microbioTA: an atlas of the microbiome in multiple disease tissues of Homo sapiens and Mus musculus

Wang, Ping; Zhang, Sainan; He, Guo-You; Du, Meiyu; Qi, Changlu; Liu, Ruyue; Zhang, Siyuan; Liang, Cheng; Shi, Lei; Zhang, Xue

doi:10.1093/nar/gkac851

Cited by 15 publications

(3 citation statements)

References 37 publications

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“…The returning canSAR database ( 78 ), which reports updates including druggability assessments using AF2 models, is joined by the ASCancer Atlas ( 79 ) that focuses on oncogenic splicing events, including annotation of upstream regulators and downstream impact; and by CREAMMIST ( 80 ), which offers an improved integrative understanding of cancer cell drug responses. Two new databases, BIC ( 81 ) and microbioTA ( 82 ) recognise the importance of the microbiota in cancer, profiling composition and abundance at different sites in comparison with controls. For drug development PubChem is a foundational resource and its update here ( 83 ) reports on 120 new data sources, with patent coverage particularly strengthened.…”

Section: New and Updated Databasesmentioning

confidence: 99%

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

Rigden

Fernández

2023

Nucleic Acids Research

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The 2023 Nucleic Acids Research Database Issue contains 178 papers ranging across biology and related fields. There are 90 papers reporting on new databases and 82 updates from resources previously published in the Issue. Six more papers are updates from databases most recently published elsewhere. Major nucleic acid databases reporting updates include Genbank, ENA, ChIPBase, JASPAR, mirDIP and the Issue's first Breakthrough Article, NACDDB for Circular Dichroism data. Updates from BMRB and RCSB cover experimental protein structural data while AlphaFold 2 computational structure predictions feature widely. STRING and REBASE are stand-out updates in the signalling and enzymes section. Immunology-related databases include CEDAR, the second Breakthrough Article, for cancer epitopes and receptors alongside returning IPD-IMGT/HLA and the new PGG.MHC. Genomics-related resources include Ensembl, GWAS Central and UCSC Genome Browser. Major returning databases for drugs and their targets include Open Targets, DrugCentral, CTD and Pubchem. The EMPIAR image archive appears in the Issue for the first time. The entire database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, revisiting 463 entries, adding 92 new resources and eliminating 96 discontinued URLs so bringing the current total to 1764 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

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Section: New and Updated Databasesmentioning

confidence: 99%

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

Rigden

Fernández

2023

Nucleic Acids Research

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“…This conversion is commonly known as feature extraction (Basith et al, 2020;Dao et al, 2022b;Zhang Z.-Y. et al, 2022;Hunt et al, 2022;Karuna Nidhi et al, 2022;Sun et al, 2022;Tran and Nguyen, 2022;Wang et al, 2022;Yang et al, 2022). The amino acid composition (ACC) of the protein has a great impact on protein classification research (Awais et al, 2021;Shoombuatong et al, 2022b;Manavalan and Patra, 2022;Rout et al, 2022;Zhu et al, 2022).…”

Section: Feature Encodingmentioning

confidence: 99%

Recognition of outer membrane proteins using multiple feature fusion

Su¹,

Qian²,

Yang³

et al. 2023

Front. Genet.

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Introduction: Outer membrane proteins are crucial in maintaining the structural stability and permeability of the outer membrane. Outer membrane proteins exhibit several functions such as antigenicity and strong immunogenicity, which have potential applications in clinical diagnosis and disease prevention. However, wet experiments for studying OMPs are time and capital-intensive, thereby necessitating the use of computational methods for their identification.Methods: In this study, we developed a computational model to predict outer membrane proteins. The non-redundant dataset consists of a positive set of 208 outer membrane proteins and a negative set of 876 non-outer membrane proteins. In this study, we employed the pseudo amino acid composition method to extract feature vectors and subsequently utilized the support vector machine for prediction.Results and Discussion: In the Jackknife cross-validation, the overall accuracy and the area under receiver operating characteristic curve were observed to be 93.19% and 0.966, respectively. These results demonstrate that our model can produce accurate predictions, and could serve as a valuable guide for experimental research on outer membrane proteins.

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“…Microbial communities are thought to influence the initiation, progression, metastasis, and response to the treatment of a variety of cancers ( Cullin et al, 2021 ; Qi et al, 2022 ; Wang et al, 2022 ). In addition to gut microbes, microbes in other niches may influence host physiology.…”

Section: Introductionmentioning

confidence: 99%

The microbiome types of colorectal tissue are potentially associated with the prognosis of patients with colorectal cancer

Zhao

et al. 2023

Front. Microbiol.

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As the second leading cause of cancer worldwide, colorectal cancer (CRC) is associated with a poor prognosis. Although recent studies have explored prognostic markers in patients with CRC, whether tissue microbes carry prognostic information remains unknown. Here, by assessing the colorectal tissue microbes of 533 CRC patients, we found that Proteobacteria (43.5%), Firmicutes (25.3%), and Actinobacteria (23.0%) dominated the colorectal tissue microbiota, which was different from the gut microbiota. Moreover, two clear clusters were obtained by clustering based on the tissue microbes across all samples. By comparison, the relative abundances of Proteobacteria and Bacteroidetes in cluster 1 were significantly higher than those in cluster 2; while compared with cluster 1, Firmicutes and Actinobacteria were more abundant in cluster 2. In addition, the Firmicutes/Bacteroidetes ratios in cluster 1 were significantly lower than those in cluster 2. Further, compared with cluster 2, patients in cluster 1 had relatively poor survival (Log-rank test, p = 0.0067). By correlating tissue microbes with patient survival, we found that the relative abundance of dominant phyla, including Proteobacteria, Firmicutes, and Bacteroidetes, was significantly associated with survival in CRC patients. Besides, the co-occurrence network of tissue microbes at the phylum level of cluster 2 was more complicated than that of cluster 1. Lastly, we detected some pathogenic bacteria enriched in cluster 1 that promote the development of CRC, thus leading to poor survival. In contrast, cluster 2 showed significant increases in the abundance of some probiotics and genera that resist cancer development. Altogether, this study provides the first evidence that the tissue microbiome of CRC patients carries prognostic information and can help design approaches for clinically evaluating the survival of CRC patients.

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microbioTA: an atlas of the microbiome in multiple disease tissues of Homo sapiens and Mus musculus

Cited by 15 publications

References 37 publications

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

Recognition of outer membrane proteins using multiple feature fusion

The microbiome types of colorectal tissue are potentially associated with the prognosis of patients with colorectal cancer

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