Change search
Refine search result
1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1. Dupont, Chris L.
    et al.
    Larsson, John
    Yooseph, Shibu
    Ininbergs, Karolina
    Goll, Johannes
    Asplund-Samuelsson, Johannes
    McCrow, John P.
    Celepli, Narin
    Allen, Lisa Zeigler
    Ekman, Martin
    Lucas, Andrew J.
    Hagström, Åke
    Thiagarajan, Mathangi
    Brindefalk, Björn
    Richter, Alexander R.
    Andersson, Anders F.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tenney, Aaron
    Lundin, Daniel
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Tovchigrechko, Andrey
    Nylander, Johan A. A.
    Brami, Daniel
    Badger, Jonathan H.
    Allen, Andrew E.
    Rusch, Douglas B.
    Hoffman, Jeff
    Norrby, Erling
    Friedman, Robert
    Pinhassi, Jarone
    Venter, J. Craig
    Bergman, Birgitta
    Functional Tradeoffs Underpin Salinity-Driven Divergence in Microbial Community Composition2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 2, p. e89549-Article in journal (Refereed)
    Abstract [en]

    Bacterial community composition and functional potential change subtly across gradients in the surface ocean. In contrast, while there are significant phylogenetic divergences between communities from freshwater and marine habitats, the underlying mechanisms to this phylogenetic structuring yet remain unknown. We hypothesized that the functional potential of natural bacterial communities is linked to this striking divide between microbiomes. To test this hypothesis, metagenomic sequencing of microbial communities along a 1,800 km transect in the Baltic Sea area, encompassing a continuous natural salinity gradient from limnic to fully marine conditions, was explored. Multivariate statistical analyses showed that salinity is the main determinant of dramatic changes in microbial community composition, but also of large scale changes in core metabolic functions of bacteria. Strikingly, genetically and metabolically different pathways for key metabolic processes, such as respiration, biosynthesis of quinones and isoprenoids, glycolysis and osmolyte transport, were differentially abundant at high and low salinities. These shifts in functional capacities were observed at multiple taxonomic levels and within dominant bacterial phyla, while bacteria, such as SAR11, were able to adapt to the entire salinity gradient. We propose that the large differences in central metabolism required at high and low salinities dictate the striking divide between freshwater and marine microbiomes, and that the ability to inhabit different salinity regimes evolved early during bacterial phylogenetic differentiation. These findings significantly advance our understanding of microbial distributions and stress the need to incorporate salinity in future climate change models that predict increased levels of precipitation and a reduction in salinity.

  • 2. Dwivedi, Bhakti
    et al.
    Xue, Bingjie
    Lundin, Daniel
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edwards, Robert A.
    Breitbart, Mya
    A bioinformatic analysis of ribonucleotide reductase genes in phage genomes and metagenomes2013In: BMC Evolutionary Biology, ISSN 1471-2148, E-ISSN 1471-2148, Vol. 13, p. 33-Article in journal (Refereed)
    Abstract [en]

    Background: Ribonucleotide reductase (RNR), the enzyme responsible for the formation of deoxyribonucleotides from ribonucleotides, is found in all domains of life and many viral genomes. RNRs are also amongst the most abundant genes identified in environmental metagenomes. This study focused on understanding the distribution, diversity, and evolution of RNRs in phages (viruses that infect bacteria). Hidden Markov Model profiles were used to analyze the proteins encoded by 685 completely sequenced double-stranded DNA phages and 22 environmental viral metagenomes to identify RNR homologs in cultured phages and uncultured viral communities, respectively. Results: RNRs were identified in 128 phage genomes, nearly tripling the number of phages known to encode RNRs. Class I RNR was the most common RNR class observed in phages (70%), followed by class II (29%) and class III (28%). Twenty-eight percent of the phages contained genes belonging to multiple RNR classes. RNR class distribution varied according to phage type, isolation environment, and the host's ability to utilize oxygen. The majority of the phages containing RNRs are Myoviridae (65%), followed by Siphoviridae (30%) and Podoviridae (3%). The phylogeny and genomic organization of phage and host RNRs reveal several distinct evolutionary scenarios involving horizontal gene transfer, co-evolution, and differential selection pressure. Several putative split RNR genes interrupted by self-splicing introns or inteins were identified, providing further evidence for the role of frequent genetic exchange. Finally, viral metagenomic data indicate that RNRs are prevalent and highly dynamic in uncultured viral communities, necessitating future research to determine the environmental conditions under which RNRs provide a selective advantage. Conclusions: This comprehensive study describes the distribution, diversity, and evolution of RNRs in phage genomes and environmental viral metagenomes. The distinct distributions of specific RNR classes amongst phages, combined with the various evolutionary scenarios predicted from RNR phylogenies suggest multiple inheritance sources and different selective forces for RNRs in phages. This study significantly improves our understanding of phage RNRs, providing insight into the diversity and evolution of this important auxiliary metabolic gene as well as the evolution of phages in response to their bacterial hosts and environments.

  • 3. Herlemann, Daniel P. R.
    et al.
    Lundin, Daniel
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Labrenz, Matthias
    Jürgens, Klaus
    Zheng, Zongli
    Aspeborg, Henrik
    KTH, School of Biotechnology (BIO), Glycoscience.
    Andersson, Anders F.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Metagenomic De Novo Assembly of an Aquatic Representative of the Verrucomicrobial Class Spartobacteria2013In: mBio, ISSN 2161-2129, E-ISSN 2150-7511, Vol. 4, no 3, p. e00569-12-Article in journal (Refereed)
    Abstract [en]

    The verrucomicrobial subdivision 2 class Spartobacteria is one of the most abundant bacterial lineages in soil and has recently also been found to be ubiquitous in aquatic environments. A 16S rRNA gene study from samples spanning the entire salinity range of the Baltic Sea indicated that, in the pelagic brackish water, a phylotype of the Spartobacteria is one of the dominating bacteria during summer. Phylogenetic analyses of related 16S rRNA genes indicate that a purely aquatic lineage within the Spartobacteria exists. Since no aquatic representative from the Spartobacteria has been cultured or sequenced, the metabolic capacity and ecological role of this lineage are yet unknown. In this study, we reconstructed the genome and metabolic potential of the abundant Baltic Sea Spartobacteria phylotype by metagenomics. Binning of genome fragments by nucleotide composition and a self-organizing map recovered the near-complete genome of the organism, the gene content of which suggests an aerobic heterotrophic metabolism. Notably, we found 23 glycoside hydrolases that likely allow the use of a variety of carbohydrates, like cellulose, mannan, xylan, chitin, and starch, as carbon sources. In addition, a complete pathway for sulfate utilization was found, indicating catabolic processing of sulfated polysaccharides, commonly found in aquatic phytoplankton. The high frequency of glycoside hydrolase genes implies an important role of this organism in the aquatic carbon cycle. Spatiotemporal data of the phylotype's distribution within the Baltic Sea indicate a connection to Cyanobacteria that may be the main source of the polysaccharide substrates. IMPORTANCE The ecosystem roles of many phylogenetic lineages are not yet well understood. One such lineage is the class Spartobacteria within the Verrucomicrobia that, despite being abundant in soil and aquatic systems, is relatively poorly studied. Here we circumvented the difficulties of growing aquatic Verrucomicrobia by applying shotgun metagenomic sequencing on a water sample from the Baltic Sea. By using a method based on sequence signatures, we were able to in silico isolate genome fragments belonging to a phylotype of the Spartobacteria. The genome, which represents the first aquatic representative of this clade, encodes a diversity of glycoside hydrolases that likely allow degradation of various complex carbohydrates. Since the phylotype cooccurs with Cyanobacteria, these may be the primary producers of the carbohydrate substrates. The phylotype, which is highly abundant in the Baltic Sea during summer, may thus play an important role in the carbon cycle of this ecosystem.

  • 4.
    Hugerth, Luisa W.
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Muller, Emilie E. L.
    Hu, Yue O. O.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lebrun, Laura A. M.
    Roume, Hugo
    Lundin, Daniel
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Wilmes, Paul
    Andersson, Anders F.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Systematic Design of 18S rRNA Gene Primers for Determining Eukaryotic Diversity in Microbial Consortia2014In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 9, no 4, p. 095567-Article in journal (Refereed)
    Abstract [en]

    High-throughput sequencing of ribosomal RNA gene (rDNA) amplicons has opened up the door to large-scale comparative studies of microbial community structures. The short reads currently produced by massively parallel sequencing technologies make the choice of sequencing region crucial for accurate phylogenetic assignments. While for 16S rDNA, relevant regions have been well described, no truly systematic design of 18S rDNA primers aimed at resolving eukaryotic diversity has yet been reported. Here we used 31,862 18S rDNA sequences to design a set of broad-taxonomic range degenerate PCR primers. We simulated the phylogenetic information that each candidate primer pair would retrieve using paired-or single-end reads of various lengths, representing different sequencing technologies. Primer pairs targeting the V4 region performed best, allowing discrimination with paired-end reads as short as 150 bp (with 75% accuracy at genus level). The conditions for PCR amplification were optimised for one of these primer pairs and this was used to amplify 18S rDNA sequences from isolates as well as from a range of environmental samples which were then Illumina sequenced and analysed, revealing good concordance between expected and observed results. In summary, the reported primer sets will allow minimally biased assessment of eukaryotic diversity in different microbial ecosystems.

  • 5.
    Lundin, Daniel
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Poole, Anthony M.
    Sjöberg, Britt-Marie
    Högbom, Martin
    Use of Structural Phylogenetic Networks for Classification of the Ferritin-like Superfamily2012In: Journal of Biological Chemistry, ISSN 0021-9258, E-ISSN 1083-351X, Vol. 287, no 24, p. 20565-20575Article in journal (Refereed)
    Abstract [en]

    In the postgenomic era, bioinformatic analysis of sequence similarity is an immensely powerful tool to gain insight into evolution and protein function. Over long evolutionary distances, however, sequence-based methods fail as the similarities become too low for phylogenetic analysis. Macromolecular structure generally appears better conserved than sequence, but clear models for how structure evolves over time are lacking. The exponential growth of three-dimensional structural information may allow novel structure-based methods to drastically extend the evolutionary time scales amenable to phylogenetics and functional classification of proteins. To this end, we analyzed 80 structures from the functionally diverse ferritin-like superfamily. Using evolutionary networks, we demonstrate that structural comparisons can delineate and discover groups of proteins beyond the "twilight zone" where sequence similarity does not allow evolutionary analysis, suggesting that considerable and useful evolutionary signal is preserved in three-dimensional structures.

  • 6.
    Lundin, Daniel
    et al.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Severin, I.
    Logue, J. B.
    Östman, O.
    Andersson, Anders F.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Lindström, E. S.
    Which sequencing depth is sufficient to describe patterns in bacterial alpha- and beta-diversity?2012In: Environmental Microbiology Reports, ISSN 1758-2229, E-ISSN 1758-2229, Vol. 4, no 3, p. 367-372Article in journal (Refereed)
    Abstract [en]

    The vastness of microbial diversity implies that an almost infinite number of individuals needs to be identified to accurately describe such communities. Practical and economical constraints may therefore prevent appropriate study designs. However, for many questions in ecology it is not essential to know the actual diversity but rather the trends among samples thereof. It is, hence, important to know to what depth microbial communities need to be sampled to accurately measure trends in diversity. We used three data sets of freshwater and sediment bacteria, where diversity was explored using 454 pyrosequencing. Each data set contained 615 communities from which 15 00020 000 16S rRNA gene sequences each were obtained. These data sets were subsampled repeatedly to 10 different depths down to 200 sequences per community. Diversity estimates varied with sequencing depth, yet, trends in diversity among samples were less sensitive. We found that 1000 denoised sequences per sample explained to 90% the trends in beta-diversity (Bray-Curtis index) among samples observed for 15 00020 000 sequences. Similarly, 5000 denoised sequences were sufficient to describe trends in a-diversity (Shannon index) with the same accuracy. Further, 5000 denoised sequences captured to more than 80% the trends in Chao1 richness and Pielou's evenness.

  • 7. Thureborn, P.
    et al.
    Lundin, Daniel
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Plathan, J.
    Poole, A. M.
    Sjöberg, B. -M
    Sjöling, S.
    A Metagenomics Transect into the Deepest Point of the Baltic Sea Reveals Clear Stratification of Microbial Functional Capacities2013In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 8, no 9, p. e74983-Article in journal (Refereed)
    Abstract [en]

    The Baltic Sea is characterized by hyposaline surface waters, hypoxic and anoxic deep waters and sediments. These conditions, which in turn lead to a steep oxygen gradient, are particularly evident at Landsort Deep in the Baltic Proper. Given these substantial differences in environmental parameters at Landsort Deep, we performed a metagenomic census spanning surface to sediment to establish whether the microbial communities at this site are as stratified as the physical environment. We report strong stratification across a depth transect for both functional capacity and taxonomic affiliation, with functional capacity corresponding most closely to key environmental parameters of oxygen, salinity and temperature. We report similarities in functional capacity between the hypoxic community and hadal zone communities, underscoring the substantial degree of eutrophication in the Baltic Proper. Reconstruction of the nitrogen cycle at Landsort deep shows potential for syntrophy between archaeal ammonium oxidizers and bacterial denitrification at anoxic depths, while anaerobic ammonium oxidation genes are absent, despite substantial ammonium levels below the chemocline. Our census also reveals enrichment in genetic prerequisites for a copiotrophic lifestyle and resistance mechanisms reflecting adaptation to prevalent eutrophic conditions and the accumulation of environmental pollutants resulting from ongoing anthropogenic pressures in the Baltic Sea.

1 - 7 of 7
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf