ABSTRACT
Here, we report 17 metagenome-assembled genomes (MAGs) recovered from microbial consortia of forest and pasture soils in the Brazilian Eastern Amazon. The bacterial MAGs have the potential to act in important ecological processes, including carbohydrate degradation and sulfur and nitrogen cycling.
ANNOUNCEMENT
The soil microbiota is responsible for several ecological functions (1) that drive biogeochemical processes and ecosystem services (2). However, losses of microbial diversity due to global changes can affect these processes (3). The Amazon is the largest reservoir of biodiversity on Earth (4, 5), and changes in land use modify soil microbial communities, leading to alterations in their taxonomic and functional profiles (5–9). Here, we used culture-dependent and -independent techniques to assess the microbial diversity of Amazonian soils. We developed a cultivation experiment using methane (CH4) to obtain metagenome-assembled genomes (MAGs) related to the carbon cycle, which resulted in two microbial consortia.
Soil sampling was conducted in the Brazilian Eastern Amazon, state of Pará, in a primary forest located in the Tapajós National Forest (2°51′19.6″S 54°57′30.1″W) and a pasture in the adjacent region (3°07′44.9″S 54°57′15.5″W). In each area, soil samples from 0- to 10-cm depth were collected in quintuplicate after removing the litter layer. Then, the samples of each land use were mixed. Microbial consortia were obtained from 10 g of forest and pasture soil samples which were initially triplicate enriched in CH4 atmosphere (12% vol/vol) for 15 days and serial diluted using the roll-tube technique (10) with a mixture (1:1) of nitrate mineral salt (NMS) medium (from the German Collection of Microorganisms and Cell Cultures [DSMZ], https://www.dsmz.de/microorganisms/medium/pdf/DSMZ_Medium632.pdf) without methanol and Bushnell Haas medium (HiMedia Lab Pvt. Ltd., Mumbai, India) under CH4 atmosphere (12%, vol/vol). From the microbial enrichment and cultivation in triplicate, we selected one forest and one pasture consortia sample for further analyses. The total consortia DNA was extracted using the PowerLyzer PowerSoil DNA Isolation Kit (Qiagen, Hilden, Germany). The metagenomic libraries were constructed using the Nextera DNA Flex Library Prep Kit (New England BioLabs, Inc., Ipswich, MA) and sequenced on the HiSeq 2500 platform (Illumina Inc., San Diego, CA) (2 × 100 bp).
The 38.5 and 42.1 million paired-end reads from the forest and pasture, respectively, were imported into the KBase platform (11), and default parameters were used for all software unless otherwise specified. Reads were quality evaluated using FastQC v0.11.9 (12) and filtered using Trimmomatic v0.36 (adapters, NexteraPE-PE; quality score, Phred scores >20) (13). After quality control, 35.1 and 38.3 million paired-end reads were maintained for forest and pasture, respectively. Data were assembled using MetaSpades v3.15.3 (14) and then binned with MaxBin2 v2.2.4 (15). The total size of the metagenomic assembly for forest was 46.11 Mbp (contigs, 2,883; GC content, 64.87%; N50, 56,397 bp) and for pasture was 89.07 Mbp (contigs, 7,503; GC content, 63.91%; N50, 29,115 bp).
CheckM v2.2.4 (16) was used to determine bin quality. Bins were quality filtered (completeness of ≥50% and contamination of ≤10%), extracted using Extract Bins as Assemblies from BinnedContigs v1.0.2, and taxonomically classified by GTDB-Tk v1.7.0 (R202) (17). We used DRAM v0.1.0 (18) for functional annotation. Bin relative abundance (the number of mapped reads divided by the number of reads in the corresponding metagenome) was calculated using Bowtie2 v2.3.2 (19).
We recovered 17 bacterial MAGs, assigned to Proteobacteria (11 MAGs), Actinobacteriota (4 MAGs), and Bacteroidota (2 MAGs) (Table 1). Functional annotations showed carbohydrate-active enzyme genes (CAZymes) and others associated with the biogeochemical cycles of nitrogen, sulfur, and methane (Fig. 1), indicating the potential ecological roles of these organisms.
TABLE 1.
Features and accession numbers of the consortia metagenome-assembled genomes (MAGs) from Amazonian forest and pasture soils
| MAG | GTDB classification | Size (Mb) | No. of contigs | N50 (bp) | GC content (%) | No. of CDSa | Coverage (×) | Compl. (%)/cont. (%)b | Relative abundance (%)c | GenBank accession no. | SRA accession no.d |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Bin.001_Forest | Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Xanthobacteraceae; 62-47 | 5.16 | 107 | 151,135 | 61.99 | 4,859 | 425 | 99.58/1.53 | 39.29 | JANINJ000000000 | SRR19663812 |
| Bin.002_Forest | Bacteria; Actinobacteriota; Actinomycetia; Propionibacteriales; Nocardioidaceae; Nocardioides; Nocardioides kongjuensis | 5.49 | 12 | 665,384 | 72.02 | 5,301 | 255 | 99.22/0.52 | 25.19 | JANINK000000000 | SRR19663812 |
| Bin.003_Forest | Bacteria; Proteobacteria; Gammaproteobacteria; Burkholderiales; Burkholderiaceae; Massilia; Massilia sp001426525 | 7.47 | 67 | 234,711 | 65.99 | 6,507 | 197 | 99.92/0.77 | 26.36 | JANINL000000000 | SRR19663812 |
| Bin.005_Forest | Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Rhizobiaceae; Mesorhizobium | 6.68 | 565 | 20,288 | 63.77 | 6,845 | 30 | 95.10/4.34 | 0.34 | JANINM000000000 | SRR19663812 |
| Bin.006_Forest | Bacteria; Proteobacteria; Alphaproteobacteria; Sphingomonadales; Sphingomonadaceae; Sphingomonas | 3.24 | 63 | 88,057 | 68.09 | 3,102 | 14 | 90.91/1.45 | 0.87 | JANINN000000000 | SRR19663812 |
| Bin.001_Pasture | Bacteria; Actinobacteriota; Actinomycetia; Propionibacteriales; Nocardioidaceae; Nocardioides; Nocardioides kongjuensis | 5.49 | 19 | 494,217 | 72.03 | 5,305 | 681 | 99.22/0.52 | 61.53 | JANINO000000000 | SRR19663813 |
| Bin.002_Pasture | Bacteria; Proteobacteria; Alphaproteobacteria; Sphingomonadales; Sphingomonadaceae; Sphingomonas | 4.63 | 8 | 1,260,393 | 64.76 | 4,308 | 57 | 99.57/2.32 | 4.40 | JANINP000000000 | SRR19663813 |
| Bin.003_Pasture | Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Xanthobacteraceae; Afipia | 4.43 | 22 | 649,841 | 61.44 | 4,294 | 47 | 97.41/4.23 | 3.48 | JANINQ000000000 | SRR19663813 |
| Bin.004_Pasture | Bacteria; Proteobacteria; Gammaproteobacteria; Xanthomonadales; Xanthomonadaceae; Luteimonas_B | 2.39 | 157 | 21,784 | 71.50 | 2,401 | 35 | 97.30/0.43 | 1.41 | JANINR000000000 | SRR19663813 |
| Bin.005_Pasture | Bacteria; Bacteroidota; Bacteroidia; Chitinophagales; Chitinophagaceae | 3.88 | 8 | 1,394,606 | 40.12 | 3,389 | 33 | 99.51/0.49 | 2.12 | JANINS000000000 | SRR19663813 |
| Bin.006_Pasture | Bacteria; Actinobacteriota; Actinomycetia; Propionibacteriales; Nocardioidaceae; Nocardioides | 4.75 | 453 | 19,777 | 72.07 | 4,947 | 50 | 95.64/2.33 | 3.92 | JANINT000000000 | SRR19663813 |
| Bin.007_Pasture | Bacteria; Proteobacteria; Alphaproteobacteria; Caulobacterales; Caulobacteraceae; Phenylobacterium | 4.81 | 359 | 22,875 | 69.48 | 4,961 | 22 | 93.79/5.01 | 1.80 | JANINU000000000 | SRR19663813 |
| Bin.008_Pasture | Bacteria; Proteobacteria; Gammaproteobacteria; Xanthomonadales; Rhodanobacteraceae; Dokdonella_A; Dokdonella_A fugitiva_A | 4.68 | 186 | 45,676 | 69.77 | 4,285 | 14 | 98.51/1.29 | 1.14 | JANINV000000000 | SRR19663813 |
| Bin.009_Pasture | Bacteria; Bacteroidota; Bacteroidia; Chitinophagales; Chitinophagaceae; Flavipsychrobacter | 3.76 | 98 | 277,925 | 43.57 | 3,588 | 11 | 98.52/2.00 | 0.72 | JANINW000000000 | SRR19663813 |
| Bin.011_Pasture | Bacteria; Actinobacteriota; Actinomycetia; Actinomycetales; Micrococcaceae; Paenarthrobacter | 3.18 | 956 | 3,691 | 62.51 | 4,297 | 9 | 65.99/0.70 | 0.48 | JANINX000000000 | SRR19663813 |
| Bin.012_Pasture | Bacteria; Proteobacteria; Alphaproteobacteria; Rhizobiales; Rhizobiaceae; Agrobacterium; Agrobacterium pusense | 5.28 | 388 | 23,271 | 57.97 | 5,743 | 7 | 71.63/5.42 | 0.64 | JANINY000000000 | SRR19663813 |
| Bin.015_Pasture | Bacteria; Proteobacteria; Gammaproteobacteria; Burkholderiales; Burkholderiaceae; Ramlibacter | 4.05 | 537 | 10,675 | 69.32 | 4,568 | 6 | 81.02/1.64 | 0.45 | JANINZ000000000 | SRR19663813 |
CDS, coding sequences.
Compl., completeness value; Cont., contamination value.
Relative abundance, the number of mapped reads divided by the number of reads in the corresponding metagenome.
SRA accession number of the raw metagenomic reads for each MAG.
FIG 1.
DRAM annotations of the consortia metagenome-assembled genomes (MAGs) from Amazonian forest and pasture soils. The colors in the heatmap represent the presence or absence of relevant metabolic functions in each MAG. CAZy, carbohydrate-active enzymes; OR, other reductases; SCFA, short-chain fatty acids.
Data availability.
All data are deposited at the NCBI under BioProject PRJNA849167. The SRA accession numbers for the raw reads are SRR19663812 and SRR19663813. The metagenome-assembled genomes are deposited under the GenBank accession numbers listed in Table 1. Data are also available on the KBase platform at https://doi.org/10.25982/116951.133/1878567.
ACKNOWLEDGMENTS
This work was supported by the São Paulo Research Foundation (FAPESP; grant numbers 2014/50320-4, 2015/12282-6, 2015/13546-7, 2015/23758-1, 2018/14974-0, 2019/25931-3, and 2019/26029-1), the National Council for Scientific and Technological Development (CNPq; grant numbers 140032/2015-0, 311008/2016-0, 130292/2019-2, and 314806/2021-0), and the Coordination for the Improvement of Higher Education Personnel - Brasil (CAPES) - Finance Code 001. A.M.V.’s research was funded by the Fung Global Fellows Program of the Princeton Institute for International and Regional Studies (PIIRS; Princeton University).
We thank Wagner Piccinini for the assistance in the field and the Large-Scale Biosphere-Atmosphere Program (LBA), coordinated by the National Institute for Amazon Research (INPA), for the logistical support and infrastructure during field activities. We thank Leandro N. Lemos and Amanda G. Bendia for their consultancy on the metagenomes assembling.
J.A.M., F.M.N., S.M.T., and A.M.V. designed the research. F.M.N. collected the samples. The experiment and molecular analysis were conducted by J.A.M. and F.M.N. J.A.M. analyzed the microbial data with contributions from J.B.G., F.M.N., and A.M.V. S.M.T. contributed with field sampling logistics, reagents, materials, and analytic tools. J.A.M. wrote the article. All authors critically revised the manuscript.
Contributor Information
Andressa M. Venturini, Email: andressa.venturini@alumni.usp.br.
David A. Baltrus, University of Arizona
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data are deposited at the NCBI under BioProject PRJNA849167. The SRA accession numbers for the raw reads are SRR19663812 and SRR19663813. The metagenome-assembled genomes are deposited under the GenBank accession numbers listed in Table 1. Data are also available on the KBase platform at https://doi.org/10.25982/116951.133/1878567.