysis can assess the conservation of RNA structures.
WILEY INTERDISCIPLINARY REVIEWS-RNA
(2021)
Review
Biochemical Research Methods
Junkang Wei, Siyuan Chen, Licheng Zong, Xin Gao, Yu Li
Summary: Protein-RNA interactions play a vital role in cellular activities. Previous computational methods heavily rely on sequence data due to the lack of protein structure data. However, the emergence of AlphaFold is set to revolutionize protein-RNA interaction prediction. In this review, we provide a comprehensive overview of the field, covering binding site and binding preference prediction, as well as commonly used datasets, features, and models. We also discuss potential challenges and opportunities in this area.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Biochemistry & Molecular Biology
Natan Nagar, Nir Ben Tal, Tal Pupko
Summary: Measuring evolutionary rates at the residue level is crucial for understanding protein structure and function. We present EvoRator, a machine-learning regression algorithm that predicts site-specific evolutionary rates based on protein structures. We demonstrate the superiority of EvoRator over traditional physicochemical features and showcase its application in three common protein evolution scenarios.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemical Research Methods
Faizy Ahsan, Zichao Yan, Doina Precup, Mathieu Blanchette
Summary: PhyloPGM is a computational model that leverages probabilistic approach to improve the prediction accuracy on human sequences by aggregating predictions from trained predictors in different orthologous regions.
Article
Virology
Mudasir Gani, Sergei Senger, Satish Lokanath, Pawan Saini, Kamlesh Bali, Rakesh Gupta, Vankadara Sivaprasad, Johannes A. Jehle, Joerg T. Wennmann
Summary: The study revealed the distribution of Indian BmNPV and investigated their genetic composition through methods like gene sequencing and phylogenetic analysis. It found genetic variations among different isolates and identified some new closely related viral strains.
Article
Biochemistry & Molecular Biology
Jeff Gaither, Yi-Hsuan Lin, Ralf Bundschuh
Summary: The study focuses on the interactions of hundreds of RNA binding proteins in the human genome with RNA in cells, introducing RBPBind as a web-based tool for quantitatively predicting the interaction by considering the effect of RNA secondary structure on binding affinity. The tool provides a quick and easy way to obtain reliable predicted binding affinities and locations for single-stranded RNA binding proteins based solely on RNA sequence.
JOURNAL OF MOLECULAR BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Margherita A. G. Matarrese, Alessandro Loppini, Martina Nicoletti, Simonetta Filippi, Letizia Chiodo
Summary: The study of RNA structure is crucial in understanding RNA molecular functioning. With the flexibility of RNA, the large number of expressed RNAs, and the diverse functions they have, it is difficult to obtain structural information on the same scale as is available for proteins. In silico prediction of RNA 3D structures is particularly important to understand the relationship between structure and function, as the 3D structure plays a significant role in molecular interactions with DNA or protein complexes. The accuracy of RNA 3D structure prediction relies on a properly predicted or measured secondary structure. This paper comparatively evaluates computational tools for modeling RNA secondary structure, focusing on freely available web-server versions for more accessible use. The evaluation focuses on the performance for long sequences and aims to select the best methods for investigating long non-coding RNAs (lncRNAs), which are of special relevance due to their involvement in regulatory mechanisms.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemical Research Methods
Sumeet Patiyal, Anjali Dhall, Khushboo Bajaj, Harshita Sahu, Gajendra P. S. Raghava
Summary: This paper describes a method called Pprint2 for predicting RNA-interacting residues in proteins. The study found that positively charged amino acids are more prominent in these residues. By using evolutionary profiles and convolutional neural network, the researchers developed a final model that performed well on the validation dataset.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Biochemical Research Methods
Kengo Sato, Michiaki Hamada
Summary: Computational analysis of RNA sequences plays a crucial role in RNA biology. In recent years, the incorporation of artificial intelligence and machine learning techniques into RNA sequence analysis has gained significant traction. Machine learning-based approaches have shown remarkable advancements, enhancing the precision of sequence analysis related to RNA secondary structures. Furthermore, artificial intelligence and machine learning innovations are also applied in the analysis of RNA-small molecule interactions, RNA drug discovery, and the design of RNA aptamers.
BRIEFINGS IN BIOINFORMATICS
(2023)
Review
Biochemistry & Molecular Biology
Xunxun Wang, Shixiong Yu, En Lou, Ya-Lan Tan, Zhi-Jie Tan
Summary: Ribonucleic acid (RNA) molecules have important biological functions such as catalysis and gene regulation, which are strongly dependent on their structure. In the past two decades, computational models have been developed to predict RNA three-dimensional (3D) structures. These models predict the structure ensemble, evaluate near-native RNAs, and refine the identified RNAs. This review provides a comprehensive overview of recent advances in RNA 3D structure modeling, including structure ensemble prediction, evaluation, and refinement, and highlights insights and perspectives in modeling RNA 3D structures.
Article
Biochemistry & Molecular Biology
Muhammad Nabeel Asim, Muhammad Ali Ibrahim, Muhammad Imran Malik, Andreas Dengel, Sheraz Ahmed
Summary: This study develops a computational framework, Circ-LocNet, to accurately detect the sub-cellular localization of circular RNAs (circRNAs). The research evaluates various sequence descriptors and machine learning classifiers and finds that residue frequency-based descriptors and tree-based classifiers are the most suitable for predicting the sub-cellular localization of circRNAs.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Biochemical Research Methods
Youjin Kim, Junseok Kwon
Summary: This study accurately predicts the protein's secondary structure by capturing the local patterns of protein and presents a novel prediction model called AttSec based on the transformer architecture. The results show that this model outperforms other no-evolutionary-information-based models by 11.8% on the evaluation datasets. Although there was no significant improvement in accuracy compared to other models, the improvement on the DSSP8 dataset is greater than that on the DSSP3 dataset, suggesting that the proposed pairwise feature could have a remarkable effect on tasks requiring finely subdivided classification.
BMC BIOINFORMATICS
(2023)
Article
Energy & Fuels
Dario Alviso, Silvia Daniela Romano
Summary: This study proposed regression models to determine the refractive index and speed of sound of biodiesel, which can be helpful in studying the characteristics and production process of biodiesel. The results obtained from the regression models showed good agreement with measured and available experimental data.
Article
Obstetrics & Gynecology
Carrie E. Jung, Mehrbod Estaki, Jessica Chopyk, Bryn C. Taylor, Antonio Gonzalez, Daniel McDonald, Jenny Shin, Kimberly Ferrante, Erika Wasenda, Quinn Lippmann, Rob Knight, David Pride, Emily S. Lukacz
Summary: In postmenopausal women with recurrent urinary tract infections, the urogenital microbiome showed an increase in Lactobacillus after 6 months of vaginal estrogen treatment. Specifically, the relative increase in L. crispatus may be associated with treatment success.
FEMALE PELVIC MEDICINE AND RECONSTRUCTIVE SURGERY
(2022)
Article
Gastroenterology & Hepatology
Qibin Qi, Jun Li, Bing Yu, Jee-Young Moon, Jin C. Chai, Jordi Merino, Je Hu, Miguel Ruiz-Canela, Casey Rebholz, Zheng Wang, Mykhaylo Usyk, Guo-Chong Chen, Bianca C. Porneala, Wenshuang Wang, Ngoc Quynh Nguyen, Elena Feofanova, Megan L. Grove, Thomas J. Wang, Robert E. Gerszten, Josee Dupuis, Jordi Salas-Salvado, Wei Bao, David L. Perkins, Mariha L. Daviglus, Bharat Thyagarijan, Jianwen Cai, Tao Wang, JoAnn E. Manson, Miguel A. Martinez-Gonzalez, Elizabeth Selvin, Kathryn M. Rexrode, Clary B. Clish, Frank B. Hu, James B. Meigs, Rob Knight, Robert D. Burk, Eric Boerwinkle, Robert C. Kaplan
Summary: The study found positive associations between tryptophan and its metabolites with the risk of type 2 diabetes, while indolepropionate was inversely associated with the risk. Additionally, host genetic variants, dietary factors, gut bacteria, and their interplay related to these type 2 diabetes-related metabolites were identified.
Article
Clinical Neurology
Ronald J. Ellis, Robert K. Heaton, Sara Gianella, Gibraan Rahman, Rob Knight
Summary: The analysis of gut microbial diversity and dysbiosis in PWH and PWoH revealed that more severe DNP was associated with lower alpha diversity in PWH. Specific changes in microbial taxa ratios were also observed in PWH with DNP. These findings suggest that gut dysbiosis may contribute to prevalent DNP in PWH.
Review
Oncology
Juan Javier-DesLoges, Rana R. McKay, Austin D. Swafford, Gregory D. Sepich-Poore, Rob Knight, J. Kellogg Parsons
Summary: There is increasing evidence that the microbiome plays a role in the development and treatment of many human diseases, including prostate cancer. The microbiome can impact prostate cancer development through direct or indirect pathways. Unique microbial signatures have been identified in prostate cancer patients, but studies vary in their findings, highlighting the need for further clinical investigation.
PROSTATE CANCER AND PROSTATIC DISEASES
(2022)
Meeting Abstract
Biochemistry & Molecular Biology
Nathan Greenberg, Marissa L. Burnsed-Torres, Antonio Gonzalez, Abigail G. Casso, Kara L. Lubieniecki, Brian P. Ziemba, Matthew J. Rossman, Emily C. Adam, Michel Chonchol
Article
Nutrition & Dietetics
Julia Beauchamp-Walters, Gajender Aleti, Lourdes Herrera, Justine Debelius, Natalie Lima, Pritha Dalal, Suzi Hong, Rob Knight, Kyung E. Rhee
Summary: This study aimed to examine the relationship between diet and the gut microbiome in children with medical complexity (CMC) who receive enteral tube feedings, and to determine the impact of different formulas on the CMC microbiome. The results showed that CMC receiving exclusive enteral nutrition had decreased alpha diversity and differences in beta diversity compared with healthy controls, highlighting the importance of diet over medications.
JOURNAL OF PARENTERAL AND ENTERAL NUTRITION
(2023)
Editorial Material
Biochemical Research Methods
Sergey Knyazev, Karishma Chhugani, Varuni Sarwal, Ram Ayyala, Harman Singh, Smruthi Karthikeyan, Dhrithi Deshpande, Pelin Icer Baykal, Zoia Comarova, Angela Lu, Yuri Porozov, Tetyana Vasylyeva, Joel O. Wertheim, Braden T. Tierney, Charles Y. Chiu, Ren Sun, Aiping Wu, Malak S. Abedalthagafi, Victoria M. Pak, Shivashankar H. Nagaraj, Adam L. Smith, Pavel Skums, Bogdan Pasaniuc, Andrey Komissarov, Christopher E. Mason, Eric Bortz, Philippe Lemey, Fyodor Kondrashov, Niko Beerenwinkel, Tommy Tsan-Yuk Lam, Nicholas C. Wu, Alex Zelikovsky, Rob Knight, Keith A. Crandall, Serghei Mangul
Summary: During the COVID-19 pandemic, genomics and bioinformatics have become crucial tools in public health. They have been used to acquire genomic data that support global health responses, aid in the development of testing methods, and enable the timely tracking of novel SARS-CoV-2 variants. However, the rapid generation and analysis of genomic data present unique technical, scientific, and organizational challenges.
Article
Multidisciplinary Sciences
Shiyu S. Bai-Tong, Megan S. Thoemmes, Kelly C. Weldon, Diba Motazavi, Jessica Kitsen, Shalisa Hansen, Annalee Furst, Bob Geng, Se Jin Song, Jack A. Gilbert, Lars Bode, Pieter C. Dorrestein, Rob Knight, Sydney A. Leibel, Sandra L. Leibel
Summary: Preterm infants are at a greater risk for asthma and atopic disease. A pilot study found that the gut metabolomic pathways of preterm infants born to mothers with a history of asthma show changes as early as the first 6 weeks of life.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Niema Moshiri, Kathleen M. Fisch, Amanda Birmingham, Peter DeHoff, Gene W. Yeo, Kristen Jepsen, Louise C. Laurent, Rob Knight
Summary: During the COVID-19 pandemic, the development of a user-friendly tool called ViReflow, utilizing Amazon Web Services and Reflow system, has enabled rapid analysis of viral sequence data, contributing to the efficient monitoring of SARS-CoV-2 strains worldwide.
SCIENTIFIC REPORTS
(2022)
Article
Biotechnology & Applied Microbiology
Julia M. Gauglitz, Kiana A. West, Wout Bittremieux, Candace L. Williams, Kelly C. Weldon, Morgan Panitchpakdi, Francesca Di Ottavio, Christine M. Aceves, Elizabeth Brown, Nicole C. Sikora, Alan K. Jarmusch, Cameron Martino, Anupriya Tripathi, Michael J. Meehan, Kathleen Dorrestein, Justin P. Shaffer, Roxana Coras, Fernando Vargas, Lindsay DeRight Goldasich, Tara Schwartz, MacKenzie Bryant, Gregory Humphrey, Abigail J. Johnson, Katharina Spengler, Pedro Belda-Ferre, Edgar Diaz, Daniel McDonald, Qiyun Zhu, Emmanuel O. Elijah, Mingxun Wang, Clarisse Marotz, Kate E. Sprecher, Daniela Vargas-Robles, Dana Withrow, Gail Ackermann, Lourdes Herrera, Barry J. Bradford, Lucas Maciel Mauriz Marques, Juliano Geraldo Amaral, Rodrigo Moreira Silva, Flavio Protasio Veras, Thiago Mattar Cunha, Rene Donizeti Ribeiro Oliveira, Paulo Louzada-Junior, Robert H. Mills, Paulina K. Piotrowski, Stephanie L. Servetas, Sandra M. Da Silva, Christina M. Jones, Nancy J. Lin, Katrice A. Lippa, Scott A. Jackson, Rima Kaddurah Daouk, Douglas Galasko, Parambir S. Dulai, Tatyana I. Kalashnikova, Curt Wittenberg, Robert Terkeltaub, Megan M. Doty, Jae H. Kim, Kyung E. Rhee, Julia Beauchamp-Walters, Kenneth P. Wright, Maria Gloria Dominguez-Bello, Mark Manary, Michelli F. Oliveira, Brigid S. Boland, Norberto Peporine Lopes, Monica Guma, Austin D. Swafford, Rachel J. Dutton, Rob Knight, Pieter C. Dorrestein
Summary: This study introduces a reference-data-driven analysis approach to increase the usage of metabolomics MS/MS data and enable empirical evaluation of dietary patterns from untargeted data.
NATURE BIOTECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Erick Armingol, Hratch M. Baghdassarian, Cameron Martino, Araceli Perez-Lopez, Caitlin Aamodt, Rob Knight, Nathan E. Lewis
Summary: In this study, the authors introduce a new method called Tensor-cell2cell for deciphering context-driven intercellular communication. By considering multiple stages, states, or locations of cells, Tensor-cell2cell can uncover communication patterns associated with different phenotypic states and provide the ability to identify communication modules related to disease severity.
NATURE COMMUNICATIONS
(2022)
Article
Cell Biology
Ana Carolina Dantas Machado, Steven D. Brown, Amulya Lingaraju, Vignesh Sivaganesh, Cameron Martino, Amandine Chaix, Peng Zhao, Antonio F. M. Pinto, Max W. Chang, R. Alexander Richter, Alan Saghatelian, Alan R. Saltiel, Rob Knight, Satchidananda Panda, Amir Zarrinpar
Summary: Compositional oscillations of the gut microbiome and transcriptome in the ileum are disrupted in diet-induced obesity, but time-restricted feeding can partially restore these rhythms and provide metabolic benefits.
Article
Plant Sciences
Si Qin, Javier Veloso, Mirna Baak, Britt Boogmans, Tim Bosman, Guido Puccetti, Xiaoqian Shi-Kunne, Sandra Smit, Robert Grant-Downton, Thomas Leisen, Matthias Hahn, Jan A. L. van Kan
Summary: The fungus Botrytis cinerea produces small RNAs (sRNAs) that target mRNAs in tomato, leading to the down-regulation of predicted target genes during early infection. However, mutant strains of B. cinerea with reduced sRNA production did not show decreased virulence on any plant species tested.
MOLECULAR PLANT PATHOLOGY
(2023)
Article
Genetics & Heredity
Wei Xiong, Dirk-Jan M. van Workum, Lidija Berke, Linda Bakker, Elio Schijlen, Frank F. M. Becker, Henri van de Geest, Sander Peters, Richard Michelmore, Rob van Treuren, Marieke Jeuken, Sandra Smit, M. Eric Schranz
Summary: This study presents a de novo reference assembly of L. virosa with high continuity and complete gene space. It compares the genome of L. virosa with that of L. sativa and L. saligna, providing insights into genetic variations and potential breeding challenges. The analysis reveals chromosomal inversions and the role of long-terminal repeat elements in genome expansion. It also investigates immune genes and receptor-like kinases, contributing to the understanding of evolutionary patterns. These findings are important for breeding improved lettuce varieties.
G3-GENES GENOMES GENETICS
(2023)
Article
Microbiology
Theo A. J. Van der Lee, Marga P. E. Van Gent-Pelzer, Eef M. Jonkheer, Balazs Brankovics, Ilse M. Houwers, Jan M. Van der Wolf, Peter J. M. Bonants, Inge Van Duivenbode, Robert A. M. Vreeburg, Mathijs Nas, Sandra Smit
Summary: P. brasiliense is a bacterial pathogen causing blackleg in potatoes. The strains of P. brasiliense can be divided into two classes, some causing blackleg symptoms and some not. Comparative pangenomic analysis identified two genes present only in the blackleg-causing strains, and specific assays were developed for the detection of these strains, providing a more efficient and robust scoring method.
