iMeta最新文献

{"title":"Short-term probiotic supplementation affects the diversity, genetics, growth, and interactions of the native gut microbiome","authors":"Xin Shen,&nbsp;Hao Jin,&nbsp;Feiyan Zhao,&nbsp;Lai-Yu Kwok,&nbsp;Zhixin Zhao,&nbsp;Zhihong Sun","doi":"10.1002/imt2.253","DOIUrl":"10.1002/imt2.253","url":null,"abstract":"<p>The precise mechanisms through which probiotics interact with and reshape the native gut microbiota, especially at the species and genetic levels, remain underexplored. This study employed a high-dose probiotic regimen of <i>Bifidobacterium animalis</i> subsp. <i>lactis</i> [200 billion colony forming units (CFU)/day] over 7 days among healthy participants. Weekly fecal samples were collected for metagenomic sequencing analysis. We found that probiotic intake can significantly enhance the diversity of the gut microbiome and impact single nucleotide variations, growth rates, and network interactions of the resident intestinal bacteria. These adaptive changes in the gut microbiota indicate the swift evolutionary responses of native bacteria to the ecological disturbance presented by probiotic supplementation. Notably, the microbial community appears to undergo rapid and multifaceted ecological adjustments, potentially preceding longer-term evolutionary changes. This knowledge lays the groundwork for further exploration into the mechanisms underlying probiotic-mediated modulation of the gut microbiome, highlighting the necessity of encompassing ecological and evolutionary perspectives in the design and optimization of probiotic applications.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683461/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The long-term intake of milk fat does not significantly increase the blood lipid burden in normal and high-fat diet-fed mice","authors":"Guang-Xu Ren,&nbsp;Liang He,&nbsp;Yong-Xin Liu,&nbsp;Yu-Ke Fei,&nbsp;Xiao-Fan Liu,&nbsp;Qiu-Yi Lu,&nbsp;Xin Chen,&nbsp;Zhi-Da Song,&nbsp;Jia-Qi Wang","doi":"10.1002/imt2.256","DOIUrl":"10.1002/imt2.256","url":null,"abstract":"<p>After 10 weeks of feeding C57BL/6J mice with a normal diet (ND) or a high-fat diet (HFD), a 7-week intervention with milk fat and whole milk was conducted to assess their long-term effects on host blood lipid levels. The results showed that milk fat and whole milk did not significantly elevate low-density lipoprotein cholesterol (LDL-C) in either ND- or HFD-fed mice. In ND mice, milk fat and whole milk improved gut microbiota diversity and Amplicon Sequence Variants. Key bacterial genera, such as <i>Blautia</i>, <i>Romboutsia</i>, and <i>Prevotellaceae_NK3B31_group</i>, were identified as bidirectional regulators of LDL-C and high-density lipoprotein cholesterol (HDL-C). Six unique metabolites were also linked to LDL-C and HDL-C regulation. Furthermore, an optimized machine learning model accurately predicted LDL-C (<i>R</i>² = 0.96) and HDL-C (<i>R</i>² = 0.89) based on gut microbiota data, with 80% of the top predictive features being gut metabolites influenced by milk fat and whole milk. These findings indicate that the long-term intake of milk fat does not significantly increase the blood lipid burden, and machine learning algorithms based on gut microbiota and metabolites offer novel insights for early lipid assessment and personalized nutrition strategies.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"iMeta Conference 2024: Building an innovative scientific research ecosystem for microbiome and One Health","authors":"Yao Wang,&nbsp;Huiyu Hou,&nbsp;Hao Luo,&nbsp;Jiani Xun,&nbsp;Chuang Ma,&nbsp;Haifei Yang,&nbsp;Defeng Bai,&nbsp;Salsabeel Yousuf,&nbsp;Hujie Lyu,&nbsp;Tianyuan Zhang,&nbsp;Xiulin Wan,&nbsp;Xiaofang Yao,&nbsp;Tengfei Ma,&nbsp;Yuanping Zhou,&nbsp;Zhihao Zhu,&nbsp;Meiyin Zeng,&nbsp;Sanqi An,&nbsp;Qing Bai,&nbsp;Yao Bai,&nbsp;Guodong Cao,&nbsp;Tingting Cao,&nbsp;Yongkai Cao,&nbsp;Chihmin Chang,&nbsp;Lijia Chang,&nbsp;Bo Chen,&nbsp;Dai Chen,&nbsp;Dijun Chen,&nbsp;Hanqing Chen,&nbsp;Jiali Chen,&nbsp;Jinfeng Chen,&nbsp;Wei-Hua Chen,&nbsp;Xinhai Chen,&nbsp;Yue Chen,&nbsp;Zhangran Chen,&nbsp;Cheng Cheng,&nbsp;Quan Cheng,&nbsp;Xi-Jian Dai,&nbsp;Chaowen Deng,&nbsp;Feilong Deng,&nbsp;Jingwen Deng,&nbsp;Chang-Sheng Dong,&nbsp;Lei Dong,&nbsp;Lianhui Duan,&nbsp;Yi Duan,&nbsp;Qingjie Fan,&nbsp;Chao Fang,&nbsp;Tingyu Fang,&nbsp;Wensheng Fang,&nbsp;Zhencheng Fang,&nbsp;Min Fu,&nbsp;Minjie Fu,&nbsp;Cong Gao,&nbsp;Hao Gao,&nbsp;Weiwei Gao,&nbsp;Xinrui Gao,&nbsp;Yi-Zhou Gao,&nbsp;Yan Geng,&nbsp;Wenping Gong,&nbsp;Shaohua Gu,&nbsp;Xia Gu,&nbsp;Zhengquan Gu,&nbsp;Jian-Wei Guo,&nbsp;Junjie Guo,&nbsp;Qiuyan Guo,&nbsp;Xiang Guo,&nbsp;Xiaoqian Guo,&nbsp;Dongfei Han,&nbsp;Ziyi Han,&nbsp;Yanan Hao,&nbsp;Jiale He,&nbsp;Jianquan He,&nbsp;Jianyu He,&nbsp;Ruolin He,&nbsp;Guosen Hou,&nbsp;Bin Hu,&nbsp;Haibo Hu,&nbsp;Yi Hu,&nbsp;Yongfei Hu,&nbsp;Yucan Hu,&nbsp;Guanyin Huang,&nbsp;Haiyun Huang,&nbsp;Jiaomei Huang,&nbsp;Shenghui Huang,&nbsp;Baolei Jia,&nbsp;Xingxing Jian,&nbsp;Chao Jiang,&nbsp;Kun Jiang,&nbsp;Lanyan Jiang,&nbsp;Shuaiming Jiang,&nbsp;Jian-Yu Jiao,&nbsp;Hao Jin,&nbsp;Jiajia Jin,&nbsp;Siyuan Kong,&nbsp;Xinxing Lai,&nbsp;Yuxin Leng,&nbsp;Bang Li,&nbsp;Bing Li,&nbsp;Fang Li,&nbsp;Hao Li,&nbsp;Huanjie Li,&nbsp;Jing Li,&nbsp;Kai Li,&nbsp;Lanqi Li,&nbsp;Leyuan Li,&nbsp;Minghan Li,&nbsp;Pengsong Li,&nbsp;Wei Li,&nbsp;Wei Li,&nbsp;Xianyu Li,&nbsp;Li Xuemeng,&nbsp;Yafei Li,&nbsp;Yuantao Li,&nbsp;Zhi Li,&nbsp;Liqin Liang,&nbsp;Rong Liang,&nbsp;Zhuobin Liang,&nbsp;Qingya Liu,&nbsp;Dejian Liu,&nbsp;Huiheng Liu,&nbsp;Jinchao Liu,&nbsp;Li Liu,&nbsp;Lihui Liu,&nbsp;Moyang Liu,&nbsp;Ran Liu,&nbsp;Shuai Liu,&nbsp;Tianyang Liu,&nbsp;Wei Liu,&nbsp;Wenjuan Liu,&nbsp;Xiaomin Liu,&nbsp;Yang Liu,&nbsp;Yichen Liu,&nbsp;Yina Liu,&nbsp;Yuan Liu,&nbsp;Zhe Liu,&nbsp;Zhipeng Liu,&nbsp;Zhiquan Liu,&nbsp;Chunhao Long,&nbsp;Yun Long,&nbsp;Changying Lu,&nbsp;Chao Lu,&nbsp;Cheng Lu,&nbsp;Qi Lu,&nbsp;Yaning Luan,&nbsp;Peng Luo,&nbsp;Sheng Luo,&nbsp;Ning Ma,&nbsp;Xiao-Ya Ma,&nbsp;Yan Ma,&nbsp;Wenjun Mao,&nbsp;Yuanfa Meng,&nbsp;Yan Ni,&nbsp;Yawen Ni,&nbsp;Kang Ning,&nbsp;Dongze Niu,&nbsp;Kai Peng,&nbsp;Zhengwu Peng,&nbsp;Xubo Qian,&nbsp;Zhiguang Qiu,&nbsp;Hui Qu,&nbsp;Zepeng Qu,&nbsp;Yan Ren,&nbsp;Zhigang Ren,&nbsp;Youming Shen,&nbsp;Lin Shi,&nbsp;Linlin Shi,&nbsp;Wenxuan Shi,&nbsp;Yongpeng Shi,&nbsp;Tianyuan Song,&nbsp;Xiaohui Song,&nbsp;Xiaoming Song,&nbsp;Xiaowei Song,&nbsp;Qi Su,&nbsp;Yufan Su,&nbsp;Lifang Sun,&nbsp;Qiang Sun,&nbsp;Tiefeng Sun,&nbsp;Yunke Sun,&nbsp;Hua Tang,&nbsp;Wenjing Tang,&nbsp;Tao Yu,&nbsp;Simon Tian,&nbsp;Shuo Wang,&nbsp;Bowen Wang,&nbsp;Cheng Wang,&nbsp;Wang Jin,&nbsp;Leli Wang,&nbsp;Liangliang Wang,&nbsp;Lixiao Wang,&nbsp;Mingbang Wang,&nbsp;Ming-Ke Wang,&nbsp;Pingyi Wang,&nbsp;Shaolin Wang,&nbsp;Shaopu Wang,&nbsp;Xinxia Wang,&nbsp;Xueqiang Wang,&nbsp;Mi Wei,&nbsp;Yan Wei,&nbsp;Yanxia Wei,&nbsp;Yongjun Wei,&nbsp;Chaoliang Wen,&nbsp;Xin Wen,&nbsp;Linkun Wu,&nbsp;Shengru Wu,&nbsp;Yuting Wu,&nbsp;Shuting Xia,&nbsp;Xiaodong Xia,&nbsp;Yu Xia,&nbsp;Xionggen Xiang,&nbsp;Chuanxing Xiao,&nbsp;Weihua Xiao,&nbsp;Yingping Xiao,&nbsp;Ruohan Xie,&nbsp;Rui Xing,&nbsp;Hui Xu,&nbsp;Wei Xu,&nbsp;Zhimin Xu,&nbsp;Hongliang Xue,&nbsp;Chao Yan,&nbsp;Qiu-Long Yan,&nbsp;Shaofei Yan,&nbsp;Xiuchuan Yan,&nbsp;Mengli Yang,&nbsp;Yufan Yang,&nbsp;Zhipeng Yang,&nbsp;Ziyuan Yang,&nbsp;Guixiang Yao,&nbsp;Yanlai Yao,&nbsp;Xianfu Yi,&nbsp;Chong Yin,&nbsp;Mingliang Yin,&nbsp;Shicheng Yu,&nbsp;Ying Yu,&nbsp;Yongyao Yu,&nbsp;Fusong Yuan,&nbsp;Shao-Lun Zhai,&nbsp;Bo Zhang,&nbsp;Chen Zhang,&nbsp;Fang Zhang,&nbsp;Feng-Li Zhang,&nbsp;Hengguo Zhang,&nbsp;Jinping Zhang,&nbsp;Junya Zhang,&nbsp;Kun Zhang,&nbsp;Li Zhang,&nbsp;Lin Zhang,&nbsp;Lingxuan Zhang,&nbsp;Meng Zhang,&nbsp;Qian Zhang,&nbsp;Runan Zhang,&nbsp;Tongtong Zhang,&nbsp;Tongxue Zhang,&nbsp;Weipeng Zhang,&nbsp;Yong Zhang,&nbsp;Yuchao Zhang,&nbsp;Yujun Zhang,&nbsp;Zeng Zhang,&nbsp;Zhengxiao Zhang,&nbsp;Zhi-Feng Zhang,&nbsp;Boxi Zhao,&nbsp;Yanyan Zhao,&nbsp;Yibing Zhao,&nbsp;Ziwei Zhao,&nbsp;Diwei Zheng,&nbsp;Ying Zheng,&nbsp;Wenqiang Zhi,&nbsp;Jixin Zhong,&nbsp;Xiangjian Zhong,&nbsp;Wei Zhou,&nbsp;Xin Zhou,&nbsp;Zhemin Zhou,&nbsp;Zhichao Zhou,&nbsp;Congmin Zhu,&nbsp;Feiying Zhu,&nbsp;Xiaodie Zhu,&nbsp;Yutian Zou,&nbsp;Hongling Zhou,&nbsp;Lei Lei,&nbsp;Yanliang Bi,&nbsp;Hubing Shi,&nbsp;Hui-Zeng Sun,&nbsp;Shuangxia Jin,&nbsp;Wenkai Ren,&nbsp;Lei Dai,&nbsp;Xin Wang,&nbsp;Canhui Lan,&nbsp;Hongwei Liu,&nbsp;Shuang-Jiang Liu,&nbsp;Yulong Yin,&nbsp;Chun-Lin Shi,&nbsp;Ren-You Gan,&nbsp;Fangqing Zhao,&nbsp;Jun Yu,&nbsp;Tong Chen,&nbsp;Xin Hong,&nbsp;Hua Yang,&nbsp;Bangzhou Zhang,&nbsp;Shifu Chen,&nbsp;Xiaodong Li,&nbsp;Yunyun Gao,&nbsp;Yong-Xin Liu","doi":"10.1002/imt2.251","DOIUrl":"10.1002/imt2.251","url":null,"abstract":"<p>The <i>iMeta</i> Conference 2024 provides a platform to promote the development of an innovative scientific research ecosystem for microbiome and One Health. The four key components - Technology, Research (Biology), Academic journals, and Social media - form a synergistic ecosystem. Advanced technologies drive biological research, which generates novel insights that are disseminated through academic journals. Social media plays a crucial role in engaging the public and facilitating scientific communication, thus amplifying the impact of research. Together, these elements create a self-sustaining loop that fosters continuous innovation and collaboration in the field of bioinformatics, biotechnology and microbiome research.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683455/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive multi-tissue epigenome atlas in sheep: A resource for complex traits, domestication, and breeding","authors":"Deyin Zhang,&nbsp;Jiangbo Cheng,&nbsp;Xiaolong Li,&nbsp;Kai Huang,&nbsp;Lvfeng Yuan,&nbsp;Yuan Zhao,&nbsp;Dan Xu,&nbsp;Yukun Zhang,&nbsp;Liming Zhao,&nbsp;Xiaobin Yang,&nbsp;Zongwu Ma,&nbsp;Quanzhong Xu,&nbsp;Chong Li,&nbsp;Xiaojuan Wang,&nbsp;Chen Zheng,&nbsp;Defu Tang,&nbsp;Fang Nian,&nbsp;Xiangpeng Yue,&nbsp;Wanhong Li,&nbsp;Huibin Tian,&nbsp;Xiuxiu Weng,&nbsp;Peng Hu,&nbsp;Yuanqing Feng,&nbsp;Peter Kalds,&nbsp;Zhihua Jiang,&nbsp;Yunxia Zhao,&nbsp;Xiaoxue Zhang,&nbsp;Fadi Li,&nbsp;Weimin Wang","doi":"10.1002/imt2.254","DOIUrl":"10.1002/imt2.254","url":null,"abstract":"<p>Comprehensive functional genome annotation is crucial to elucidate the molecular mechanisms of agronomic traits in livestock, yet systematic functional annotation of the sheep genome is lacking. Here, we generated 92 transcriptomic and epigenomic data sets from nine major tissues, along with whole-genome data from 2357 individuals across 29 breeds worldwide, and 4006 phenotypic data related to tail fat weight. We constructed the first multi-tissue epigenome atlas in terms of functional elements, chromatin states, and their functions and explored the utility of the functional elements in interpreting phenotypic variation during sheep domestication and improvement. Particularly, we identified a total of 753,723 nonredundant functional elements, with over 60% being novel. We found tissue-specific promoters and enhancers related to sensory abilities and immune response that were highly enriched in genomic regions influenced by domestication, while <i>longissimus dorsi</i> tissue-specific active enhancers and tail fat tissue-specific active promoters were highly enriched in genomic regions influenced by breeding and improvement. Notably, a variant, Chr13:51760995A&gt;C, located in an enhancer region, was identified as a causal variant for tail fat deposition based on multi-layered data sets. Overall, this research provides foundational resources and a successful case for future investigations of complex traits in sheep through the integration of multi-omics data sets.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683475/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiomics analysis reveals signatures of selection and loci associated with complex traits in pigs","authors":"Lei Liu,&nbsp;Guoqiang Yi,&nbsp;Yilong Yao,&nbsp;Yuwen Liu,&nbsp;Jiang Li,&nbsp;Yalan Yang,&nbsp;Mei Liu,&nbsp;Lingzhao Fang,&nbsp;Delin Mo,&nbsp;Longchao Zhang,&nbsp;Yonggang Liu,&nbsp;Yongchao Niu,&nbsp;Liyuan Wang,&nbsp;Xiaolu Qu,&nbsp;Zhangyuan Pan,&nbsp;Lei Wang,&nbsp;Muya Chen,&nbsp;Xinhao Fan,&nbsp;Yun Chen,&nbsp;Yongsheng Zhang,&nbsp;Xingzheng Li,&nbsp;Zhen Wang,&nbsp;Yijie Tang,&nbsp;Hetian Huang,&nbsp;Pengxiang Yuan,&nbsp;Yuying Liao,&nbsp;Xinjian Li,&nbsp;Zongjun Yin,&nbsp;Di Liu,&nbsp;Dongjie Zhang,&nbsp;Quanyong Zhou,&nbsp;Wangjun Wu,&nbsp;Jicai Jiang,&nbsp;Yahui Gao,&nbsp;George E. Liu,&nbsp;Lixian Wang,&nbsp;Yaosheng Chen,&nbsp;Kui Li,&nbsp;Martien A. M. Groenen,&nbsp;Zhonglin Tang","doi":"10.1002/imt2.250","DOIUrl":"https://doi.org/10.1002/imt2.250","url":null,"abstract":"<p>The genetic basis of complex traits and phenotypic differentiation remains unclear in pigs. Using nine genomes—seven of which were newly generated, high-quality de novo assembled genomes—and 1081 resequencing genomes, we built a pan-genome and identified 134.24 Mb nonredundant nonreference sequences, 1099 novel protein-coding genes, 187,927 structural variations (SVs) and 30,143,962 single-nucleotide polymorphisms (SNPs). Analysis of selective domestication revealed <i>BRCA1</i> associated with enhanced adipocyte growth and fat deposition, and <i>ABCA3</i> linked to an alleviated immune response and reduced lung injury. Integrating 162 transcriptomes and 162 methylomes of skeletal muscle across 27 developmental stages revealed the regulatory mechanism of phenotypic differentiation between Eastern and Western breeds. Artificial selection reshaped local DNA methylation status and imparted regulatory effects on the progression patterns of heterochronic genes such as <i>GHSR</i> and <i>BDH1</i>, particularly during embryonic development. Altogether, our work provides valuable resources for understanding molecular mechanisms behind phenotypic variations and enhancing the genetic improvement programs in pigs.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/imt2.250","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143252747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “Lepidium meyenii Walp (Maca)-derived extracellular vesicles ameliorate depression by promoting 5-HT synthesis via the modulation of gut–brain axis”","authors":"","doi":"10.1002/imt2.259","DOIUrl":"10.1002/imt2.259","url":null,"abstract":"<p>In Hong et al. [<span>1</span>], following details should have been corrected.</p><p>1. In page 6, “We also investigated the effect of Maca-EVs on microbial diversity and found that microbial richness as indicated by the Faith-pd and Observed features index was higher in the Maca-EVs groups (Control+Maca-EVs and UCMS+Maca-EVs).” was incorrect.</p><p>This should be: “We also investigated the effect of Maca-EVs on microbial diversity and found that microbial richness as indicated by the Faith-pd and Observed features index was lower in the Maca-EVs groups (Control+Maca-EVs and UCMS+Maca-EVs).”</p><p>2. In page 6, the sentence “Only the Faith pd index in Control + Maca EVs group was significantly lower than that in the Control group (<i>p</i> &lt; 0.05, figure 3D).” should be deleted.</p><p>3. In Figure 4, page 8 of the article, “(F) Reciprocal interactions between altered gut bacteria and serum metabolites identified by a co-occurrence network based on Spearman correlation analysis in pos mode.” was incorrect.</p><p>This should be: “(F) Reciprocal interactions between altered gut bacteria and metabolites identified by a co-occurrence network based on Spearman correlation analysis in pos mode.”</p><p>We apologize for these errors.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683467/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"EXPRESSION OF CONCERN: Intratumoral Microbiota is Associated with Prognosis in Patients with Adrenocortical Carcinoma","authors":"","doi":"10.1002/imt2.255","DOIUrl":"10.1002/imt2.255","url":null,"abstract":"<p><b>EXPRESSION OF CONCERN</b>: Y. Li, D. Zhang, M. Wang, H. Jiang, C. Feng, and Y.–X. Li, “Intratumoral Microbiota is Associated with Prognosis in Patients with Adrenocortical Carcinoma,” <i>iMeta</i> 2, no. 2 (2023): e102, https://doi.org/10.1002/imt2.102.</p><p>This Expression of Concern is for the above article, published online on 05 April 2023 in Wiley Online Library (wileyonlinelibrary.com), and has been published by agreement between the journal Editors-in-Chief, Shuang-Jiang Liu and Jingyuan Fu; iMeta Science; and John Wiley &amp; Sons Australia, Ltd.</p><p>The above article utilized data partially derived from Poore et al. [<span>1</span>], which was later retracted due to data analysis errors [<span>2</span>]. In light of this retraction and the resulting uncertainty regarding the data, readers are advised to interpret the results of the present study with caution.</p><p>The journal team and the publisher are currently investigating the concerns to determine whether it affects the conclusions of the article. The authors have agreed to re-analyze their data. In the meantime, the journal has decided to issue an Expression of Concern to inform and alert the readers.</p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683465/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Polyploidy drives autophagy to participate in plant-specific functions","authors":"Moyang Liu,&nbsp;Ming Yang,&nbsp;Heng Liang,&nbsp;Bote Luo,&nbsp;Junjie Deng,&nbsp;Lingyan Cao,&nbsp;Daojun Zheng,&nbsp;Cheng Chen","doi":"10.1002/imt2.252","DOIUrl":"10.1002/imt2.252","url":null,"abstract":"<p>Polyploidization promotes the functional diversification of autophagy in plants, expanding autophagy-associated genes (AAGs) to support processes like chloroplast division and flowering. Analysis of 92,967 AAGs in <i>Arabidopsis thaliana</i>, <i>Solanum lycopersicum, Camellia oleifera</i>, and 74 other plant species shows that 45.69% of AAGs are polyploidy-related, highlighting polyploidy's role in linking autophagy to plant-specific functions.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683458/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metagenomic analysis sheds light on the mixotrophic lifestyle of bacterial phylum Zhuqueibacterota","authors":"Zheng-Han Lian,&nbsp;Nimaichand Salam,&nbsp;Sha Tan,&nbsp;Yang Yuan,&nbsp;Meng-Meng Li,&nbsp;Yu-Xian Li,&nbsp;Ze-Tao Liu,&nbsp;Chao-Jian Hu,&nbsp;Ai-Ping Lv,&nbsp;Yu-Ting OuYang,&nbsp;Cai-Yu Lu,&nbsp;Jing-Yi Zhang,&nbsp;Ying Chen,&nbsp;Le-Bin Chen,&nbsp;Zhen-Hao Luo,&nbsp;Bin Ma,&nbsp;Zheng-Shuang Hua,&nbsp;Jian-Yu Jiao,&nbsp;Wen-Jun Li,&nbsp;Lan Liu","doi":"10.1002/imt2.249","DOIUrl":"10.1002/imt2.249","url":null,"abstract":"<p><i>Zhuqueibacterota</i> is a novel bacterial phylum proposed based on hot spring metagenomes and public metagenome-assembled genomes, classified within the <i>Fibrobacterota</i>-<i>Chlorobiota</i>-<i>Bacteroidota</i> superphylum. This globally distributed phylum consists of one class and five orders, with the majority of its members being facultative anaerobes. Notably, the order <i>Zhuqueibacterales</i> utilizes hydrogen as an electron donor for carbon fixation through the Calvin Benson Bassham cycle. Phylogenetic and metabolic analyses reveal the phylum's key role in the carbon cycle, with frequent horizontal gene transfer events influencing its evolutionary trajectory.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683472/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Targeting SLC7A11/xCT improves radiofrequency ablation efficacy of HCC by dendritic cells mediated anti-tumor immune response","authors":"Yuzhao Jin,&nbsp;Songhua Cai,&nbsp;Yang Zhou,&nbsp;Dandan Guo,&nbsp;Yuzhen Zeng,&nbsp;Wangting Xu,&nbsp;Yiting Sun,&nbsp;Yueli Shi,&nbsp;Zhiyong Xu,&nbsp;Zaoqu Liu,&nbsp;Peng Luo,&nbsp;Zhao Huang,&nbsp;Bufu Tang","doi":"10.1002/imt2.248","DOIUrl":"10.1002/imt2.248","url":null,"abstract":"<p>After RFA treatment in patients with liver cancer, the expression of <i>SLC7A11</i>/xCT and the proportion of DCs in the TME were significantly increased. <i>SLC7A11</i>/xCT is a poor prognostic marker for liver cancer and is mainly expressed in DCs in the TME. Targeting xCT in DCs combined with RFA significantly enhances anti-tumor immunity, suppressing tumor growth and offering a promising strategy for improved therapeutic outcomes in liver cancer.\u0000\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":73342,"journal":{"name":"iMeta","volume":"3 6","pages":""},"PeriodicalIF":23.7,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11683471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}