Review
Biology
Janani Manochkumar, Aswani Kumar Cherukuri, Raju Suresh Kumar, Abdulrahman I. Almansour, Siva Ramamoorthy, Thomas Efferth
Summary: This review provides a comprehensive overview of the -omics and multi-omics approaches used for characterizing marine metabolites, along with the need for data integration and machine learning algorithms. It also discusses the challenges and recommendations for conducting multi-omics studies.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Chemistry, Medicinal
Oliver Fiehn, Parker Ladd Bremer, Arpana Vaniya, Tobias Kind, Shunyang Wang
Summary: CFM-ID is a machine learning tool for predicting MS/MS spectra of metabolites. Matching experimental collision energy with CFM-ID's predicted energy produced optimal results, especially for benzenoids on HCD-Orbitrap instruments. CFM-ID 4.0 could be useful as a supplementary tool in the broader context of identification workflows.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2022)
Article
Chemistry, Physical
Victor Fung, Jiaxin Zhang, Eric Juarez, Bobby G. Sumpter
Summary: The study found that in the materials field, graph neural networks perform better and have more flexibility in input with compositionally diverse datasets compared to traditional models. However, GNNs also have some weaknesses, such as high data requirements, which need further improvement.
NPJ COMPUTATIONAL MATERIALS
(2021)
Article
Biochemistry & Molecular Biology
Guangyan Zhou, Zhiqiang Pang, Yao Lu, Jessica Ewald, Jianguo Xia
Summary: Researchers are using OmicsNet to interpret molecular data within a multi-omics context, facilitating hypothesis generation and mechanistic insights.
NUCLEIC ACIDS RESEARCH
(2022)
Article
Chemistry, Analytical
Fatema Bhinderwala, Thao Vu, Thomas G. Smith, Julian Kosacki, Darrell D. Marshall, Yuhang Xu, Martha Morton, Robert Powers
Summary: This article discusses the importance of using multispectral approaches to improve the accuracy and convenience of metabolite assignments, as well as the common experiments used in metabolite assignments. It also explores the impact of 13C-labeled feedstocks like glucose on experimental results and the corresponding improvement methods.
ANALYTICAL CHEMISTRY
(2022)
Article
Agriculture, Multidisciplinary
Hehe Liu, Qinglan Yang, Rui Guo, Jiwei Hu, Qian Tang, Jingjing Qi, Jiwen Wang, Chunchun Han, Rongping Zhang, Liang Li
Summary: The study investigated the impact of storage period on the metabolite composition in duck eggs using non-targeted metabolome technology. The results revealed changes in metabolites in both egg yolk and albumen, showing degradation of nutrients and production of harmful substances over time, ultimately affecting the quality of duck eggs. The findings contribute to a comprehensive understanding of metabolite changes during the deterioration of duck eggs in storage.
JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE
(2022)
Review
Endocrinology & Metabolism
Niek F. de Jonge, Kevin Mildau, David Meijer, Joris J. R. Louwen, Christoph Bueschl, Florian Huber, Justin J. J. van der Hooft
Summary: This article introduces the recent advances in computational metabolite annotation workflows, with a special focus on the evaluation and comparison of these tools. While the progress is significant and promising, inconsistencies in benchmarking different tools hinder users from selecting the most appropriate method. The article summarizes the benchmarking strategies of different tools and provides recommendations.
Article
Biology
Yunwei Zhang, Germaine Wong, Graham Mann, Samuel Muller, Jean Y. H. Yang
Summary: This article introduces the importance of survival analysis and proposes a new benchmarking design, SurvBenchmark, for evaluating the performance of various survival models on clinical and omics datasets. Through a systematic comparison of 320 comparisons, it demonstrates the variations of survival models in real-world applications and highlights the importance of using multiple performance metrics for evaluation.
Article
Chemistry, Multidisciplinary
Muhammad Arif, Abhishek Basu, Kaelin M. Wolf, Joshua K. Park, Lenny Pommerolle, Madeline Behee, Bernadette R. Gochuico, Resat Cinar
Summary: This study identifies gene subnetworks associated with pulmonary fibrosis and proposes peripheral CB1R antagonism as a potential therapeutic target. The findings are based on integrated multi-omics data and validate the results in both mouse models and human patients.
Editorial Material
Microbiology
Joris J. R. Louwen, Justin J. J. van der Hooft
Summary: Microbial specialized metabolites play a crucial role in host-microbiome interactions, and there is a need for new methods to utilize the expanding genomic and metabolomic datasets while connecting them to structural and functional knowledge inferred from transcriptomics and proteomics experiments. This article describes current approaches for comprehensive mining of metabolomics and genomics data, as well as proposes a vision for automated linking of omics data of specialized metabolites to their structures, biosynthesis pathways, producers, and functions.
Article
Chemistry, Analytical
Carter K. Asef, Markace A. Rainey, Brianna M. Garcia, Goncalo J. Gouveia, Amanda O. Shaver, Franklin E. Leach, Alison M. Morse, Arthur S. Edison, Lauren M. McIntyre, Facundo M. Fernandez
Summary: Ion mobility spectrometry (IM) provides valuable data for identifying unknown metabolites in non-targeted metabolomics. This study presents a workflow using de novo molecular formula annotation, MS/MS structure elucidation, and machine learning predictions to identify differential unknown metabolites in Caenorhabditis elegans mutant strains. However, the performance of this approach is limited by instrumentation and data analysis challenges, resulting in a relatively low success rate in filtering candidate structures.
ANALYTICAL CHEMISTRY
(2023)
Article
Biophysics
Minsu Jang, Jonghoon Shin, You Hwan Kim, Tae-Young Jeong, Soojin Jo, Sung-Jo Kim, Vasanthan Devaraj, Joonhee Kang, Eun-Jung Choi, Ji Eun Lee, Jin-Woo Oh
Summary: Metabolome analysis using 3D superstructures has been applied for glaucoma diagnosis, providing comprehensive information and accurate classification of patients. The advantages of 3D superstructures, including high hotspot density, excellent signal repeatability, and thermal stability, enable versatile metabolic analysis and disease diagnosis.
BIOSENSORS & BIOELECTRONICS
(2024)
Article
Biochemistry & Molecular Biology
Bei Gao, Tsung-Chin Wu, Sonja Lang, Lu Jiang, Yi Duan, Derrick E. Fouts, Xinlian Zhang, Xin-Ming Tu, Bernd Schnabl
Summary: This study used various analysis methods to predict mortality in patients with alcoholic hepatitis, and found that gradient boosting achieved the best results when using the bacteria and metabolic pathways dataset for 30-day mortality prediction.
Article
Chemistry, Analytical
Huan Yao, Hansen Zhao, Xingyu Pan, Xu Zhao, Jiaxin Feng, Chengdui Yang, Sichun Zhang, Xinrong Zhang
Summary: This study introduces a general strategy to analyze leukocyte heterogeneity and screen biomarkers using label-free mass cytometry. By applying this method, different types of leukemia cells can be distinguished and specific metabolites can be identified as potential biomarkers.
ANALYTICAL CHEMISTRY
(2021)
Article
Genetics & Heredity
Dengxiang Du, Hanxian Xiong, Congping Xu, Wanyong Zeng, Jinhua Li, Guoqing Dong
Summary: This study identified key metabolic pathways in the response to cadmium stress in perennial tartary buckwheat DK19 through transcriptomic and metabolomic data analysis. The results provide useful clues for genetically improving the resistance to cadmium and improving buckwheat yield and quality.
Article
Biochemistry & Molecular Biology
Barbara R. Terlouw, Kai Blin, Jorge C. Navarro-Munoz, Nicole E. Avalon, Marc G. Chevrette, Susan Egbert, Sanghoon Lee, David Meijer, Michael J. J. Recchia, Zachary L. Reitz, Jeffrey A. van Santen, Nelly Selem-Mojica, Thomas Torring, Liana Zaroubi, Mohammad Alanjary, Gajender Aleti, Cesar Aguilar, Suhad A. A. Al-Salihi, Hannah E. Augustijn, J. Abraham Avelar-Rivas, Luis A. Avitia-Dominguez, Francisco Barona-Gomez, Jordan Bernaldo-Aguero, Vincent A. Bielinski, Friederike Biermann, Thomas J. Booth, Victor J. Carrion Bravo, Raquel Castelo-Branco, Fernanda O. Chagas, Pablo Cruz-Morales, Chao Du, Katherine R. Duncan, Athina Gavriilidou, Damien Gayrard, Karina Gutierrez-Garcia, Kristina Haslinger, Eric J. N. Helfrich, Justin J. J. van der Hooft, Afif P. Jati, Edward Kalkreuter, Nikolaos Kalyvas, Kyo B. Kang, Satria Kautsar, Wonyong Kim, Aditya M. Kunjapur, Yong-Xin Li, Geng-Min Lin, Catarina Loureiro, Joris J. R. Louwen, Nico L. L. Louwen, George Lund, Jonathan Parra, Benjamin Philmus, Bita Pourmohsenin, Lotte J. U. Pronk, Adriana Rego, Devasahayam Arokia Balaya Rex, Serina Robinson, L. Rodrigo Rosas-Becerra, Eve T. Roxborough, Michelle A. Schorn, Darren J. Scobie, Kumar Saurabh Singh, Nika Sokolova, Xiaoyu Tang, Daniel Udwary, Aruna Vigneshwari, Kristiina Vind, Sophie P. J. M. Vromans, Valentin Waschulin, Sam E. Williams, Jaclyn M. Winter, Thomas E. Witte, Huali Xie, Dong Yang, Jingwei Yu, Mitja Zdouc, Zheng Zhong, Jerome Collemare, Roger G. Linington, Tilmann Weber, Marnix H. Medema
Summary: With the increasing amount of genomic data, (meta)genome mining plays a critical role in discovering pharmaceutical drugs and other materials. MIBiG is a standardized data format and online database for describing and characterizing biosynthetic gene clusters. MIBiG 3.0 is an update of the database that includes validation, re-annotation, and new entries.
NUCLEIC ACIDS RESEARCH
(2023)
Article
Microbiology
Joris J. R. Louwen, Marnix H. Medema, Justin J. J. van der Hooft
Summary: Integrative genome and metabolome mining is a popular method for characterizing specialized metabolites and their producers. To address the issue of too many candidate links, a feature-based correlation method is introduced to match compound classes between biosynthetic gene clusters (BGCs) and mass fragmentation spectra (MS/MS).
Article
Oncology
Ossia M. Eichhoff, Corinne I. Stoffel, Jan Kasler, Luzia Briker, Patrick Turko, Gergely Karsai, Nina Zila, Verena Paulitschke, Phil F. Cheng, Alexander Leitner, Andrea Bileck, Nicola Zamboni, Anja Irmisch, Zsolt Balazs, Aizhan Tastanova, Susana Pascoal, Pal Johansen, Rebekka Wegmann, Julien Mena, Alaa Othman, Vasanthi S. Viswanathan, Judith Wenzina, Andrea Aloia, Annalisa Saltari, Andreas Dzung, Michael Krauthammer, Stuart L. Schreiber, Thorsten Hornemann, Martin Distel, Berend Snijder, Reinhard Dummer, Mitchell P. Levesque
Summary: The clinical management of NRAS-mutated melanomas is challenging due to resistance that arises through genetic, transcriptional, and metabolic adaptation. However, the adoption of a mesenchymal phenotype with a quiescent metabolic program in NRAS-mutated melanoma cells confers sensitivity to reactive oxygen species (ROS) induction, which can be inhibited by ROS inducers in combination with MAPK pathway inhibitors. The findings suggest that targeting both metabolic reprogramming and MAPK signaling could improve patient treatment in melanoma and other cancers.
Article
Multidisciplinary Sciences
Kathleen E. Kyle, Sara P. Puckett, Andres Mauricio Caraballo-Rodriguez, Jose Rivera-Chavez, Robert M. Samples, Cody E. Earp, Huzefa A. Raja, Cedric J. Pearce, Madeleine Ernst, Justin J. J. van der Hooft, Madison E. Adams, Nicholas H. Oberlies, Pieter C. Dorrestein, Jonathan L. Klassen, Marcy J. Balunas
Summary: This study reveals that Trichoderma spp. can act as previously unrecognized pathogens of Trachymyrmex septentrionalis fungus gardens. The ants detect and respond to Trichoderma infections through specific secondary metabolites called peptaibols. This discovery is important for understanding ant fungiculture behavior and the protective mechanisms of fungus gardens.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2023)
Article
Multidisciplinary Sciences
Niek F. de Jonge, Joris J. R. Louwen, Elena Chekmeneva, Stephane Camuzeaux, Femke J. Vermeir, Robert S. Jansen, Florian Huber, Justin J. J. van der Hooft
Summary: The authors have developed a machine learning approach, MS2Query, to facilitate chemical discovery in mass spectral libraries. This tool increases the annotation rate and aids in assessing novelty in metabolomics datasets. By integrating mass spectral embedding-based chemical similarity predictors and detected precursor masses, MS2Query offers a more reliable and efficient alternative for searching structurally related molecules in metabolomics studies.
NATURE COMMUNICATIONS
(2023)
Article
Endocrinology & Metabolism
Anand Kumar Sharma, Tongtong Wang, Alaa Othman, Radhika Khandelwal, Miroslav Balaz, Salvatore Modica, Nicola Zamboni, Christian Wolfrum
Summary: Emerging evidence suggests the existence of constant basal lipolysis and re-esterification of fatty acids. In this study, the role of lipolysis coupled to re-esterification under basal conditions was investigated. The results showed that DGAT1 and DGAT2 mediated re-esterification plays a role in regulating fatty acid oxidation and mitochondrial fuel utilization.
MOLECULAR METABOLISM
(2023)
Article
Biochemistry & Molecular Biology
Joe Wandy, Ross McBride, Simon Rogers, Nikolaos Terzis, Stefan Weidt, Justin J. J. van der Hooft, Kevin Bryson, Ronan Daly, Vinny Davies
Summary: This study systematically compares the performance of Data-Dependent Acquisition (DDA) and Data-Independent Acquisition (DIA) modes in untargeted metabolomics using simulation and actual mass spectrometer validation. The results show that the performance of these methods varies with the average number of co-eluting ions. The study highlights the significance of simulation in optimizing data acquisition methods and provides valuable insights into the strengths and limitations of DDA and DIA.
FRONTIERS IN MOLECULAR BIOSCIENCES
(2023)
Article
Endocrinology & Metabolism
Karin H. U. Meier, Julian Trouillon, Hai Li, Melanie Lang, Tobias Fuhrer, Nicola Zamboni, Shinichi Sunagawa, Andrew J. Macpherson, Uwe Sauer
Summary: Anatomically resolved maps of small molecules reveal distinct spatial patterns throughout the gut of colonized and germ-free mice, which can be associated with specific microorganisms. The map of the longitudinal metabolome in the gut of healthy mice shows a shift from amino acids to organic acids, vitamins, and nucleotides along the gut. Comparisons between colonized and germ-free mice help identify the origin of metabolites and suggest specific microbial influence on the metabolome.
Article
Nutrition & Dietetics
Alexis C. Wood, Goncalo Graca, Meghana Gadgil, Mackenzie K. Senn, Matthew A. Allison, Ioanna Tzoulaki, Philip Greenland, Timothy Ebbels, Paul Elliott, Mark O. Goodarzi, Russell Tracy, Jerome I. Rotter, David Herrington
Summary: This study investigated the relationship between red meat intake and inflammation. The results showed no significant association between processed or unprocessed red meat and markers of inflammation. However, unprocessed red meat intake was inversely associated with the plasma metabolite glutamine, which was also inversely associated with C-reactive protein levels.
AMERICAN JOURNAL OF CLINICAL NUTRITION
(2023)
Article
Nutrition & Dietetics
Alexis C. Wood, Mark O. Goodarzi, Mackenzie K. Senn, Meghana D. Gadgil, Goncalo Graca, Matthew A. Allison, Ioanna Tzoulaki, Michael Y. Mi, Philip Greenland, Timothy Ebbels, Paul Elliott, Russell P. Tracy, David M. Herrington, Jerome I. Rotter
Summary: Avocado intake is associated with metabolomic biomarkers related to glycemia. These biomarkers are strongly associated with lower fasting glucose, lower fasting insulin, and lower incidence of type 2 diabetes. However, the association between avocado intake and fasting insulin is attenuated when controlling for body mass index.
JOURNAL OF NUTRITION
(2023)
Review
Pharmacology & Pharmacy
Mitja M. Zdouc, Justin J. J. van der Hooft, Marnix H. Medema
Summary: Ribosomally synthesized and post-translationally modified peptides (RiPPs) are chemically diverse metabolites with potent biological activities, making them attractive targets for drug development. Genome mining is a promising approach for discovering new classes of RiPPs, but the lack of signature genes shared among different RiPP classes hampers its accuracy. Integrating genomics and metabolomics data through compatible software tools is a potential solution, and several new approaches have been developed. This review discusses the challenges and opportunities in data integration and the development of new bioactive RiPPs.
TRENDS IN PHARMACOLOGICAL SCIENCES
(2023)
Article
Biochemical Research Methods
Andrei Dmitrenko, Michelle Reid, Nicola Zamboni
Summary: We propose a new method, RALPS, for the normalization of multi-batch untargeted metabolomics data using deep adversarial learning. RALPS outperforms six state-of-the-art methods for batch correction, preserving biological identity, spectral properties, and coefficients of variation. It demonstrates good scalability, robustness, ability to handle missing values, and adaptability to different experimental designs.
