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Comparison of measured run times (red line) and the least square fitting of equation (1) as a function of the number of parallel threads.
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The study of microbial diversity and community structures heavily relies on the analyses of sequence data, predominantly taxonomic marker genes like the small subunit of the ribosomal RNA (SSU rRNA) amplified from environmental samples. Until recently, the "gold standard" for this strategy was the cloning and Sanger sequencing of amplified target g...
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... function, as an approximation, nicely fits our test results as shown in Figure 4; even if the usage of only 4 data points is not strongly convincing its shape can be explained as follows: Parts of JAguc's computation are not performed in parallel (e.g., constructing the Trie) and thus imply a (for a fixed input) constant contri- bution to the overall run time. Those parts that are parallelized (e.g., computing pairwise alignments) give rise to a contribution scaled by the number of parallel threads. ...
Citations
... The length distribution of the tags was plotted in R (R Core Team 2012). The core (longest and thus most informative) sequence for each phylotype at 97% was extracted in a FASTA file, which was analysed with JAguc software (Nebel et al. 2011). The JAguc employed BLASTn searches, with algorithm parameters adjusted for short (200-500 bp) reads (-m 7 -r 5q -4 -G 8 -E 6 -b 50). ...
The diverse physicochemical conditions prevailing in the Arabian Sea are expected to result in marked spatial variations in heterotrophic flagellate (HF) and ciliate communities. Here, we report the environmental association of heterotrophic micro-eukaryotes, particularly the heterotrophic flagellates and ciliates, based on 18S rRNA gene survey in the region. High-throughput next-generation sequencing, using the V4 eukaryotic-specific primer, was employed to study the composition of these communities associated with low-O2 waters in both coastal and offshore settings. Canonical correspondence analysis (CCA) revealed a preference of the heterotrophic flagellates for nitrate- and nitrite-rich zones. Notably, the heterotrophic nanoflagellate genus Monosiga showed a strong positive correlation with NO3−, which suggests its potential denitrifying capability. Shannon’s entropy analysis revealed a higher HF diversity in the hypoxic waters of the open ocean (depth 103 m), whereas ciliates were more diverse at oxygenated coastal stations. The estuarine waters exhibited a low diversity of both ciliates and flagellates. The UPGMA clusters of heterotrophic flagellates and ciliates in suboxic waters of the open ocean oxygen minimum zone were distinct from those found at other sites. Overall, CCA revealed the important relationship between nitrite, nitrate, salinity and chlorophyll a, which could be important factors for the partitioning of different ecological niches for specific HF and ciliate communities in the Arabian Sea. The community of heterotrophic protists that can adapt to varying biogeochemical regimes has been identified.
... Reference databases for marker genes SILVA (Pruesse et al., 2007), Greengenes (DeSantis et al., 2006), RDP (Maidak et al., 2001), rrnDB (Stoddard et al., 2015), PhylOPDb (Jaziri et al., 2014), UNITE (Nilsson et al., 2018) 16S rRNA gene pipelines Packages of tools and commands to analyze 16S marker gene data from raw data to visualization QIIME2 (Bolyen et al., 2018), mothur , SILVA (Yilmaz et al., 2013), Megan (Huson et al., 2016), FASTGroup2 (Seguritan and Rohwer, 2001), PANGEA (Giongo et al., 2010), CLOTU (Kumar et al., 2011), Jaguc (Nebel et al., 2011), DADA2 (Callahan et al., 2016, MICCA (Albanese et al., 2015), FunFrame (Weisman et al., 2013), UPARSE (Edgar, 2013), MG-Rast ...
Metagenomics is the study of all genetic material from microbial communities. Rapid advances in sequencing capabilities, coupled with a steady decrease in price have made metagenomics-based research accessible to more researchers, allowing deeper insights into a variety of novel environments. The resulting increase in heterogeneous and noisy metagenomics data has resulted in the development a stream of analysis tools and platforms that enable the unveiling of the underlying biological processes. In this review, we introduce the fundamental strategies for generating and analyzing these data, along with associated tools for translating raw sequence data into robust, reproducible and interpretable results.
... Information on the sequence numbers after each step is given in Supplementary Table S5. Sequences with a minimum length of 400 bp were analyzed using Jaguc2 (Nebel et al., 2011). In brief, Jaguc2 operates with average linkage clustering and pairwise alignments for calling operational taxonomic units (OTUs). ...
... Paired-end forward and reverse reads were combined using BBMerge 34.48 1 by the LGC Genomics GmbH and used for further analysis. Random subsamples (4,000 sequences each for archaeal 16S rRNA gene transcript and eukaryotic 18S rRNA gene transcript libraries; 2000 sequences each for chiA libraries) were taken using USEARCH as the computing time of Jaguc2 for the clustering increases exponentially (Nebel et al., 2011). A minimum of 1,221 reads per dataset remained for further analysis. ...
Chitin provides a valuable carbon and nitrogen source for soil microorganisms and is a major component of particulate organic matter in agricultural soils. To date, there is no information on interaction and interdependence in chitin-degrading soil microbiomes. Since microbial chitin degradation occurs under both oxic and anoxic conditions and both conditions occur simultaneously in soil, the comparison of the active microbiome members under both conditions can reveal key players for the overall degradation in aerated soil. A time-resolved 16S rRNA stable isotope probing experiment was conducted with soil material from the top soil layer of a wheat-covered field. [¹³CU]-chitin was largely mineralized within 20 days under oxic conditions. Cellvibrio, Massilia, and several Bacteroidetes families were identified as initially active chitin degraders. Subsequently, Planctomycetes and Verrucomicrobia were labeled by assimilation of ¹³C carbon either from [¹³CU]-chitin or from ¹³C-enriched components of primary chitin degraders. Bacterial predators (e.g., Bdellovibrio and Bacteriovorax) were labeled, too, and non-labeled microeukaryotic predators (Alveolata) increased their relative abundance toward the end of the experiment (70 days), indicating that chitin degraders were subject to predation. Trophic interactions differed substantially under anoxic and oxic conditions. Various fermentation types occurred along with iron respiration. While Acidobacteria and Chloroflexi were the first taxa to be labeled, although at a low ¹³C level, Firmicutes and uncultured Bacteroidetes were predominantly labeled at a much higher ¹³C level during the later stages, suggesting that the latter two bacterial taxa were mainly responsible for the degradation of chitin and also provided substrates for iron reducers. Eventually, our study revealed that (1) hitherto unrecognized Bacteria were involved in a chitin-degrading microbial food web of an agricultural soil, (2) trophic interactions were substantially shaped by the oxygen availability, and (3) detectable predation was restricted to oxic conditions. The gained insights into trophic interactions foster our understanding of microbial chitin degradation, which is in turn crucial for an understanding of soil carbon dynamics.
... Software and pipelines Some of the commonly used software and pipelines used for short and structural variant discovery have been listed in Table 4.1. BWA [36] and Bowtie2 [37] are the primary choice for indexing and alignment of reads to human genome, while, most of the pipelines for variant discovery implements Genome Analysis Tool Kit (GATK) [38] for variant calling. Similarly, filtering and annotations of variant files are achieved through snpEff and ANNOVAR. ...
... Peter Mansfield [36]. This technique became the central tool in noninvasive diagnosis and functional monitoring of in vivo systems, helping in the functional evaluation of physiological disorders. ...
... FTIR spectroscopy has played vital role in unraveling the mechanism of nucleation and growth of supermagnetic β-FeOOH nanostructures in presence of nucleic bases. Adenine (23) (Fig. 6.7) based β-FeOOH nanoparticles have been fabricated by hydrolysis of Fe(III) chloride by employing varying concentrations of adenine [36]. The FTIR analysis revealed the iron oxide (β-FeOOH) interactions with adenine, primarily through aNH 2 , N(3) of the pyrimidine ring and N(7) and N(9)H of imidazole ring. ...
The NMR technique has brought an unparalleled contribution
to the biomolecular studies, both related to structural
elucidation and the advancement in dynamics
studies. A detailed study of enzymatic catalysis, carbohydrate
dynamics, and protein folding dynamics is made
feasible. The interaction between molecules and their
biological targets, as well as understanding about evolution
of the misfolding diseases, are some of the other
domains that are deciphered using this technique. We
have overviewed many techniques in this chapter that
can help a beginning user in the analysis of the NMR
spectrum to plan their experiments for different objectives.
Nevertheless, it is necessary to dedicate the handling
of the magnets with specialized personnel to
further data processing and analysis skills. The participation
in class courses offered throughout the year by the
worldwide NMR community is a very positive approach
that will help the beginner NMR spectroscopist. Always
have in hand theoretical materials and reference
tables for appropriate data handling. These documents
are of extreme importance since they are efficient and
precise, concerning the challenges presented by the biopolymers
analysis.
... Only sequences that matched primer sequences were further analyzed. Pairedend merging for napA, nrfA, nirS, and nirK, quality filtering (Q > 15), length trimming (Q > 15), dereplication, and clustering was done with the usearch pipeline and Jaguc [44,45]. For 16S rRNA, narG, napA, nrfA, nirS, and nirK, 43,000 ± 5000 (16S rRNA), 63,000 ± 5100 (narG), 17,500 ± 2300 (napA), 211,000 ± 25,000 (nrfA), 211,000 ± 28,000 (nirS), and 9800 ± 1700 (nirK), respectively, reads were obtained per replicate and transcript (mean ± standard error). ...
Nitrous acid (HONO) is a precursor of the hydroxyl radical (OH), a key oxidant in the degradation of most air pollutants. Field measurements indicate a large unknown source of HONO during the day time. Release of nitrous acid (HONO) from soil has been suggested as a major source of atmospheric HONO. We hypothesize that nitrite produced by biological nitrate reduction in oxygen-limited microzones in wet soils is a source of such HONO. Indeed, we found that various contrasting soil samples emitted HONO at high water-holding capacity (75–140%), demonstrating this to be a widespread phenomenon. Supplemental nitrate stimulated HONO emissions, whereas ethanol (70% v/v) treatment to minimize microbial activities reduced HONO emissions by 80%, suggesting that nitrate-dependent biotic processes are the sources of HONO. High-throughput Illumina sequencing of 16S rRNA as well as functional gene transcripts associated with nitrate and nitrite reduction indicated that HONO emissions from soil samples were associated with nitrate reduction activities of diverse Proteobacteria. Incubation of pure cultures of bacterial nitrate reducers and gene-expression analyses, as well as the analyses of mutant strains deficient in nitrite reductases, showed positive correlations of HONO emissions with the capability of microbes to reduce nitrate to nitrite. Thus, we suggest biological nitrate reduction in oxygen-limited microzones as a hitherto unknown source of atmospheric HONO, affecting biogeochemical nitrogen cycling, atmospheric chemistry, and global modeling.
... Information on the sequence numbers after each step is given in Table 20. Sequences with a minimum length of 400 bp were analyzed using Jaguc2 (Nebel et al., 2011). In brief, Jaguc2 operates with average linkage clustering and pairwise alignments for calling operational taxonomic units (OTUs). ...
... by the LGC Genomics GmbH and used for further analysis. Random subsamples (4000 sequences each) were taken using USEARCH as the computing time of Jaguc2 for the clustering increases exponentially (Nebel et al., 2011). Prior clustering barcodes as used in the pyrosequencing analysis were added to the fastq files in silico. ...
Chitin is the second most abundant polysaccharide after cellulose and is subject to rapid microbial turnover in the environment. Microbial degradation of chitin in soil substantially contributes to carbon cycling and release in terrestrial ecosystems. In aerated soil ecosystems, chitin occurs as a structural component in protists, arthropods, and fungi. Thereby, fungi represent the main source of chitin in such soils as fungi have cell walls with up to 25% chitin and account for up to 60-90% of the microbial biomass in aerated soils. Chitin degradation can theoretically occur via two major degradation pathways. It can be deacetylated to chitosan or can be hydrolyzed to N,N´-diacetylchitobiose and oligomers of N-acetylglucosamine by aerobic and anaerobic microorganisms. Which pathway of chitin hydrolysis is preferred by soil microbiomes was unknown prior to this thesis. Therefore, processes, metabolic responses and degradation products associated with chitin and chitosan hydrolysis were assessed. Chitin was immediately broken down by the tested microbiome, but chitosan only with a considerable time delay, which suggests that the microbiome is adjusted to chitin as a substrate, and the degradation of chitin probably likely does not take place via the deacetylation to chitosan. Another objective of this study was to study the trophic interactions and dynamics of members of a chitin-degrading microbiome and the influence of oxygen on the carbon flow from chitin degradation, as these topics are largely uninvestigated in aerated soils. Therefore, a time-resolved 16S rRNA stable isotope probing experiment was conducted to label and identify those members of a soil microbiome that are involved in the aerobic and anaerobic degradation of chitin. [13C]-chitin was largely mineralized within 20 days, and Cellvibrio, Massilia, and several Bacteroidetes families were identified as initial active chitin degraders under oxic conditions. Subsequently, Planctomycetes and Verrucomicrobia were labeled by assimilating carbon either directly from chitin or from the degradation of cell wall polysaccharides, biofilm-associated exopolysaccharides, and small metabolic byproducts of chitinolytic bacteria. Bacterial predators (e.g., Bdellovibrio and Bacteriovorax) were labeled and non-labeled micro-eukaryotic predators (Alveolata) increased in relative abundance towards the end of the incubation (70 days), indicating that chitin degraders were subject to predation. Under anoxic conditions, trophic interactions differed substantially compared to oxic conditions. Various fermentation types occurred along with iron respiration. While Acidobacteria and Chloroflexi were initially labeled, Firmicutes and uncultured Bacteroidetes were predominantly labeled, suggesting that the latter two bacterial groups were mainly responsible for the degradation of chitin, and also provided substrates for iron reducers. The collective data indicated (a) that hitherto unrecognized Bacteria were involved in the chitin-degrading food web of an agricultural soil, (b) that trophic interactions of the chitin-degrading microbial food web were substantially shaped by the oxygen availability, and (c) that predation was restricted to oxic conditions. The functional redundancy of the soil microbiome and the catabolic diversity likely enable continued biopolymer degradation independent of oxygen concentration. Furthermore, chitin was readily and nearly completely degraded, suggesting that chitin is not as recalcitrant as it is sometimes believed to be. Thus, ‘recalcitrance’ of chitin is relative, rather than absolute and a matter of accessibility to the soil microbiome that is collectively adapted to degrade ubiquitous and abundant naturally occurring structural polysaccharides like chitin and cellulose.
... The length distribution of the tags was plotted in R (R Core Team, 2012). For taxonomic classifications and statistical diversity, OTUs called at 97% sequence similarity were used (Nebel et al., 2011;Dunthorn et al., 2014). The core (the longest and thus most informative) sequence for each phylotype at 97% was extracted into a FASTA file. ...
... The core (the longest and thus most informative) sequence for each phylotype at 97% was extracted into a FASTA file. This file was analyzed with JAguc software (Nebel et al., 2011). JAguc employed BLASTn searches, with algorithm parameters adjusted for short (200-500 bp) reads (-m 7 -r 5 − q − 4 − G 8 -E 6 -b 50). ...
Eukaryotic microbes inhabiting diverse ecological niches are capable of mediating biogeochemical shifts. Here, we studied the distribution patterns of protistan community in oxygen-deficient sites in the Arabian Sea and nearby estuarine waters. Protist diversity was quantified through Illumina Miseq sequencing of the V4 region of 18S rRNA gene amplicons. Overall, 12687 OTUs represented the diverse protist communities at various sampling sites such as the open ocean, outer shelf and inner shelf along the oxygen gradient. As per Alpha diversity estimation, estuarine communities were less diverse than the coastal, and open ocean sites. Multivariate analysis was applied to differentiate the community structure in estuarine, coastal and open ocean sites. The results indicated distinct community variation between oxic, hypoxic and suboxic water column at a comparatively deep sea station. However, the influence of dissolved oxygen was statistically insignificant for the protist distribution. The DistLM analysis suggests that the adaptation of protist communities across the spatial habitats could be significantly correlated with temperature, salinity, and nitrate. Moreover, chlorophyll a was the important environmental variable associated with the estuarine complex, whereas salinity, nitrate, and temperature influenced coastal and open ocean stations.
... The reads of bacterial genes were trimmed to nearly equal sequence lengths (446 bp for 16S rRNA, 440 bp for mxaF), amplicon pyrosequencing errors were corrected using ACACIA, and potential 16S rRNA chimeric sequences were sorted out using the UCHIME algorithm implemented in USEARCH and the latest RDP Gold database for high-quality 16S rRNA gene reference sequences (Edgar et al., 2011;Bragg et al., 2012). Using JAguc v2.1, the sequences were clustered into operational taxonomic units (OTUs) applying the UPGMA model (Nebel et al., 2011). The OTUs of 16S rRNA were clustered at the family level using 90.1% as the pairwise similarity cut-off value (to ensure sufficient sampling depth), and mxaF OTUs were clustered with a cut-off value of 90%, which was higher than that previously reported, to obtain a higher diversity (Yarza et al., 2010;Stacheter et al., 2013). ...
Methanol is an abundant atmospheric volatile organic compound that is released from both living and decaying plant material. In forest and other aerated soils, methanol can be consumed by methanol-utilizing microorganisms that constitute a known terrestrial sink. However, the environmental factors that drive the biodiversity of such methanol-utilizers have been hardly resolved. Soil-derived isolates of methanol-utilizers can also often assimilate multicarbon compounds as alternative substrates. Here, we conducted a comparative DNA stable isotope probing experiment under methylotrophic (only [¹³C1]-methanol was supplemented) and combined substrate conditions ([¹²C1]-methanol and alternative multi-carbon [¹³Cu]-substrates were simultaneously supplemented) to (i) identify methanol-utilizing microorganisms of a deciduous forest soil (European beech dominated temperate forest in Germany), (ii) assess their substrate range in the soil environment, and (iii) evaluate their trophic links to other soil microorganisms. The applied multi-carbon substrates represented typical intermediates of organic matter degradation, such as acetate, plant-derived sugars (xylose and glucose), and a lignin-derived aromatic compound (vanillic acid). An experimentally induced pH shift was associated with substantial changes of the diversity of active methanol-utilizers suggesting that soil pH was a niche-defining factor of these microorganisms. The main bacterial methanol-utilizers were members of the Beijerinckiaceae (Bacteria) that played a central role in a detected methanol-based food web. A clear preference for methanol or multi-carbon substrates as carbon source of different Beijerinckiaceae-affiliated phylotypes was observed suggesting a restricted substrate range of the methylotrophic representatives. Apart from Bacteria, we also identified the yeasts Cryptococcus and Trichosporon as methanol-derived carbon-utilizing fungi suggesting that further research is needed to exclude or prove methylotrophy of these fungi.
... Per gene library, plasmids were extracted from 96 clones, and inserts were Sanger sequenced (4 gene libraries x 96) at LGC genomics (Berlin, Germany). nifH sequences were clustered with JAGUC2 and OTUs were called at 97% sequence similarity 33,34 . Cluster representatives were phylogenetically affiliated with BLASTX 35 . ...
Biological N2 fixation (BNF) in the rhizosphere of Podocarpaceae is currently attributed to unspecific
diazotrophs with negligible impact on N acquisition. Here, we report specific and high associative
BNF in dead cells of root nodules of Lepidothamnus fonkii distributed in ombrotrophic peatlands of
Patagonia. BNF of nodulated roots, intact plants of L. fonkii and rhizospheric peat was assessed by 15N2
and acetylene reduction. Diazotrophs were identified by electron microscopy, analysis of nitrogenase
encoding genes (nifH) and transcripts, and 16S rRNA. Nitrogenase encoding nifH transcripts from
root nodules point to Beijerinckiaceae (Rhizobiales), known as free-living diazotrophs. Electron
microscopy and 16S rRNA analysis likewise identified active Beijerinckiaceae in outer dead cells of
root nodules. NifH transcripts from the rhizopshere peat revealed diverse active diazotrophs including
Beijerinckiaceae. Both methods revealed high activity of nitrogenase rates in cut roots of L. fonkii
(2.5 μmol N g−1 d.w. d−1 based on 15N2 assay; 2.4 μmol C2H4 g−1 d.w. d−1 based on acetylene reduction
assay). The data suggest that (i) nodules recruit diazotrophic Beijerinckiaceae from peat, (ii) dead nodule
cells provide an exclusive habitat for Beijerinckiaceae, and (iii) BNF in L. fonkii is one potent pathway to
overcome N deficiency in ombrotrophic peatlands of Patagonia.
... Using a custom script (Appendix S1, Supporting information), an OTU contingency table was created based on the output files of SWARM. Representative sequences (i.e. the most abundant sequence) from each OTU were extracted and analysed with the software package JAGUC (Nebel et al. 2011) and GenBank's nr nucleotide database release 202 as reference database. The tabular taxonomic information and the OTU contingency ...
Microbial eukaryotes hold a key role in aquatic ecosystem functioning. Yet, their diversity in freshwater lakes, particularly in high-mountain lakes, is relatively unknown compared to the marine environment. Low nutrient availability, low water temperature and high ultraviolet radiation make most high-mountain lakes extremely challenging habitats for life and require specific molecular and physiological adaptations. We therefore expected that these ecosystems support a plankton diversity that differs notably from other freshwater lakes. In addition, we hypothesized that the communities under study exhibit geographic structuring. Our rationale was that geographic dispersal of small-sized eukaryotes in high-mountain lake over continental distances seems difficult. We analyzed hypervariable V4 fragments of the SSU rRNA gene to compare the genetic microbial eukaryote diversity in high-mountain lakes located in the European Alps, the Chilean Altiplano, and the Ethiopian Bale Mountains. Microbial eukaryotes were not globally distributed corroborating patterns found for bacteria, multicellular animals and plants. Instead, the plankton community composition emerged as a highly specific fingerprint of a geographic region even on higher taxonomic levels. The intra-regional heterogeneity of the investigated lakes was mirrored in shifts in microbial eukaryote community structure, which, however, was much less pronounced compared to inter-regional beta-diversity. Statistical analyses revealed that on a regional scale, environmental factors are strong predictors for plankton community structures in high-mountain lakes. While on long-distance scales (>10,000 km), isolation-by-distance is the most plausible scenario, on intermediate scales (up to 6000 km), both, contemporary environmental factors and historical contingencies interact to shift plankton community structures. This article is protected by copyright. All rights reserved.
