MicroScope: an integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis

Vallenet, David; Calteau, Alexandra; Dubois, Mathieu; Amours, Paul; Bazin, Adelme; Beuvin, Mylène; Burlot, Laura; Bussell, Xavier; Fouteau, Stéphanie; Gautreau, Guillaume; Lajus, Aurélie; Langlois, Jordan; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoé; Sabatet, Valentin; Médigue, Claudine

doi:10.1093/nar/gkz926

“…Future applications of PPanGGOLiN could include the prediction of genomics islands within the shell and cloud genomes. A first version of this application (Bazin et al, in preparation) is already integrated in the MicroScope genome analysis platform [43]. Next, it would be interesting to determine the architecture of these variable regions by predicting conserved gene modules using information on the occurrence of families and their genomic neighborhood in the pangenome graph.…”

Section: Resultsmentioning

confidence: 99%

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

Gautreau

¹

,

Bazin

²

,

Gachet

³

et al. 2020

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The use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. These methods usually lack multivariate statistical models to infer the partitions and the optimal number of classes and don't account for genome organization. We introduce a graph structure to model pangenomes in which nodes represent gene families and edges represent genomic neighborhood. Our method, named PPanGGOLiN, partitions nodes using an Expectation-Maximization algorithm based on multivariate Bernoulli Mixture Model coupled with a Markov Random Field. This approach takes into account the topology of the graph and the presence/absence of genes in pangenomes to classify gene families into persistent, cloud, and one or several shell partitions. By analyzing the partitioned pangenome graphs of isolate genomes from 439 species and metagenome-assembled genomes from 78 species, we demonstrate that our method is effective in estimating the persistent genome. Interestingly, it shows that the shell genome is a key element to understand genome dynamics, presumably because it reflects how genes present at intermediate frequencies drive adaptation of species, and its proportion in genomes is independent of genome size. The graph-based approach proposed by PPanGGOLiN is useful to depict the overall genomic diversity of thousands of strains in a compact structure and provides an effective basis for very large scale comparative genomics. The software is freely available at https://github.com/labgem/ PPanGGOLiN. PLOS COMPUTATIONAL BIOLOGYPLOS Computational Biology | https://doi.org/10.

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“…Future applications of PPanGGOLiN could include the prediction of genomics islands within the shell and cloud genomes. A first version of this application (Bazin et al, in preparation) is already integrated in the MicroScope genome analysis platform [39]. Next, it would be interesting to determine the architecture of these variable regions by predicting conserved gene modules using information on the 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 occurrence of families and their genomic neighborhood in the pangenome graph.…”

Section: Resultsmentioning

confidence: 99%

PPanGGOLiN: depicting microbial diversity via a partitioned pangenome graph

Gautreau

¹

,

Bazin

²

,

Gachet

³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

The use of comparative genomics for functional, evolutionary, and epidemiological studies requires methods to classify gene families in terms of occurrence in a given species. These methods usually lack multivariate statistical models to infer the partitions and the optimal number of classes and don't account for genome organization. We introduce a graph structure to model pangenomes in which nodes represent gene families and edges represent genomic neighborhood. Our method, named PPanGGOLiN, partitions nodes using an Expectation-Maximization algorithm based on multivariate Bernoulli Mixture Model coupled with a Markov Random Field. This approach takes into account the topology of the graph and the presence/absence of genes in pangenomes to classify gene families into persistent, cloud, and one or several shell partitions. By analyzing the partitioned pangenome graphs of isolate genomes from 439 species and metagenome-assembled genomes from 78 species, we demonstrate that our method is effective in estimating the persistent genome. Interestingly, it shows that the shell genome is a key element to understand genome dynamics, presumably because it reflects how genes present at intermediate frequencies drive adaptation of species, and its proportion in genomes is independent of genome size. The graph-based approach proposed by PPanGGOLiN is useful to depict the overall genomic diversity of thousands of strains in a compact structure and provides an effective basis for very large scale comparative genomics. The software is freely available at https://github.com/labgem/PPanGGOLiN.

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“…The completeness, contamination and strain heterogeneity of genome were evaluated using CheckM v1.013 (Parks et al ., 2015). Gene prediction and annotation were done using JGI-IMG/MER (Chen et al ., 2019) and MicroScope platform (Vallenet et al ., 2019). KEGG pathways were generated using KASS (Moriya et al ., 2007).…”

Section: Methodsmentioning

confidence: 99%

Physiological and genomic analysis of “CandidatusNitrosocosmicus agrestis”, an ammonia tolerant ammonia-oxidizing archaeon from vegetable soil

Liu

¹

,

Liu

²

,

Jiang

³

et al. 2019

Preprint

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The presences of ammonia tolerant ammonia-oxidizing archaea (AOA) in environments are always underestimated and their adaption to complex habitats has also rarely been reported. Here we present the physiological and genomic characteristics of an ammonia tolerant soil AOA strain Candidatus Nitrosocosmicus agrestis. This strain was able to form aggregates and adhere on the surface of hydrophobic matrix. Ammonia-oxidizing activities were still observed at 200 mM NH4+ (> 1500 μM of free ammonia) and 50 mM NO2-. Urea could be used as sole energy source but exogenous organics had no significant effect on the ammonia oxidation. Besides the genes involving in ammonia oxidation, carbon fixation and urea hydrolysis, the genome also encodes a full set of genes (GTs, GHs, CEs, MOP, LPSE, etc) that responsible for polysaccharide metabolism and secretion, suggesting the potential production of extracellular polymeric substances (EPS). Moreover, a pathway connecting urea cycle, polyamines synthesis and excretion was identified in the genome, which indicates the NH4+ in cytoplasm could potentially be converted into polyamines and excreted out of cell, and then contributes to the high ammonia tolerance. Genes encoding the cytoplasmic carbonic anhydrase and putative polyamine exporter are unique in Ca. Nitrosocosmicus agrestis or the genus Ca. Nitrosocosmicus, suggesting the prevalence of ammonia tolerance in this clade. The proposed mechanism of ammonia tolerance via polyamines synthesis and export was verified by using transcriptional gene regulation and polyamines determination.IMPORTANCEAOA are ubiquitous in different environments and play a major role in nitrification. Though AOA have higher affinities for ammonia, their maximum specific cell activity and ammonia tolerance are usually much lower than AOB, resulting in low contribution to the global ammonia oxidation and N2O production. However, in some agricultural soils, the AOA activity would not be suppressed by the fertilization with high concentration of ammonium nitrogen, suggesting the presence of some ammonia tolerant species. This study provides some physiological and genomic characteristics for an ammonia tolerant soil AOA strain Ca. Nitrosocosmicus agrestis and proposes some mechanisms of this AOA adapting to a variety of environments and tolerating to high ammonia. Ammonia tolerance of AOA was always underestimated in many previous studies, physiological and genomic analyses of this AOA clade are benefit to uncover the role of AOA playing in global environmental patterns.

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MicroScope: an integrated platform for the annotation and exploration of microbial gene functions through genomic, pangenomic and metabolic comparative analysis

Cited by 228 publications

References 34 publications

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

PPanGGOLiN: Depicting microbial diversity via a partitioned pangenome graph

PPanGGOLiN: depicting microbial diversity via a partitioned pangenome graph

Physiological and genomic analysis of “CandidatusNitrosocosmicus agrestis”, an ammonia tolerant ammonia-oxidizing archaeon from vegetable soil

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