Geochemical and sequencing data from Goff et. al. 2022

Ecophysiological and genomic analyses of a highly abundant Bacillus cereus strain reveal niche adaptation to contaminated subsurface sediments

submitted for publication 3-19-2022

Contents of narrative

1. Environmental samples and geochemical data
2. 16S amplicon sequencing
3. B. cereus strain CPT56D-587-MTF (CPTF) complete genome
4. References

Environmental samples and geochemical data

Sampling and geochemical measurements

Sediment samples were collected from Area 3 of the Field Research Center (FRC) in Oak Ridge, TN which lies adjacent to the former S-3 waste-disposal pond. Sediment samples were collected using a 1.5” diameter sediment sampler. At the surface, sample casing was removed, and samples were aseptically collected from the inner sections of the core using a sterile plastic scraper. Porewater nitrate was determined using an electrical conductivity detector on a Dionex™ ICS-5000+ series system (ThermoFisher Scientific, Waltham, MA) with an IonPac AS11HC analytical column. Soil pH was determined by EPA method 9045D.

Data import

1. Sample metadata were imported into KBase using the Import Samples (v1.1.1) function. These data include sampling geographic coordinates, sample depth, and sample pH.
2. A chemical abundance matrix template for the nitrate data was generated using the Create Chemical Abundance Matrix Template (v1.0.29) function.
3. Porewater nitrate concentrations (mg/Kg) were imported using the Import Chemical Abundance Matrix from CSV/Excel/TSV File in Staging Area (v1.0.29) function. This generated a Chemical Abundance Matrix for nitrate. Porewater was not available for all samples. Within the generated matrix a "0.0" value indicates that no measurement was made.

16S amplicon sequencing

Microbial genomic DNA isolation, 16S sequencing, and processing

1. Microbial genomic DNA was extracted from the sediment samples described above by a freeze-grinding method (1) and purified using a DNeasy PowerSoil DNA isolation Kit (QIAGEN; bead tubes were not used).
2. DNA quality was checked by NanoDrop, ,and double-strand DNA concentration was measured by Quant-iT™ PicoGreen™ dsDNA Assay Kit.
3. A two-step PCR was used for library preparation (2). First, the standard primers were used to amplify the V4 region of prokaryotic 16S rRNA genes (515F [5’-GTGCCAGCMGCCGCGGTAA-3’] and 806R [5’-GGACTACHVGGGTWTCTAAT-3’]). Second, phasing primers were designed and used to increase the base diversity in sequences of the sample libraries. PCR was performed for 11 cycles in the first step and 22 cycles in the second step.
4. Sample libraries were sequenced on a MiSeq platform (Illumina, San Diego, CA, USA) (3).
5. Sequencing data was processed with QIIME2 (v2021.2)(4). After barcode and primer sequences were trimmed with zero error, exact amplicon sequence variants (ASV) were identified by DADA2 (5). The method ‘consensus’ was used to remove chimeras; samples are denoised independently; forward and reverse truncate positions are 163 and 130, respectively, after quality trim with a quality score 2; maximal expected error score is 2.0 when combining forward and reverse sequences.

Raw reads

Raw sequencing reads can be downloaded from the Sequence Read Archive via the BioProject accession number PRJNA827189 upon its release (Scheduled: 05-31-22).

Data import

1. Processed 16S amplicon sequencing reads (FASTA sequence file and ASV table) were imported into KBase using the Import Amplicon Matrix from TSV/FASTA File in Staging Area (v1.0.29) function.
2. Taxonomic assignment was performed using the Classify rRNA with taxonomy using naive Bayes with RDP Classifier-v2.13 (v0.01) function with a boostrap confidence threshhold of 0.5 against the SILVA 138-SSU,V4 database .

B. cereus strain CPT56D-587-MTF (CPTF) complete genome

The complete genome sequence can be found in this static narrative (6).

References

1. Zhou, J., Bruns, M.A.,and Tiedje, J.M. (1996) DNA recovery from soils of diverse composition. Appl Environ Microbiol 62: 316-22. DOI: 10.1128/aem.62.2.316-322.1996
2. Wu, L., Wen, C., Qin, Y., Yin, H., Tu, Q., Van Nostrand, J.D., Yuan, T., Yuan, M., Deng, Y.,and Zhou, J. (2015) Phasing amplicon sequencing on Illumina Miseq for robust environmental microbial community analysis. BMC Microbiol 15: 125. DOI: 10.1186/s12866-015-0450-4
3. Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S.M., Betley, J., Fraser, L., Bauer, M., Gormley, N., Gilbert, J.A., Smith, G.,and Knight, R. (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6: 1621-1624. DOI: 10.1038/ismej.2012.8
4. Bolyen, et al. (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 37: 852-857. DOI: 10.1038/s41587-019-0209-9
5. Callahan, B.J., Mcmurdie, P.J., Rosen, M.J., Han, A.W., Johnson, A.J.A.,and Holmes, S.P. (2016) DADA2: High-resolution sample inference from Illumina amplicon data. Nature Methods 13: 581-583. DOI: 10.1038/nmeth.3869
6. Goff J. 2022. Complete Genome of ORR Isolate Bacillus cereus CPT56D-587-MTF, on DOE Systems Biology Knowledgebase. https://kbase.us/n/105874/55/. DOI: 10.25982/105874.55/1844990