Review
Cell Biology
Tao Wen, Guoqing Niu, Tong Chen, Qirong Shen, Jun Yuan, Yong-Xin Liu
Summary: With the advancement of sequencing technology, numerous microbiome studies have been published, leading to the development of related analysis tools. This study organizes and classifies 324 common R packages for microbiome analysis, which can assist researchers in quickly finding suitable tools for their analysis.
Article
Biotechnology & Applied Microbiology
Rong Guo, Wei Zhang, Wei Shen, Guoliang Zhang, Taifeng Xie, Ling Li, Jiacuo Jinmei, Yiduan Liu, Fanyong Kong, Baozhu Guo, Benke Li, Yujiang Sun, Shuqin Liu
Summary: In this study, the gut microbiome of donkeys from six different regions was sequenced, revealing differences in composition and function of gut microbes among different geographic regions. This study is valuable for donkey gut microbiome research.
Article
Computer Science, Hardware & Architecture
Zied Aouini, Adrian Pekar
Summary: This paper discusses the design and implementation of NFStream, a flexible network data analysis framework that provides real-time statistical analysis and reliable ground truth for modern network usage. This framework serves as a common research platform to stimulate research and develop more efficient and reproducible solutions in network traffic analytics.
Article
Gastroenterology & Hepatology
Wenli Tang, Huimin Zheng, Shuangbin Xu, Pan Li, Li Zhan, Xiao Luo, Zehan Dai, Qianwen Wang, Guangchuang Yu
Summary: The gut metabolome plays a crucial role in the relationship between gut microbiota and the host, and has great potential for diagnosis and therapy. This study developed a computational framework called Microbe-Metabolite INteractions-based metabolic profiles Predictor (MMINP) to predict the metabolic profiles associated with the gut microbiota. The predictive value of MMINP was demonstrated and the factors influencing the prediction performance of data-driven methods were identified.
Article
Endocrinology & Metabolism
Wanglong Gou, Chu-wen Ling, Yan He, Zengliang Jiang, Yuanqing Fu, Fengzhe Xu, Zelei Miao, Ting-yu Sun, Jie-sheng Lin, Hui-lian Zhu, Hongwei Zhou, Yu-ming Chen, Ju-Sheng Zheng
Summary: Our study identified core gut microbial features associated with type 2 diabetes risk and future glucose increment using an interpretable machine learning framework. We also confirmed the relationship between these features and type 2 diabetes through human fecal sample transplantation to germ-free mice. Additionally, we found body fat distribution to be a key factor modulating the gut microbiome-type 2 diabetes relationship.
Article
Biochemical Research Methods
Tang Li, Yanbin Yin
Summary: The pan-genome analysis of metagenome-assembled genomes (MAGs) can be affected by issues such as fragmentation, incompleteness, and contamination. In this study, the researchers conducted a critical assessment of pan-genomics by comparing the results of complete bacterial genomes and simulated MAGs. The findings show that incompleteness leads to significant loss of core genes, while contamination mainly affects accessory genomes. Lowering the core gene threshold and using gene prediction algorithms that consider fragmented genes can alleviate the loss, but to a limited extent. The study concludes that new pan-genome analysis tools specifically for MAGs are needed.
BRIEFINGS IN BIOINFORMATICS
(2022)
Article
Multidisciplinary Sciences
Nicole L. Laia, Patrick C. Barko, Drew R. Sullivan, Maureen A. McMichael, David A. Williams, Jennifer M. Reinhart
Summary: Numerous studies in humans and rodents have shown the role of the gastrointestinal microbiome in diabetes mellitus. However, little is known about the gut microbiome in dogs with diabetes. This pilot study aimed to characterize the gastrointestinal microbiome in newly diagnosed diabetic dogs and explore its associations with glycemic control. The findings suggest that changes in the gut microbiome may be related to the progression and control of diabetes in dogs.
Article
Immunology
Xian-hua Xie, Yu-jie Huang, Guo-sheng Han, Zu-guo Yu, Yuan-lin Ma
Summary: This study proposes a multifractal analysis for metagenomic research, finding that metagenomes exhibit self-similarity by visualizing the chaotic game representation. The multifractal dimension is calculated and correlated with traditional species diversity indices, and the results reveal differences based on the age of infants' gut microbiomes.
FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY
(2023)
Article
Biotechnology & Applied Microbiology
Ping Li, Jiyang Jiang, Yifei Li, Yue Lan, Fan Yang, Jiao Wang, Yuxin Xie, Fei Xiong, Jinhui Wu, Hanmin Liu, Zhenxin Fan
Summary: The study observed significant differences in the gut microbiome of obese children compared to controls, with the bacterial pathogen Campylobacter rectus significantly more abundant in obese children. Functional annotation of microbial genes indicated the presence of gut inflammation in obese children, while the gut microbiomes of overweight children were in a transitional state between obese and control children. Additionally, Trichuris trichiura was found to be significantly more abundant in the guts of obese Mexican children compared to obese Chinese children, highlighting differences in gut microbial composition between populations.
Article
Medicine, General & Internal
Zhangling Chen, Djawad Radjabzadeh, Lianmin Chen, Alexander Kurilshikov, Maryam Kavousi, Fariba Ahmadizar, M. Arfan Ikram, Andre G. Uitterlinden, Alexandra Zhernakova, Jingyuan Fu, Robert Kraaij, Trudy Voortman
Summary: This study found that higher microbiome alpha diversity, as well as more butyrate-producing gut bacteria, were associated with lower incidence of type 2 diabetes and reduced levels of insulin resistance in individuals without diabetes, providing insights into the etiology, pathogenesis, and potential treatment of type 2 diabetes.
Review
Biochemistry & Molecular Biology
Nikolai V. Ravin, Tatyana S. Rudenko, Dmitry D. Smolyakov, Alexey V. Beletsky, Maria V. Gureeva, Olga S. Samylina, Margarita Yu. Grabovich
Summary: Representatives of the genus Thiothrix are filamentous, sulfur-oxidizing bacteria that inhabit flowing waters with counter-oriented sulfide and oxygen gradients. Traditional phylogenetic markers, such as the 16S rRNA gene, are not effective for species differentiation in this genus, and genome analysis is required for accurate classification.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Agriculture, Dairy & Animal Science
Dafei Yin, Youli Wang, Liqun Wang, Yuqin Wu, Xiaoyi Bian, Samuel E. Aggrey, Jianmin Yuan
Summary: This study evaluated the proteomic profile of newly harvested corn and its influence on intestinal microbiota in broiler chickens. The results showed that storage of newly harvested corn significantly affected the properties of corn and the performance of broiler chickens.
JOURNAL OF ANIMAL SCIENCE AND BIOTECHNOLOGY
(2022)
Article
Fisheries
Wei Ye, Yao Zheng, Yi Sun, Quanjie Li, Haojun Zhu, Gangchun Xu
Summary: Resveratrol (RES) has immunological enhancement effects on Oreochromis niloticus. RES administration increases hepatic hemosiderin and intestinal goblet cells. The PPAR signaling pathway may be involved in the lipid metabolism in immune-related organs affected by RES supplementation.
FISH & SHELLFISH IMMUNOLOGY
(2023)
Article
Environmental Sciences
Ayixon Sanchez-Reyes, Itzel Gaytan, Julian Pulido-Garcia, Manuel Burelo, Martin Vargas-Suarez, M. Javier Cruz-Gomez, Herminia Loza-Tavera
Summary: Plastic accumulation is a worldwide problem and polyurethane is a particularly difficult plastic to degrade. This study explores the ability of the BP6 microbial community to degrade a commercial coating containing a polyether polyurethane copolymer and various additives. The study identifies new metabolic pathways and suggests that the BP6 community could be a potential tool for polyurethane bio-recycling.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Automation & Control Systems
Xiang-Kun Zhao, Xiao-Min Zhu, Kai-Yuan Bai, Run-Tong Zhang
Summary: This study proposes a novel FMEA method that utilizes picture fuzzy sets theory to address the challenges in existing methods, such as difficulty in assessment expression and acquisition, imprecision in assessment aggregation, and missing relationships among risk factors. The method simplifies the expert evaluation process through a flexible knowledge acquisition framework, standardizes non-fuzzy values using a strategy-based picture fuzzy conversion method, improves assessment aggregation accuracy with a picture fuzzy evidential reasoning method, and establishes alternative models using picture fuzzy Petri nets to describe the relationships among risk factors.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)