MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data

Mongad, Dattatray S.; Chavan, Nikeeta S.; Narwade, Nitin; Dixit, Kunal; Shouche, Yogesh S.; Dhotre, Dhiraj

doi:10.1016/j.ygeno.2021.08.016

Cited by 26 publications

(12 citation statements)

References 36 publications

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“…Functional prediction of 16S rRNA gene amplicon data was performed using MicFunPred tool ( Mongad et al, 2021 ) using the OTU abundance table. The analysis was conducted using Pfam database ( Li et al, 2014 ; Keller-Costa et al, 2021 ; Mistry et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Bacterial Endophytes Contribute to Rice Seedling Establishment Under Submergence

et al. 2022

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Flooding events caused by severe rains and poor soil drainage can interfere with plant germination and seedling establishment. Rice is one of the cereal crops that has unique germination strategies under flooding. One of these strategies is based on the fast coleoptile elongation in order to reach the water surface and re-establish the contact with the air. Microorganisms can contribute to plant health via plant growth promoters and provide protection from abiotic stresses. To characterise the community composition of the microbiome in rice germination under submergence, a 16S rRNA gene profiling metagenomic analysis was performed of temperate japonica rice varieties Arborio and Lamone seedlings, which showed contrasting responses in terms of coleoptile length when submerged. This analysis showed a distinct microbiota composition of Arborio seeds under submergence, which are characterised by the development of a long coleoptile. To examine the potential function of microbial communities under submergence, culturable bacteria were isolated, identified and tested for plant growth-promoting activities. A subgroup of isolated bacteria showed the capacity to hydrolyse starch and produce indole-related compounds under hypoxia. Selected bacteria were inoculated in seeds to evaluate their effect on rice under submergence, showing a response that is dependent on the rice genotype. Our findings suggest that endophytic bacteria possess plant growth-promoting activities that can substantially contribute to rice seedling establishment under submergence.

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Section: Methodsmentioning

confidence: 99%

Bacterial Endophytes Contribute to Rice Seedling Establishment Under Submergence

et al. 2022

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“…In contrast, genes of the reductive citrate cycle (Arnon-Buchanan cycle) were negatively associated with nitrate in the Chang cave ( Supplementary Table S4 ). To be note, partially sequenced 16S rRNA genes fail to distinguish taxa beyond the genus level ( Heidrich and Beule, 2022 ), and functional prediction accuracy depends on the size and research area of the reference gene database ( Mongad et al, 2021 ). Uncertainty dose exist in functional predictions based on the partially sequenced 16S rRNA gene sequence data ( Mongad et al, 2021 ; Heidrich and Beule, 2022 ), which can be overcome via metagenome sequencing in near future.…”

Section: Discussionmentioning

confidence: 99%

Nitrate determines the bacterial habitat specialization and impacts microbial functions in a subsurface karst cave

Liu

Wang²,

Wang³

et al. 2023

Front. Microbiol.

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Karst caves are usually considered as natural laboratories to study pristine microbiomes in subsurface biosphere. However, effects of the increasingly detected nitrate in underground karst ecosystem due to the acid rain impact on microbiota and their functions in subsurface karst caves have remained largely unknown. In this study, samples of weathered rocks and sediments were collected from the Chang Cave, Hubei province and subjected to high-throughput sequencing of 16S rRNA genes. The results showed that nitrate significantly impacted bacterial compositions, interactions, and functions in different habitats. Bacterial communities clustered according to their habitats with distinguished indicator groups identified for each individual habitat. Nitrate shaped the overall bacterial communities across two habitats with a contribution of 27.2%, whereas the pH and TOC, respectively, structured bacterial communities in weathered rocks and sediments. Alpha and beta diversities of bacterial communities increased with nitrate concentration in both habitats, with nitrate directly affecting alpha diversity in sediments, but indirectly on weathered rocks by lowering pH. Nitrate impacted more on bacterial communities in weathered rocks at the genus level than in sediments because more genera significantly correlated with nitrate concentration in weathered rocks. Diverse keystone taxa involved in nitrogen cycling were identified in the co-occurrence networks such as nitrate reducers, ammonium-oxidizers, and N2-fixers. Tax4Fun2 analysis further confirmed the dominance of genes involved in nitrogen cycling. Genes of methane metabolism and carbon fixation were also dominant. The dominance of dissimilatory and assimilatory nitrate reduction in nitrogen cycling substantiated nitrate impact on bacterial functions. Our results for the first time revealed the impact of nitrate on subsurface karst ecosystem in terms of bacterial compositions, interactions, and functions, providing an important reference for further deciphering the disturbance of human activities on the subsurface biosphere.

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“…However, since 16S sequencing does not provide information about the gene content of the sample, many methods have been developed to infer gene content and functions from the 16S sequence. These include popular tools such as, PICRUSt (1), Piphillin (2), Tax4Fun (3), PAPRICA (4), PanFP (5), and MicFunPred (6). Although the algorithmic steps vary, in essence, these tools utilize the relationship between phylogeny and gene content and make their predictions based on a set of closely related reference genomes (7).…”

Section: Introductionmentioning

confidence: 99%

Predicting Protein-encoding Gene Content inEscherichia coliGenomes

Nguyen

Elmore

Ihle

et al. 2023

Preprint

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In this study, we built machine learning classifiers for predicting the presence or absence of the variable genes occurring in 10-90% of all publicly available high-quality Escherichia coli genomes. The BV-BRC genus-specific protein families were used to define orthologs across the set of genomes, and a single binary classifier was built for predicting the presence or absence of each family in each genome. Each model was built using the nucleotide k-mers from a set of 100 conserved genes as features. The resulting set of 3,259 XGBoost classifiers had a per-genome average macro F1 score of 0.944 [0.943-0.945, 95% CI]. We show that the F1 scores are stable across MLSTs, and that the trend can be recapitulated through sampling with a smaller number of core genes or diverse input genomes. Surprisingly, the presence or absence of poorly annotated proteins, including hypothetical proteins, were easily predicted (F1 = 0.902 [0.898-0.906, 95% CI]). Models for proteins with horizontal gene transfer-related functions, including transposition- (F1 = 0.895 [0.882-0.907, 95% CI]), phage- (F1 = 0.872 [0.868-0.876, 95% CI]), and plasmid-related (F1 = 0.824 [0.814-0.834, 95% CI]) functions had slightly lower F1 scores, but were still accurate. Finally, we applied the models to a holdout set of 419 diverse E. coli genomes that were isolated from freshwater environmental sources and observed an average per-genome F1 score of 0.880 [0.876-0.883, 95% CI], demonstrating the extensibility of the models. Overall, this study provides a framework for predicting variable gene content using a limited amount of input sequence data.

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MicFunPred: A conserved approach to predict functional profiles from 16S rRNA gene sequence data

Cited by 26 publications

References 36 publications

Bacterial Endophytes Contribute to Rice Seedling Establishment Under Submergence

Bacterial Endophytes Contribute to Rice Seedling Establishment Under Submergence

Nitrate determines the bacterial habitat specialization and impacts microbial functions in a subsurface karst cave

Predicting Protein-encoding Gene Content inEscherichia coliGenomes

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