Systems biology of acidophile biofilms for efficient metal extraction.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
07 07 2020
07 07 2020
Historique:
received:
13
02
2020
accepted:
12
05
2020
entrez:
9
7
2020
pubmed:
9
7
2020
medline:
8
1
2021
Statut:
epublish
Résumé
Society's demand for metals is ever increasing while stocks of high-grade minerals are being depleted. Biomining, for example of chalcopyrite for copper recovery, is a more sustainable biotechnological process that exploits the capacity of acidophilic microbes to catalyze solid metal sulfide dissolution to soluble metal sulfates. A key early stage in biomining is cell attachment and biofilm formation on the mineral surface that results in elevated mineral oxidation rates. Industrial biomining of chalcopyrite is typically carried out in large scale heaps that suffer from the downsides of slow and poor metal recoveries. In an effort to mitigate these drawbacks, this study investigated planktonic and biofilm cells of acidophilic (optimal growth pH < 3) biomining bacteria. RNA and proteins were extracted, and high throughput "omics" performed from a total of 80 biomining experiments. In addition, micrographs of biofilm formation on the chalcopyrite mineral surface over time were generated from eight separate experiments. The dataset generated in this project will be of great use to microbiologists, biotechnologists, and industrial researchers.
Identifiants
pubmed: 32636389
doi: 10.1038/s41597-020-0519-2
pii: 10.1038/s41597-020-0519-2
pmc: PMC7340779
doi:
Substances chimiques
Acids
0
Bacterial Proteins
0
Metals
0
RNA, Bacterial
0
chalcopyrite
1308-56-1
Copper
789U1901C5
Types de publication
Dataset
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
215Subventions
Organisme : Vetenskapsrådet (Swedish Research Council)
ID : 2014-6545
Pays : International
Organisme : Fonds National de la Recherche Luxembourg (National Research Fund)
ID : INTER/SYSAPP/14/05
Pays : International
Organisme : Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Swiss National Science Foundation)
ID : 205321_173020
Pays : International
Références
Brierley, C. L. & Brierley, J. A. Progress in bioleaching: part B: applications of microbial processes by the minerals industries. Appl. Microbiol. Biotechnol. 97, 7543–7552 (2013).
doi: 10.1007/s00253-013-5095-3
Petersen, J. Heap leaching as a key technology for recovery of values from low-grade ores – a brief overview. Hydrometallurgy 165, 206–212 (2016).
doi: 10.1016/j.hydromet.2015.09.001
Bonnefoy, V. & Holmes, D. S. Genomic insights into microbial iron oxidation and iron uptake strategies in extremely acidic environments. Environ. Microbiol. 14, 1597–1611 (2012).
doi: 10.1111/j.1462-2920.2011.02626.x
Vera, M., Schippers, A. & Sand, W. Progress in bioleaching: fundamentals and mechanisms of bacterial metal sulfide oxidation–part A. Appl. Microbiol. Biotechnol. 97, 7529–7541 (2013).
doi: 10.1007/s00253-013-4954-2
Dopson, M. & Johnson, D. B. Biodiversity, metabolism and applications of acidophilic sulfur-metabolizing microorganisms. Environ. Microbiol. 14, 2620–2631 (2012).
doi: 10.1111/j.1462-2920.2012.02749.x
Khoshkhoo, M., Dopson, M., Engström, F. & Sandström, Å. New insights into the influence of redox potential on chalcopyrite leaching behaviour. Min. Engin. 100, 9–16 (2017).
doi: 10.1016/j.mineng.2016.10.003
Li, Y., Kawashima, N., Li, J., Chandra, A. & Gerson, A. A review of the structure, and fundamental mechanisms and kinetics of the leaching of chalcopyrite. Adv. in Colloid Interface Sci. 197–198, 1–32 (2013).
Panda, S., Akcil, A., Pradhan, N. & Deveci, H. Current scenario of chalcopyrite bioleaching: A review on the recent advances to its heap-leach technology. Biores. Technol. 196, 694–706 (2015).
doi: 10.1016/j.biortech.2015.08.064
Gericke, M., Govender, Y. & Pinches, A. Tank bioleaching of low-grade chalcopyrite concentrates using redox control. Hydrometallurgy 104, 414–419, 18th International Biohydrometallurgy Symposium, IBS2009, Bariloche-Argentina, 13–17 September 2009 (2010).
Masaki, Y., Hirajima, T., Sasaki, K., Miki, H. & Okibe, N. Microbiological redox potential control to improve the efficiency of chalcopyrite bioleaching. Geomicrobiol. 35, 648–656 (2018).
doi: 10.1080/01490451.2018.1443170
Christel, S. et al. Weak iron oxidation by Sulfobacillus thermosulfidooxidans maintains a favorable redox potential for chalcopyrite bioleaching. Front. Microbiol. 9, 3059 (2018).
doi: 10.3389/fmicb.2018.03059
Bellenberg, S. et al. Biofilm formation, communication and interactions of leaching bacteria during colonization of pyrite and sulfur surfaces. Res. Microbiol. 165, 773–781 (2014).
doi: 10.1016/j.resmic.2014.08.006
Christel, S. et al. Multi-omics reveal the lifestyle of the acidophilic, mineral-oxidizing model species Leptospirillum ferriphilum
Bellenberg, S. et al. Automated microscopic analysis of metal sulfide colonization by acidophilic microorganisms. Appl. and Environ. Microbiol. 84, e01835-18 (2018).
Buetti-Dinh, A. et al. Deep neural networks outperform human expert’s capacity in characterizing bioleaching bacterial biofilm composition. Biotechnol. Rep. 22, e00321 (2019).
doi: 10.1016/j.btre.2019.e00321
Buetti-Dinh, A. et al. Reverse engineering directed gene regulatory networks from transcriptomics and proteomics data of biomining bacterial communities with approximate bayesian computation and steady-state signalling simulations. BMC Bioinformatics 21, 23 (2020).
Forssberg, K. S. E. Flotation of sulphide minerals/edited by Eric Forssberg, K. S. (Elsevier; Distributors for the U.S. and Canada, Elsevier Science Pub. Co Amsterdam; New York: New York, N.Y, 1985).
Clarke, P., Fornasiero, D., Ralston, J. & Smart, R. A study of the removal of oxidation products from sulfide mineral surfaces. Min. Engin. 8, 1347–1357 (1995).
doi: 10.1016/0892-6875(95)00101-U
Dopson, M., Sundkvist, J.-E. & Lindström, E. B. Toxicity of metal extraction and flotation chemicals to Sulfolobus metallicus and chalcopyrite bioleaching. Hydrometallurgy 81, 205–213 (2006).
doi: 10.1016/j.hydromet.2005.12.005
Coram, N. J. & Rawlings, D. E. Molecular relationship between two groups of the genus Leptospirillum and the finding that Leptospirillum ferriphilum sp. nov. dominates South African commercial biooxidation tanks that operate at 40 degrees C. Appl. Environ. Microbiol. 68, 838–845 (2002).
doi: 10.1128/AEM.68.2.838-845.2002
Golovacheva, R. S. & Karavaiko, G. I. Sulfobacillus, a new genus of thermophilic sporulating bacteria. Mikrobiologiia 47, 815–822 (1978).
pubmed: 101742
Hallberg, K. B. & Lindstrom, E. B. Characterization of Thiobacillus caldus sp. nov., a moderately thermophilic acidophile. Microbiology (Reading, Engl.) 140, 3451–3456 (1994).
doi: 10.1099/13500872-140-12-3451
Mackintosh, E. M. Nitrogen fixation by Thiobacillus ferrooxidans. Microbiology 105, 215–218 (1978).
Roume, H. et al. A biomolecular isolation framework for eco-systems biology. ISME J. 7, 110–121 (2013).
doi: 10.1038/ismej.2012.72
Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
doi: 10.1093/bioinformatics/btu170
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
doi: 10.1038/nmeth.1923
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).
doi: 10.1093/bioinformatics/btt656
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq 2. Genome Biol. 15, 550 (2014).
doi: 10.1186/s13059-014-0550-8
Klingenberg, H. & Meinicke, P. How to normalize metatranscriptomic count data for differential expression analysis. PeerJ 5, e3859 (2017).
doi: 10.7717/peerj.3859
Rappsilber, J., Mann, M. & Ishihama, Y. Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007).
doi: 10.1038/nprot.2007.261
Kaur, H. et al. Targeted ablation of periostin-expressing activated fibroblasts prevents adverse cardiac remodeling in mice. Circ. Res. 118, 1906–1917 (2016).
doi: 10.1161/CIRCRESAHA.116.308643
Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).
doi: 10.1021/pr101065j
Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell Proteomics 13, 2513–2526 (2014).
doi: 10.1074/mcp.M113.031591
Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).
doi: 10.1038/nmeth.3901
Leinonen, R. et al. The European Nucleotide Archive. Nucleic Acids Res. 39, 28–31 (2011).
doi: 10.1093/nar/gkq967
Buetti-Dinh, A. et al. RNAseq SysMetEx, mixed and single species cultures European Nucleotide Archive https://identifiers.org/ena.embl:PRJEB30001 (2018).
Buetti-Dinh, A. et al. RNAseq of binary cultures of S. thermosulfidooxidans and A. caldus with varied inoculum sizing. European Nucleotide Archive https://identifiers.org/ena.embl:PRJEB29980 (2018).
Bellenberg, S. et al. RNAseq of chalcopyrite leaching cultures for L.ferriphilum and L.ferriphilum + S.thermosulfidooxidans cultures. European Nucleotide Archive https://identifiers.org/ena.embl:PRJEB27815 (2018).
Christel, S. et al. RNAseq of binary and tertiary mixtures of microorganisms in chalcopyrite bioleaching. European Nucleotide Archive https://identifiers.org/ena.embl:PRJEB27534 (2018).
Christel, S. et al. RNA sequencing for L. ferriphilum cultures. European Nucleotide Archive https://identifiers.org/ena.embl:PRJEB21842 (2017).
Perez-Riverol, Y. et al. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 47, D442–D450 (2019).
doi: 10.1093/nar/gky1106
Buetti-Dinh, A. et al. Sysmetex proteome data comparison for ASX and LSX planktonic growth. PRIDE Archive https://identifiers.org/pride.project:PXD011502 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for SAL mineral growth. PRIDE Archive https://identifiers.org/pride.project:PXD011503 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for SLX mineral growth. PRIDE Archive https://identifiers.org/pride.project:PXD011504 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for SAX planktonic growth. PRIDE Archive https://identifiers.org/pride.project:PXD011506 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for Acidithiobacillus caldus in continuous culture. PRIDE Archive https://identifiers.org/pride.project:PXD011507 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for AAS. PRIDE Archive https://identifiers.org/pride.project:PXD011508 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for ASS. PRIDE Archive https://identifiers.org/pride.project:PXD011509 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for SAL planktonic growth. PRIDE Archive https://identifiers.org/pride.project:PXD011540 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for Acidithiobacillus caldus planktonic growth. PRIDE Archive https://identifiers.org/pride.project:PXD011863 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for Sulfobacillus thermosulfidooxidans planktonic growth. PRIDE Archive https://identifiers.org/pride.project:PXD011921 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for Leptospirillum ferriphilum mineral growth. PRIDE Archive https://identifiers.org/pride.project:PXD012780 (2020).
Buetti-Dinh, A. et al. Sysmetex proteome data for Leptospirillum ferriphilum planktonic growth. PRIDE Archive https://identifiers.org/pride.project:PXD012783 (2020).
Wolstencroft, K. et al. FAIRDOMHub: a repository and collaboration environment for sharing systems biology research. Nucleic Acids Res. 45, D404–D407 (2017).
doi: 10.1093/nar/gkw1032
Herold, M. SysMetEx – Dataset collection. FAIRDOMHub, https://doi.org/10.15490/fairdomhub.1.investigation.292.2 (2020).
Ewels, P., Magnusson, M., Lundin, S. & Kaller, M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32, 3047–3048 (2016).
doi: 10.1093/bioinformatics/btw354
SysMetEx – Data analysis, https://git-r3lab.uni.lu/malte.herold/sysmetex_data_analysis .
SysMetEx – Reference genomes, https://git-r3lab.uni.lu/malte.herold/SysMetEx_ReferenceGenomes .