GMrepo: a database of curated and consistently annotated human gut metagenomes

Wu, Sicheng; Sun, Chuqing; Li, Yanze; Wang, Teng; Jia, Longhao; Lai, Senying; Yang, Ya‐Ling; Luo, Pengyu; Dai, Die; Yang, Yong-Qing; Luo, Qibin; Gao, Na; Ning, Kang; He, Lijie; Zhao, Xing‐Ming; Chen, Weihua

doi:10.1093/nar/gkz764

Cited by 120 publications

(106 citation statements)

References 42 publications

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“…Other similar resources that have been developed subsequently are Microbiome Learning Repo (ML Repo (Vangay, Hillmann and Knights 2019 )) and Data Repository for Gut Microbiota (GMRepo (Wu et al . 2020 )). ML Repo is a public, web-based repository of 33 curated classification and regression tasks from 15 already published datasets.…”

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confidence: 99%

The food-gut axis: lactic acid bacteria and their link to food, the gut microbiome and human health

Filippis

Pasolli

2020

FEMS Microbiology Reviews

183

108

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Abstract Lactic acid bacteria (LAB) are present in foods, the environment and the animal gut, although fermented foods (FFs) are recognized as the primary niche of LAB activity. Several LAB strains have been studied for their health-promoting properties and are employed as probiotics. FFs are recognized for their potential beneficial effects, which we review in this article. They are also an important source of LAB, which are ingested daily upon FF consumption. In this review, we describe the diversity of LAB and their occurrence in food as well as the gut microbiome. We discuss the opportunities to study LAB diversity and functional properties by considering the availability of both genomic and metagenomic data in public repositories, as well as the different latest computational tools for data analysis. In addition, we discuss the role of LAB as potential probiotics by reporting the prevalence of key genomic features in public genomes and by surveying the outcomes of LAB use in clinical trials involving human subjects. Finally, we highlight the need for further studies aimed at improving our knowledge of the link between LAB-fermented foods and the human gut from the perspective of health promotion.

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confidence: 99%

The food-gut axis: lactic acid bacteria and their link to food, the gut microbiome and human health

Filippis

Pasolli

2020

FEMS Microbiology Reviews

183

108

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“…Thus, Pseudomonas is a prominent biomarker for brain metastasis in sputum. Pseudomonas consists of a groups of aerobic, Gram-negative and rod-shaped bacteria [1] that are associated with many human diseases but are relatively rare in the healthy gut (see https://gmrepo.humangut.info/species/286 for an overview their prevalence and abundances in gut microbiota associated with human health and diseases [45]). According to a MAPseq tool [46], which assigns 16S sequencing reads to distinct taxa with confidence scores, most of the Pseudomonas reads could be reliably identified as Pseudomonas aeruginosa (see Methods for details) .…”

Section: Resultsmentioning

confidence: 99%

Alterations of human lung and gut microbiome in non-small cell lung carcinomas and distant metastasis

Lü

Gao

Wei

et al. 2020

Preprint

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25Background 26Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related deaths 27 worldwide. Although dysbiosis of lung and gut microbiota have been associated with 28 NSCLC, their relative contributions are unclear; in addition, their roles in distant metastasis 29 (DM) are still illusive. 30 Results 31We surveyed the fecal and sputum (as a proxy for lung) microbiota in healthy controls and 32 NSCLC patients of various stages, and found significant perturbations of gut-and sputum-33 microbiota in patients with NSCLC and DM. Machine-learning models combining both 34 microbiota (mixed models) performed better than either dataset in patient stratification, 35with the highest area under the curve (AUC) value of 0.842. Sputum-microbiota 36 contributed more than the gut in the mixed models; in addition, sputum-only models 37 performed similarly to the mixed models in most cases. Several microbial-biomarkers were 38 shared by both microbiota, indicating their similar roles at distinct body sites. 39Microbial-biomarkers of distinct disease stages were mostly shared, suggesting 40 biomarkers for distant metastasis could be acquired early. Furthermore, Pseudomonas 41 aeruginosa, a species previously associated with wound infections, was significantly more 42 3 abundant in brain metastasis, indicating distinct types of DMs could have different 43 microbial-biomarkers. 44 Conclusion 45Our results indicate that alterations of sputum-microbiota have stronger relationships with 46 NSCLC and distant metastasis than the gut, and strongly support the feasibility of 47 metagenome-based non-invasive disease diagnosis and risk evaluation. 48 49 Keywords: gut microbiota, lung microbiota, machine learning, patient stratification, 50 NSCLC, distant metastasis, brain metastasis 51 52 4 53 Background 54 Lung cancer (LC) is the leading cause of cancer-related deaths mortality worldwide, with 55 non-small cell lung cancer (NSCLC) being the most common form of LC [1]. Despite the 56 recent development of therapies for NSCLC, tumor metastasis is the main cause of 57 recurrence and mortality in patients with NSCLC [1]. One of the key challenges is the low 58 heritability of lung cancer susceptibility revealed by genetic studies: although numerous 59 studies have established the important roles of somatic mutations as well as inheritable 60 familial risks [2, 3], the genetic influence can only explain 3~15% of the heritability [4, 5], 61 depending on the surveyed population. 62 Conversely, non-genetic factors, including life styles, environmental factors and lung 63 and gut microbes are believed to contribute mostly to the disease. Especially, numerous 64 recent studies have shown that both lung and gut microbiota are involved in the 65 development of LC [6-8]. For example, researchers have used samples from 66 bronchoalveolar fluid (BALF), tissues and spontaneous sputum of lung cancer patients for 67 bacterial identification and microbiome characterization [7, 9-11]. When compared with 68 healthy controls, researchers have id...

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“…As a proof-of-concept study, we chose to focus on the EOS species F. prausnitzii . This species represents approximately 5 to 10% of the healthy gut microbiota [12], it has been associated with a number of favorable outcomes in various disease conditions, including lower risk of postoperative recurrence of ileal Crohn’s Disease [13] and improved response to immune check point blockers [14, 15]. Several different mechanisms have been proposed to explain beneficial anti-inflammatory effects, including the production of specific molecules that inhibit the NF-κB pathway [16] or the production of extracellular polymeric matrix that modulates IL-10 and IL-12 production in a TLR-2 dependent way [17, 18].…”

Section: Discussionmentioning

confidence: 99%

Sorting and cultivation ofFaecalibacterium prausnitziifrom fecal samples using flow cytometry in anaerobic conditions

Bellais

Nehlich

Duquenoy

et al. 2020

Preprint

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BackgroundThere is a growing interest in using gut commensal bacteria as ‘next generation’ probiotics. However, this approach is still hampered by the fact that there are few or no strains available for specific species that are difficult to cultivate. Our objective was therefore to adapt flow cytometry and cell sorting to be able to detect, separate, isolate and cultivate new strains of Extremely Oxygen Sensitive (EOS) species from fecal material, focusing on Faecalibacterium prausnitzii as a proof-of-concept.ResultsA BD Influx® cell sorter was equipped with a glovebox that covers the sorting area. This box is flushed with nitrogen to deplete oxygen in the enclosure. Several non-specific staining methods including Wheat Germ Agglutinin (WGA), Vancomycin BODIPY™ and LIVE/DEAD BacLight were evaluated with three different strains of the EOS species F. prausnitzii. In parallel, we generated polyclonal antibodies directed against this species by immunizing rabbits with heat-inactivated bacteria. Anaerobic conditions were maintained during the full process, resulting in only minor viability loss during sorting and culture of unstained F. prausnitzii reference strains. In addition, staining solutions did not severely impact bacterial viability while allowing discrimination between groups of strains. Efficient detection was achieved using polyclonal antibodies directed against heat-fixed bacteria. Finally, we were able to detect, isolate and cultivate a variety of F. prausnitzii strains from healthy volunteer’s fecal samples using WGA staining and antibodies. These strains present markedly different phenotypes, thus confirming the heterogeneity of the species.ConclusionsCell-sorting in anaerobic conditions is a promising tool for the study of fecal microbiota. It gives the opportunity to quickly analyze microbial populations and to sort strains of interest using specific antibodies, thus opening new avenues for targeted culturomics experiments.

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GMrepo: a database of curated and consistently annotated human gut metagenomes

Cited by 120 publications

References 42 publications

The food-gut axis: lactic acid bacteria and their link to food, the gut microbiome and human health

The food-gut axis: lactic acid bacteria and their link to food, the gut microbiome and human health

Alterations of human lung and gut microbiome in non-small cell lung carcinomas and distant metastasis

Sorting and cultivation ofFaecalibacterium prausnitziifrom fecal samples using flow cytometry in anaerobic conditions

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