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Estrada R, Porras T, Romero Y, Pérez WE, Vilcara EA, Cruz J, Arbizu CI. Soil depth and physicochemical properties influence microbial dynamics in the rhizosphere of two Peruvian superfood trees, cherimoya and lucuma, as shown by PacBio-HiFi sequencing. Sci Rep 2024; 14:19508. [PMID: 39174594 PMCID: PMC11341828 DOI: 10.1038/s41598-024-69945-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 08/12/2024] [Indexed: 08/24/2024] Open
Abstract
The characterization of soil microbial communities at different depths is essential to understand their impact on nutrient availability, soil fertility, plant growth and stress tolerance. We analyzed the microbial community at three depths (3 cm, 12 cm, and 30 cm) in the native fruit trees Annona cherimola (cherimoya) and Pouteria lucuma (lucuma), which provide fruits in vitamins, minerals, and antioxidants. We used PacBio-HiFi, a long-read high-throughput sequencing to explore the composition, diversity and putative functionality of rhizosphere bacterial communities at different soil depths. Bacterial diversity, encompassing various phyla, families, and genera, changed with depth. Notable differences were observed in the alpha diversity indices, especially the Shannon index. Beta diversity also varied based on plant type and depth. In cherimoya soils, positive correlations with Total Organic Carbon (TOC) and Cation Exchange Capacity (CEC) were observed, but negative ones with certain cations. In lucuma soils, indices like the Shannon index exhibited negative correlations with several metals and specific soil properties. We proposed that differences between the plant rhizosphere environments may explain the variance in their microbial diversity. This study provides insights into the microbial communities present at different soil depths, highlighting the prevalence of decomposer bacteria. Further research is necessary to elucidate their specific metabolic features and overall impact on crop growth and quality.
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Affiliation(s)
- Richard Estrada
- Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru.
| | - Tatiana Porras
- Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru
| | - Yolanda Romero
- Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru
| | - Wendy E Pérez
- Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru
| | - Edgardo A Vilcara
- Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru
- Facultad de Agronomía, Universidad Nacional Agraria la Molina, Lima, 15024, Peru
| | - Juancarlos Cruz
- Dirección de Supervisión y Monitoreo en las Estaciones Experimentales Agrarias, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru
| | - Carlos I Arbizu
- Dirección de Desarrollo Tecnológico Agrario, Instituto Nacional de Innovación Agraria (INIA), Lima, 15024, Peru.
- Facultad de Ingeniería y Ciencias Agrarias, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Chachapoyas, 01001, Peru.
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Boyang H, Yanjun Y, Jing Z, Chenxin Y, Ying M, Shuwen H, Qiang Y. Investigating the influence of the gut microbiome on cholelithiasis: unveiling insights through sequencing and predictive modeling. J Appl Microbiol 2024; 135:lxae096. [PMID: 38614959 DOI: 10.1093/jambio/lxae096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 03/26/2024] [Accepted: 04/11/2024] [Indexed: 04/15/2024]
Abstract
BACKGROUND Cholelithiasis is one of the most common disorders of hepatobiliary system. Gut bacteria may be involved in the process of gallstone formation and are, therefore considered as potential targets for cholelithiasis prediction. OBJECTIVE To reveal the correlation between cholelithiasis and gut bacteria. METHODS Stool samples were collected from 100 cholelithiasis and 250 healthy individuals from Huzhou Central Hospital; The 16S rRNA of gut bacteria in the stool samples was sequenced using the third-generation Pacbio sequencing platform; Mothur v.1.21.1 was used to analyze the diversity of gut bacteria; Wilcoxon rank-sum test and linear discriminant analysis of effect sizes (LEfSe) were used to analyze differences in gut bacteria between patients suffering from cholelithiasis and healthy individuals; Chord diagram and Plot-related heat maps were used to analyze the correlation between cholelithiasis and gut bacteria; six machine algorithms were used to construct models to predict cholelithiasis. RESULTS There were differences in the abundance of gut bacteria between cholelithiasis and healthy individuals, but there were no differences in their community diversity. Increased abundance of Costridia, Escherichia flexneri, and Klebsiella pneumonae were found in cholelithiasis, while Bacteroidia, Phocaeicola, and Phocaeicola vulgatus were more abundant in healthy individuals. The top four bacteria that were most closely associated with cholelithiasis were Escherichia flexneri, Escherichia dysenteriae, Streptococcus salivarius, and Phocaeicola vulgatus. The cholelithiasis model based on CatBoost algorithm had the best prediction effect (sensitivity: 90.48%, specificity: 88.32%, and AUC: 0.962). CONCLUSION The identification of characteristic gut bacteria may provide new predictive targets for gallstone screening. As being screened by the predictive model, people at high risk of cholelithiasis can determine the need for further testing, thus enabling early warning of cholelithiasis.
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Affiliation(s)
- Hu Boyang
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Central Hospital, The Fifth School of Clinical Medicine, Zhejiang Chinese Medical University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
| | - Yao Yanjun
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Central Hospital, The Fifth School of Clinical Medicine, Zhejiang Chinese Medical University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
| | - Zhuang Jing
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Central Hospital, The Fifth School of Clinical Medicine, Zhejiang Chinese Medical University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
| | - Yan Chenxin
- Shulan International Medical school, Zhejiang Shuren University, No.848 Dongxin Road, Gongshu District, Hangzhou City, Zhejiang Province 310000, China
| | - Mei Ying
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Central Hospital, The Fifth School of Clinical Medicine, Zhejiang Chinese Medical University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
| | - Han Shuwen
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Central Hospital, The Fifth School of Clinical Medicine, Zhejiang Chinese Medical University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
| | - Yan Qiang
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Hospital, Zhejiang University School of Medicine, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of Hepatobiliary and Pancreatic Surgery, Huzhou Central Hospital, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Central Hospital, Huzhou University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Department of General Surgery, Huzhou Central Hospital, Affiliated Huzhou Central Hospital, The Fifth School of Clinical Medicine, Zhejiang Chinese Medical University, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
- Huzhou Key Laboratory of Intelligent and Digital Precision Surgery, No.1558, Sanhuan North Road, Wuxing District, Huzhou, Zhejiang Province 313000, China
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Zhang T, Li H, Ma S, Cao J, Liao H, Huang Q, Chen W. The newest Oxford Nanopore R10.4.1 full-length 16S rRNA sequencing enables the accurate resolution of species-level microbial community profiling. Appl Environ Microbiol 2023; 89:e0060523. [PMID: 37800969 PMCID: PMC10617388 DOI: 10.1128/aem.00605-23] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 08/04/2023] [Indexed: 10/07/2023] Open
Abstract
The long-read amplicon provides a species-level solution for the community. With the improvement of nanopore flowcells, the accuracy of Oxford Nanopore Technologies (ONT) R10.4.1 has been substantially enhanced, with an average of approximately 99%. To evaluate its effectiveness on amplicons, three types of microbiomes were analyzed by 16S ribosomal RNA (hereinafter referred to as "16S") amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1) in the current study. We showed the error rate, recall, precision, and bias index in the mock sample. The error rate of ONT R10.4.1 was greatly reduced, with a better recall in the case of the synthetic community. Meanwhile, in different types of environmental samples, ONT R10.4.1 analysis resulted in a composition similar to Pacbio data. We found that classification tools and databases influence ONT data. Based on these results, we conclude that the ONT R10.4.1 16S amplicon can also be used for application in environmental samples. IMPORTANCE The long-read amplicon supplies the community with a species-level solution. Due to the high error rate of nanopore sequencing early on, it has not been frequently used in 16S studies. Oxford Nanopore Technologies (ONT) introduced the R10.4.1 flowcell with Q20+ reagent to achieve more than 99% accuracy as sequencing technology advanced. However, there has been no published study on the performance of commercial PromethION sequencers with R10.4.1 flowcells on 16S sequencing or on the impact of accuracy improvement on taxonomy (R9.4.1 to R10.4.1) using 16S ONT data. In this study, three types of microbiomes were investigated by 16S ribosomal RNA (rRNA) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1). In the mock sample, we displayed the error rate, recall, precision, and bias index. We observed that the error rate in ONT R10.4.1 is significantly lower, especially when deletions are involved. First and foremost, R10.4.1 and Pacific Bioscience platforms reveal a similar microbiome in environmental samples. This study shows that the R10.4.1 full-length 16S rRNA sequences allow for species identification of environmental microbiota.
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Affiliation(s)
- Tianyuan Zhang
- National Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
- Wuhan Benagen Technology Co., Ltd., Wuhan, China
| | - Hanzhou Li
- Wuhan Benagen Technology Co., Ltd., Wuhan, China
| | - Silin Ma
- National Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
| | - Jian Cao
- Wuhan Benagen Technology Co., Ltd., Wuhan, China
| | - Hao Liao
- National Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
| | - Qiaoyun Huang
- National Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- Hubei Key Laboratory of Soil Environment and Pollution Remediation, Huazhong Agricultural University, Wuhan, China
| | - Wenli Chen
- National Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China
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