The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Microbial activity in forest soil reflects the changes in ecosystem properties between summer and winter
Open accessAbstract
Summary: Understanding the ecology of coniferous forests is very important because these environments represent globally largest carbon sinks. Metatranscriptomics, microbial community and enzyme analyses were combined to describe the detailed role of microbial taxa in the functioning of the P icea abies ‐dominated coniferous forest soil in two contrasting seasons. These seasons were the summer, representing the peak of plant photosynthetic activity, and late winter, after an extended period with no photosynthate input. The results show that microbial communities were characterized by a high activity of fungi especially in litter where their contribution to microbial transcription was over 50%. Differences in abundance between summer and winter were recorded for 26–33% of bacterial genera and < 15% of fungal genera, but the transcript profiles of fungi, archaea and most bacterial phyla were significantly different among seasons. Further, the seasonal differences were larger in soil than in litter. Most importantly, fungal contribution to total microbial transcription in soil decreased from 33% in summer to 16% in winter. In particular, the activity of the abundant ectomycorrhizal fungi was reduced in winter, which indicates that plant photosynthetic production was likely one of the major drivers of changes in the functioning of microbial communities in this coniferous forest.
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Cites
Trimmomatic: a flexible trimmer for Illumina sequence data
Bolger, A. M., Lohse, M., & Usadel, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu170 · Cited by 65,548
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 20,826
UPARSE: highly accurate OTU sequences from microbial amplicon reads
Edgar, R. C. (2013) · Nature Methods · doi:10.1038/nmeth.2604 · Cited by 16,707
Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences
Li, W., & Godzik, A. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl158 · Cited by 11,410
Cd-hit: Accelerated for clustering the next-generation sequencing data
Fu, L., Niu, B., Zhu, Z., Wu, S., & Li, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts565 · Cited by 11,175
Velvet: Algorithms for de novo short read assembly using de Bruijn graphs
Zerbino, D. R., & Birney, E. (2008) · Genome Research · doi:10.1101/gr.074492.107 · Cited by 9,491
Phylogenetic identification and in situ detection of individual microbial cells without cultivation
Amann, R., Ludwig, W., & SCHLEIFER, K. H. (1995) · Microbiological Reviews · doi:10.1128/mmbr.59.1.143-169.1995 · Cited by 9,093
Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms
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., et al. (2012) · The ISME Journal · doi:10.1038/ismej.2012.8 · Cited by 8,839
Ribosomal Database Project: data and tools for high throughput rRNA analysis
Cole, J. R., Wang, Q., Fish, J. A., Chai, B., McGarrell, D. M., Sun, Y., Brown, C. T., Porras-Alfaro, A., Kuske, C. R., & Tiedje, J. M. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1244 · Cited by 4,367
Cited by
Forest microbiome: diversity, complexity and dynamics
Baldrian, P. (2016) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuw040 · Cited by 710
Self-citationBastida, F., Torres, I. F., Hernández, T., & García, C. (2017) · Soil Biology and Biochemistry · doi:10.1016/j.soilbio.2017.06.012 · Cited by 129
Metadata
- Authors
- Žifčáková, L., Větrovský, T., Howe, A., & Baldrian, P.
- Venue
- Environmental Microbiology
- Publisher
- Wiley
- Published
- 2015-10-14
- Volume
- 18
- Issue
- 1
- Pages
- 288-301
- ISSN
- 1462-2912 (ISSN-L)
- 1462-2920
- OpenAlex
- W2139244905
- Cited by
- 406
- References
- 55
- FWCI
- 35.19
- Type
- journal article
- Language
- en
- Open access
- green
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