- Open Access
Hunters or farmers? Microbiome characteristics help elucidate the diet composition in an aquatic carnivorous plant
- Dagmara Sirová†1, 2Email authorView ORCID ID profile,
- Jiří Bárta†2,
- Karel Šimek1, 2,
- Thomas Posch3,
- Jiří Pech2,
- James Stone4, 5,
- Jakub Borovec1,
- Lubomír Adamec6 and
- Jaroslav Vrba1, 2
© The Author(s). 2018
- Received: 24 July 2018
- Accepted: 18 November 2018
- Published: 17 December 2018
The Correction to this article has been published in Microbiome 2019 7:4
Utricularia are rootless aquatic carnivorous plants which have recently attracted the attention of researchers due to the peculiarities of their miniaturized genomes. Here, we focus on a novel aspect of Utricularia ecophysiology—the interactions with and within the complex communities of microorganisms colonizing their traps and external surfaces.
Bacteria, fungi, algae, and protozoa inhabit the miniature ecosystem of the Utricularia trap lumen and are involved in the regeneration of nutrients from complex organic matter. By combining molecular methods, microscopy, and other approaches to assess the trap-associated microbial community structure, diversity, function, as well as the nutrient turn-over potential of bacterivory, we gained insight into the nutrient acquisition strategies of the Utricularia hosts.
We conclude that Utricularia traps can, in terms of their ecophysiological function, be compared to microbial cultivators or farms, which center around complex microbial consortia acting synergistically to convert complex organic matter, often of algal origin, into a source of utilizable nutrients for the plants.
- Ciliate bacterivory
- Digestive mutualism
- Nutrient turnover
- Plant–microbe interactions
- Utricularia traps
Plant-associated microorganisms have long been recognized as key partners in enhancing plant nutrient acquisition, mitigating plant stress, promoting growth, or facilitating successful defense mechanisms against pathogens or grazers . Apart from the well-studied and close symbioses such as mycorrhizal and rhizobial interactions, there is a large pool of diverse microorganisms in varying degrees of association with different plant surfaces and tissues. These often highly complex microbial communities clearly play a significant role in plant ecophysiology, but many of the underlying mechanisms governing these looser associations still remain unexplored .
One example of such associations is that between rootless aquatic carnivorous plants from the genus Utricularia and the complex microbial communities actively colonizing their traps [3–5] and external leaf surfaces . The exudation of large amounts of bioavailable photosynthates into Utricularia traps and their subsequent rapid utilization by the microorganisms present has been experimentally confirmed and represents a direct link between the plant host and associated microbiota [7, 8]. Utricularia are among the most numerous and cosmopolitan genera of carnivorous plants, attractive to researchers, due to their extremely small and unusual genomes [9–11]. Depending on the species and growth conditions, a single Utricularia plant may bear hundreds to thousands of traps, usually on highly segmented leaves (Additional file 1: Figure S1). These are tiny (1–5 mm long) liquid-filled bladders, whose lumen is completely isolated from the environment by a two-cell thick trap wall . Due to high respiration rates of both plant tissues and microorganisms present, traps become deeply anoxic at night or during intensive organic matter digestion. Short bursts of oxygenated water from the outside transiently improve the oxygen conditions each time the trap fires .
Utricularia were long thought to be classical examples of the carnivorous habit (Darwin, 1875). However, their nutrient acquisition strategy is the subject of debate and the importance of carnivory in their nutrition has been questioned [14, 15]. During trap lifespan, only a minority of traps capture a macroscopic prey, while all of them contain communities of microbial commensals [14, 16]. It has therefore been proposed that algae, frequently observed and abundant in both the plant periphyton and traps [15, 17], rather than metazoan plankton, are the main source of nutrients for the plants [18, 19]. Over a hundred different species from virtually all major freshwater algal groups were detected inside the traps of Utricularia species at a particular location, with large differences among plant species or sampling locations (for review, see ). However, only a few of the genera, mainly species capable of osmotrophy (Euglena spp., Phacus spp., Scenedesmus spp.), are able to survive and propagate in the traps. The rest of the algal cells die and decay, representing a potentially abundant source of nutrients for the plant-microbe system. According to previously published research, shoots of aquatic Utricularia serve as a substrate for rich periphytic communities and are often colonized significantly more abundantly than other aquatic macrophytes at the same location . Published data suggest that it is the periphyton itself, not the surrounding water, which is the main source of algal cells found inside of the traps .
Microbial community structure and diversity. We present the results of the trap microbiome (amplicon and metatranscriptome) sequencing, distinguishing between the inner and periphytic communities associated with two Utricularia species—U. australis and U. vulgaris.
The nutrient recycling potential by trap-inhabiting bacterivorous protists as well as their importance for plant growth in a third Utricularia species, U. reflexa.
Functional capabilities of trap-associated microorganisms with respect to gene expression.
In addition, we compare the microbial community structure with similar datasets from pitcher traps of other carnivorous plants, gut microflora of various vertebrates and invertebrates, including carnivores and detritivores, the rumen microbiota of various herbivores, and environmental samples from the soil, rhizosphere, and freshwater.
By combining molecular methods, microscopy, and meta-analysis, we were able to shed light onto the ecology of this highly specific microbial niche which represents a unique system in the study of plant–microbe interactions.
Unique trap-associated prokaryotic communities
We have also detected the family Bacteriovoracaceae in the lumen, whose members are known for being obligatory predators of other, especially Gram-negative, bacteria. There have been few studies of the ecological roles of predatory bacteria. They are, however, present in diverse habitats, which indicates that, like viruses, they are important determinants of microbial community dynamics and functioning . In the Utricularia traps, Bacteriovoraceae together with Myxococcales, another potentially predatory bacterial group, represent almost 5% (Additional file 2: Table S5a); both groups are metabolically active (Additional file 3: Table S6) and, therefore, likely to selectively influence the trap microbial community dynamics through enhanced mortality rates of particular bacterial species in this isolated environment .
Deeper analyses of our sequencing data revealed other interesting microbial functional guilds in the traps. These included the cellulolytic species capable of degrading complex organic material of plant (algal) origin (Additional file 2: Table S5a), for example, Clostridium, Ruminococcus, Caldicellulosiruptor, Butyrivibrio, Acetivibrio, Cellulomonas, Erwinia, Thermobifida, Fibrobacter, Cytophaga, and Sporocytophaga. Also notable is the significant presence of active myxobacteria (Cystobacter spp.), which are known to include cellulolytic species and are frequently isolated from systems with high decomposing plant material content . Overall the cellulolytic bacteria represented approx. 10% of the total bacterial community (Table 3, Additional file 2: Table S5a). The transcriptomic analysis offers several clues indicating the ability of these microbes to degrade complex organic material of algal origin. Algal cell walls and other cellular structures are composed of various monosaccharides, derived from glucose, linked into polymers (cellulose and hemicellulose). These monosaccharides also include D-galactose . The α- and β-galactosidases catalyze the cleavage of the terminal D-galactosyl residues of plant and algal hemicelluloses and their activity is often associated with herbivore digestive systems [35, 36]. These were among the most expressed prokaryotic genes in Utricularia traps (Additional file 4: Table S7), together with UDP-glucose 4-epimerase, which performs the final step in the Leloir pathway catalyzing the reversible conversion of UDP-galactose to UDP-glucose. The high expression levels of these enzymes underscore the importance of microbial galactose metabolism in the traps and are a further indication that the trap microbes, especially bacteria, actively degrade complex algal/plant material. Other enzymes, such as those belonging to the families of glycoside hydrolases, cellulases, peroxidases, and xylanases, were also found to be expressed in the trap lumen (Additional file 4: Table S7).
Looking at Utricularia-associated microbiome structure, despite of the high similarity between the trap lumen and the periphyton in terms of prokaryotic community composition, when we compare the microbial co-occurrence analyses, we see two strikingly different systems with distinct potential “keystone” taxa (Additional file 1: Table S4) and a distinct degree of interconnectedness (Additional file 1: Figures S3 and S4) in each of the two environments. While the periphytic communities show a co-occurrence pattern typically observed in highly spatially and functionally interconnected microbial biofilms (Additional file 1: Figure S3), the co-occurrence pattern of the trap community consists of several smaller, mutually disconnected microbial networks and implies a much more heterogeneous and fragmented environment inside the trap lumen (Additional file 1: Figure S4). This result is consistent with previously published observations showing progressing degree of microbial aggregation into flocks and multispecies biofilms with progressing Utricularia trap development . Further support is provided by the metatranscriptomic data. The high expression of bacterial UDP-glucose 6-dehydrogenase, which has been linked to the environmentally regulated biosynthesis of exopolysaccharides , or that of transaldolase, which is also one of the highly expressed proteins in the trap fluid and has been shown to be an important colonization factor favoring the establishment of bacteria in the gut , provides further support for bacterial aggregation and attachment to organic particles in the trap lumen. This activity is typical for the gut environment of herbivores and suggests that metabolically related organisms in the Utricularia trap lumen associate with their preferred substrates and produce the myriad of enzymes necessary for the digestion of chemically and structurally complex particles, hence creating a system of mutually disconnected micro-environments.
Traps as methane sources?
Herbivore gut ecosystems generally tend to produce copious amounts of methane as a result of the anaerobic respiration activity by the strictly anaerobic methanogenic Archaea . Using gas chromatography, we have not detected the release of methane gas from the Utricularia traps (data not shown), and methanogens were not detected in our trap fluid samples using the qPCR assay (Additional file 1: Table S3). However, significant amounts of diverse methanotrophs were found in the traps, constituting up to 40% of the total prokaryotic community (Additional file 1: Table S3, Additional file 2: Table S5b. These included active obligate methanotrophs, for example, from the genus Methylococcus (Gammaproteobacteria, Additional file 2: Table S5). Moreover, methane metabolism was also found to be one of the most expressed prokaryotic modules (KEGG) in the trap fluid metatranscriptome from U. vulgaris (Table 1). This raises a question of where the methanotrophs acquire methane since there are no active methanogens. These somewhat paradoxical results may be explained by a recent discovery  that the degradation of mainly polysaccharides and their derivates in the aquatic environment by commonly occurring bacteria, e.g., Pseudomonas spp., can, even in the presence of oxygen, result in the release of methane, ethylene, and propylene.
We speculate that this process can explain the presence and activity of methanotrophs in the Utricularia traps, which may metabolize all of the produced methane, thus preventing its detection. This hypothesis, however, needs to be experimentally verified.
Trap-associated eukaryotic communities
Compared to the prokaryotes, the eukaryotic communities were relatively poor in diversity. The most diverse and abundant group were the Algae, whose species composition and richness was described in detail elsewhere [18, 24]. However, we also found the Fungi to be present in the traps as a significant proportion of the total microbial community, as quantified by qPCR (Additional file 1: Table S3). Many fungal taxa, whose presence inside of the Utricularia traps was determined by SSU rRNA sequencing (e.g., Chrysomphalina sp., Agaricales, Basidiomycota, Additional file 2: Table S5c), were most probably entrapped as spores from the ambient environment and do not represent trap-associated microbes as such, but rather a potential source of nutrients. Others, most notably the saprotrophic Basidiobolus sp. (Basidiobolales, Zygomycota) abundant in the traps of all ages (up to 45% of total OTUs), or species belonging to the Chytridiomycota (Additional file 2: Table S5c), found to be actively growing in the traps (Additional file 3: Table S6), are likely a component of the trap microbial network and contribute to the nutrient release and assimilation by the plant host.
The estimates of bacterial and ciliate numbers, the individual grazing rate (IGR) and total grazing rate (TGR) of ciliates and the turnover rate of bacterial standing stock (turnover) in U. reflexa traps of different age is presented. Means of three technical replicates are shown for IGR
[bact. prot.− 1 h− 1]
[106 bact. ml−1 d− 1]
Relative proportions (%) of selected ecologically relevant prokaryotic functional guilds in different U. vulgaris trap ages (young, mature, and old)
DNRA (nrfA gene)
Urea decomposers (ureA gene)
Experimental design, plant material, and sampling
To assess the presence and diversity of trap associated microbiota, the ecophysiologically well characterized aquatic species U. vulgaris and U. australis were selected. Adult U. australis plants (40–50 cm in length) were collected from a mesotrophic bog at Ruda fishpond (South Bohemia, see  for details). The 0.8 m2 polypropylene experimental container, where U. vulgaris plants were cultivated, contained Carex sp. litter and approximately 250 l of dystrophic water, closely simulating natural conditions [51, 52]. For the assessment of microbial community structure, U. vulgaris and U. australis plants were divided into three sections of increasing age (young, mature, old). From each of these segments, approximately 70 larger, excised, functional traps without visible metazoan prey and trapless leaves with periphyton were collected (approximately 200 mg fresh weight).
To assess the actively transcribed microbial gene pool, excised U. vulgaris traps from the entire shoot without visible metazoan prey were collected randomly (approximately 250 mg fresh weight), with pooled traps from a single plant considered a replicate; three biological replicates were collected in total. All collected plant material was immediately placed into liquid N2 and samples were stored at −80 °C until further processing.
For the estimation of the protozoan grazing rates, a different species with larger traps—the tropical U. reflexa—was selected, because relatively large volumes of trap fluid are needed for this analysis. The plants were cultivated indoors in 3-l aquaria, in dystrophic cultivation water closely simulating natural conditions (see ).
DNA extraction from Utricularia trap fluid and the taxonomical evaluation of the Utricularia-associated microorganisms
Nucleic acid extractions were conducted according to a modified bead-beating protocol . Approximately 500 μl of pooled trap fluid were extracted for each sample. Total DNA was quantified fluorometrically using SybrGreen and StepOne (Applied Biosystems, USA) instrument in “fluorescence reading mode” . The PCR primers (515F/806R) targeted the V4 region of the SSU rRNA, previously shown to yield accurate phylogenetic information and to have only a few biases against any bacterial taxa [55–57]. Each sample was amplified in triplicate, combined, and quantified using Invitrogen PicoGreen and a plate reader, and equal amounts of DNA from each amplicon were pooled into a single 1.5-ml microcentrifuge tube. Once pooled, amplicons were cleaned up using the UltraClean PCR Clean-up kit (MO BIO Laboratories). Amplicons were sequenced on the Illumina MiSeq platform at the Institute of Genomics and Systems Biology, Argonne National Laboratory, Argonne (Chicago, USA). Paired-end reads were joined using Perl scripts yielding approximately 253 bp amplicons. Approximately 1.8 million paired-end reads were obtained with average 66.000 reads per sample. Quality filtering of reads and chimera check (UCHIME algorithm in de novo mode) was applied as described previously . Reads were assigned to operational taxonomic units (OTUs, cutoff 97% sequence identity) using an open-reference OTU picking protocol with QIIME implemented scripts . Reads were taxonomically assigned using Green Genes database, release 13.08 as reference. Those reads which were assigned as “chloroplast” and “mitochondrion” were excluded from further analyses. For the estimation of unique microbial taxa in U. australis and U. vulgaris traps and periphyton, the OTUs were grouped at the genus level. Genera presented only in U. australis or U. vulgaris and respective trap or periphyton samples were classified as unique for each microbiome. Differences between the various prokaryotic communities were tested with PERMANOVA and the nonparametric method adonis in QIIME 1.9.0.
Comparative meta-analyses of prokaryotic communities from different habitats
To compare the composition of Utricularia trap-associated microbial communities, data (OTU tables in biom format) from nine relevant studies representing different habitats were analyzed. Seven of the studies were obtained from Qiita (https://qiita.ucsd.edu/) database (Additional file 1: Table S1). The remaining two studies were obtained from NCBI Genebank: the 16S rRNA sequences of the Nepenthes pitcher microbiome from the SRA archive (project ID PRJNA225539) and Sarracenia pitcher sequences from the Genebank database (accession numbers JF745346–JF745532 and JN368236–JN368422) (Additional file 1: Table S1). Altogether, 4221 samples were included in the meta-analysis. The Qiita database works with the closed-reference OTU picking algorithm; we have therefore processed our sequences and also the sequences from Nepenthes and Sarracenia pitcher microbiomes in the same way as the Qiita pipeline, to ensure comparability with Qiita OTU tables. All OTU tables were then merged together using Qiime scripts and analyzed as one dataset. Non-metric multidimensional scaling (NMDS) using Bray-Curtis dissimilatory metrics was used for computing distances between samples (Fig. 1a). LDA Effect Size (LEfSe) based on the relative abundances of the microbial taxa was calculated to identify the corresponding taxa with higher abundance in U.australis and U.vulgaris samples . Analysis of LEfSe was performed according to the instructions on the website (http://huttenhower.sph.harvard.edu/galaxy).To obtain a more function-related point of view, three Utricularia vulgaris metatranscriptomes were compared to 43 metagenomes and/or metatranscriptomes available from six different habitats (Fig. 1b). The sequences from these studies were obtained from the MG-RAST server (Additional file 1: Table S1).
RNA-seq analysis for functional profiling of the U. vulgaris trap-associated microbiome
To assess the actively transcribed microbial gene pool, total RNA was extracted from the U. vulgaris trap samples (n = 3), using the protocol identical to that described in detail previously . Briefly, DNA was removed from the extracts and two transcriptomic libraries, eukaryotic and prokaryotic, were created at the Institute of Genomics and Systems Biology, Argonne National Laboratory, Argonne (Chicago, USA) using standard Illumina TruSeq RNA library preparation kits. The ribosomal RNA as well as eukaryotic (plant) RNA fraction was removed in order to enrich prokaryotic transcripts, and, vice versa, eukaryotic transcript enrichment was performed in parallel, to capture transcripts from fungi, protists, and other eukaryotic microorganisms. Enriched mRNA from both libraries was reverse transcribed to create metatranscriptomic libraries and sequenced using Illumina HiSeq platform (100 × 100 cycle paired-end run). We obtained approximately 40 million paired-end reads per sample. Reads were quality checked; low quality reads and reads with ambiguous bases were filtered out. Reads from all three replicates (approx. 120 million sequences) were then assembled with Velvet Optimizer  which resulted in approximately 500,000 contigs. In this step, we filtered out the potential Utricularia transcripts by blasting contigs against our Utricularia reference transcriptome . All contigs which gave significant hit (e value < 0.0001, min score 80) were excluded from further analyses and considered as Utricularia transcripts. Contigs were also blasted against the SILVA database (release 111) to identify ribosomal RNAs (rRNAs). Those sequences that gave BLAST bit score greater than 80 were marked as rRNAs and extracted from the dataset. Reads were then mapped back onto the remaining contigs using Trinity package (bowtie algorithm with default parameters  with FPKM gene transcript abundance normalization). To identify potential prokaryotic functional gene transcripts, the remaining contigs without rRNAs were blasted against the nr database with e value of 0.001 using diamond algorithm . Annotation was done in MEGAN 6 software . Genes below hit score 50 were manually excluded from the analyses (Additional file 4: Table S7).
The lists of bacterial and archaeal species for each ecologically relevant functional gene was downloaded from the FunGene database  from which a local database was created (Additional file 5: Table S8). The OTUs which were taxonomically annotated to genus level were scanned against this database for the presence of the specific functional genes (Additional file 5: Table S8).
Microbial network analyses in U. vulgaris and U. australis traps and periphyton
The relative abundances of OTUs were square-root transformed  (Additional file 6). To avoid spurious correlations caused by the presence of rare OTUs, we chose only those OTUs which were found in at least five out of nine traps and five out of eight U.vulgaris periphyton samples, and their sum of abundance was at least 20 and 16 sequences out of 1000, respectively. The resulting OTU tables, separately for the trap (15 samples) and the periphyton (16 samples), were used for microbial network analyses . We performed the recommended calculations (neff, sparsity) regarding the composition of prokaryotic filtered OTU tables. Based on the sparsity of filtered OTU tables, we chose the CoNet network algorithm as the relevant calculation method [68, 69]. The parameters and settings for network analyses in the CoNET application were as follow: -parent_child_exclusion, -row_minocc 5, -correlations (Spearman, Pearson, mutual information, Bray-Curtis and Kullback-Leibler dissimilatory). The threshold for edge selection was set to 1000 top and bottom. During randomization, 100 iterations were calculated for edge scores. In the following bootstrap step, 100 iterations were calculated, and unstable edges were filtered out (p-level threshold of 0.05). The Brown method was chosen as the P value merging method, and the Benjamini–Hochberg procedure was selected for multiple test correction. The resulting network was visualized and analyzed (i.e., degree of nodes, betweenness centrality, closeness centrality) in Cytoscape 3.0.2. Potential keystone OTUs were identified .
Raw sequences of 16S rRNA, ITS1 amplicons, and raw sequences of all three metatranscriptomes were deposited in European Nucleotide Archive (ENA) under study ID PRJEB25993. Annotated metatranscriptomic sequences were deposited at the following website: http://utricularia.prf.jcu.cz/
Quantification of trap-associated bacterial, fungal, methanogenic, and methanotrophic communities in U. vulgaris and U. australis
For quantification of bacterial, fungal, methanogenic and methanotrophic communities, the quantitative PCR (qPCR) of targeted 16S rRNA, 18S rRNA, mcrA, and pmoA gene was used, respectively. For detail description, please see Additional files 1, 2, 3, 4, 5, and 6.
Bacterial and protozoan enumeration and the estimation of protozoan grazing rates in U. reflexa
Ten U. reflexa plants were divided into three segments of increasing age (young, mature, old). Each segment contained six leaf whorls. Trap fluid was collected from the traps in each segment (see ), and a pooled sample (~ 750 μl for each age category) from all ten plants was made. Bacterial and protozoan counts in the trap fluid samples were estimated using epifluorescence microscopy, according to methods described previously .
The protist grazing rates were estimated using fluorescently labeled bacteria (FLB) as a tracer. The FLB were prepared from the strain Limnohabitans planktonicus, as detailed in . Cell sizes of the strain are comparable to that of bacterial cells commonly occurring within the U. reflexa traps. The FLB uptake rates were determined in short-term triplicate experiments, where tracer FLB were added to the trap-fluid samples to constitute 6–8% of the total bacterial concentration. For further details on sample fixation, protist staining and enumeration, and tracer ingestion determinations, see . At least 45 ciliates were inspected for FLB ingestion in each replicate sample. To estimate total protist grazing, we multiplied average uptake rates of protozoa by their in situ abundances as previously described .
We would like to acknowledge Dr. Helena Štorchová (Institute of Experimental Botany CAS) for her help and enthusiastic support of the project, as well as Hana Petrásková for her invaluable help in the laboratory.
This study was funded by the Czech Research Projects CSF P504/11/0783 (to LA) and CSF P504-17-10493S (to DS), as well as the Long-term research development project No. RVO 67985939 (to LA) and BC CAS, SoWa (MEYS projects LM2015075 and EF16_013/0001782 - SoWa Ecosystems Research).
Availability of data and materials
All genetic raw data generated during this study have been uploaded to the European Nucleotide Archive (ENA) under the study ID PRJEB25993. Metatranscriptomic and amplicon data were also deposited on the following web page: http://utricularia.prf.jcu.cz within the section “Other/Download”. The datasets downloaded from the Qiita (https://qiita.ucsd.edu/) database or the MG-RAST server (https://www.mg-rast.org/) and used in supporting the conclusions are referenced in this article and its supplementary material.
DS, JB, LA, and JV designed the research. DS, LA, and JV collected the samples. JB supervised the laboratory molecular work and bioinformatics analyses. JB, JS, and JP performed the bioinformatic analyses. JakBor supervised and performed the chemical analyses. KŠ and TP performed the ciliate-related analyses. DS and JB drafted the manuscript. All authors commented on previous versions of the manuscript and approved the final version.
Ethics approval and consent to participate
The authors declare that they have no competing interests.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Berg G, Grube M, Schloter M, Smalla K. Unraveling the plant microbiome: looking back and future perspectives. Front Microbiol. 2014;5:148.PubMedPubMed CentralGoogle Scholar
- Rinke C, Schwientek P, Sczyrba A, Ivanova NN, Anderson IJ, Cheng J-F, et al. Insights into the phylogeny and coding potential of microbial dark matter. Nature. 2013;499:431–7.View ArticleGoogle Scholar
- Sirová D, Borovec J, Černá B, Rejmánková E, Adamec L, Vrba J. Microbial community development in the traps of aquatic Utricularia species. Aquat Bot. 2009;90:129–36.View ArticleGoogle Scholar
- Caravieri FA, Ferreira AJ, Ferreira A, Clivati D, de Miranda VFO, Araújo WL. Bacterial community associated with traps of the carnivorous plants Utricularia hydrocarpa and Genlisea filiformis. Aquat Bot. 2014;116:8–12.View ArticleGoogle Scholar
- Alcaraz LD, Martínez-Sánchez S, Torres I, Ibarra-Laclette E, Herrera-Estrella L. The metagenome of Utricularia gibba’s traps: into the microbial input to a carnivorous plant. PLoS One. 2016;11:e0148979.View ArticleGoogle Scholar
- Díaz-Olarte J, Valoyes-Valois V, Guisande C, Torres NN, González-Bermúdez A, Sanabria-Aranda L, et al. Periphyton and phytoplankton associated with the tropical carnivorous plant Utricularia foliosa. Aquat Bot. 2007;87:285–91.View ArticleGoogle Scholar
- Sirová D, Borovec J, Šantrůčková H, Šantrůček J, Vrba J, Adamec L. Utricularia carnivory revisited: plants supply photosynthetic carbon to traps. J Exp Bot. 2010;61:99–103.View ArticleGoogle Scholar
- Sirová D, Borovec J, Picek T, Adamec L, Nedbalová L, Vrba J. Ecological implications of organic carbon dynamics in the traps of aquatic carnivorous Utricularia plants. Funct Plant Biol. 2011;38:583–93.View ArticleGoogle Scholar
- Carretero-Paulet L, Chang TH, Librado P, Ibarra-Laclette E, Herrera-Estrella L, Rozas J, et al. Genome-wide analysis of adaptive molecular evolution in the carnivorous plant Utricularia gibba. Genome Biol Evol. 2015;7:444–56.View ArticleGoogle Scholar
- Carretero-Paulet L, Librado P, Chang TH, Ibarra-Laclette E, Herrera-Estrella L, Rozas J, et al. High gene family turnover rates and gene space adaptation in the compact genome of the carnivorous plant Utricularia gibba. Mol Biol Evol. 2015;32:1284–95.View ArticleGoogle Scholar
- Silva SR, Alvarenga DO, Aranguren Y, Penha HA, Fernandes CC, Pinheiro DG, et al. The mitochondrial genome of the terrestrial carnivorous plant Utricularia reniformis (Lentibulariaceae): structure, comparative analysis and evolutionary landmarks. PLoS One. 2017;12:e0180484.View ArticleGoogle Scholar
- Adamec L. Oxygen concentrations inside the traps of the carnivorous plants Utricularia and Genlisea (Lentibulariaceae). Ann Bot. 2007;100:849–56.View ArticleGoogle Scholar
- Sirová D, Bárta J, Borovec J, Vrba J. The Utricularia-associated microbiome: composition, function, and ecology. Carnivorous Plants Physiology, Ecology, and Evolution. Oxford University Press. 2018;Chapter 25: 349–58.Google Scholar
- Darwin C. Insectivorous plants. New York: D. Appleton and Company; 1875.Google Scholar
- Richards JH. Bladder function in Utricularia purpurea (Lentibulariaceae): is carnivory important? Am J Bot. 2001;88:170–6.Google Scholar
- Friday LE. Rapid turnover of traps in Utricularia vulgaris L. Oecologia. 1989;80:272–7.View ArticleGoogle Scholar
- Płachno BJ, Łukaszek M, Wołowski K, Adamec L, Stolarczyk P. Aging of Utricularia traps and variability of microorganisms associated with that microhabitat. Aquat Bot. 2012;97:44–7.View ArticleGoogle Scholar
- Peroutka M, Adlassnig W, Volgger M, Lendl T, Url WG, Lichtscheidl IK. Utricularia: a vegetarian carnivorous plant? Agae as prey of bladderwort in oligotrophic bogs. Plant Ecol. 2008;199:153–62.View ArticleGoogle Scholar
- Alkhalaf IA, Hübener T, Porembski S. Prey spectra of aquatic Utricularia species (Lentibulariaceae) in northeastern Germany: the role of planktonic algae. Flora Morphol Distrib Funct Ecol Plants. 2009;204:700–8.View ArticleGoogle Scholar
- Nalepa C a, Bignell DE, Bandi C. Detritivory, coprophagy, and the evolution of digestive mutualisms in Dictyoptera. Insect Soc. 2001;48:194–201.View ArticleGoogle Scholar
- Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR, Bircher JS, et al. Evolution of mammals and their gut microbes. Science. 2008;320:1647–51.View ArticleGoogle Scholar
- Barboza PS, Bennett A, Lignot J-H, Mackie RI, McWhorter TJ, Secor SM, et al. Digestive challenges for vertebrate animals: microbial diversity, cardiorespiratory coupling, and dietary specialization. Physiol Biochem Zool. 2010;83:764–74.View ArticleGoogle Scholar
- Adamec L. Functional characteristics of traps of aquatic carnivorous Utricularia species. Aquat Bot. 2011;3:226–33.View ArticleGoogle Scholar
- Adlassnig W, Peroutka M, Lendl T. Traps of carnivorous pitcher plants as a habitat: composition of the fluid, biodiversity and mutualistic activities. Ann Bot. 2011;107:181–94.View ArticleGoogle Scholar
- Troyer K. Diet selection and digestion in Iguana iguana: the importance of age and nutrient requirements. Oecologia. 1984;61:201–7.View ArticleGoogle Scholar
- Berg M, Zhou XY, Shapira M. Host-specific functional significance of Caenorhabditis gut commensals. Front Microbiol. 2016. https://doi.org/10.3389/fmicb.2016.01622.
- Willems A. The family Comamonadaceae. The prokaryotes: alphaproteobacteria and Betaproteobacteria. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. The Prokaryotes. Berlin: Springer; 2014.Google Scholar
- Slobodkin A. The family peptostreptococcaceae. The prokaryotes: firmicutes and tenericutes. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. The Prokaryotes. Berlin: Springer; 2014.Google Scholar
- Attwood GT, Klieve AV, Ouwerkerk D, Patel BKC. Ammonia-hyperproducing bacteria from New Zealand ruminants. Appl Environ Microbiol. 1998;64:1796–804.PubMedPubMed CentralGoogle Scholar
- Sirová D, Šantrůček J, Adamec L, Bárta J, Borovec J, Pech J, et al. Dinitrogen fixation associated with shoots of aquatic carnivorous plants: is it ecologically important? Ann Bot. 2014;114:125–33.View ArticleGoogle Scholar
- Velicer GJ, Mendes-Soares H. Bacterial predators. Curr Biol. 2009;19:R55–6.View ArticleGoogle Scholar
- Chauhan A, Cherrier J, Williams HN. Impact of sideways and bottom-up control factors on bacterial community succession over a tidal cycle. PNAS. 2009;106:4301–6.View ArticleGoogle Scholar
- Dawid W. Biology and global distribution of myxobacteria in soils. FEMS Microbiol Rev. 2000;24:403–27.View ArticleGoogle Scholar
- Popper ZA, Michel G, Hervé C, Domozych DS, Willats WGT, Tuohy MG, et al. Evolution and diversity of plant cell walls: from algae to flowering plants. Annu Rev Plant Biol. 2011;62:567–90.View ArticleGoogle Scholar
- Yapi Assoi Yapi D, Gnakri D, Lamine Niamke S, Patrice Kouame L. Purification and biochemical characterization of a specific beta-glucosidase from the digestive fluid of larvae of the palm weevil, Rhynchophorus palmarum. J Insect Sci. 2009;9:4.View ArticleGoogle Scholar
- Chen B, Teh BS, Sun C, Hu S, Lu X, Boland W, et al. Biodiversity and activity of the gut microbiota across the life history of the insect herbivore Spodoptera littoralis. Sci Rep. 2016;6:29505.View ArticleGoogle Scholar
- Petit C, Rigg GP, Pazzani C, Smith A, Sieberth V, Stevens M, et al. Region 2 of the Escherichia coli K5 capsule gene cluster encoding proteins for the biosynthesis of the K5 polysaccharide. Mol Microbiol. 1995;17:611–20.View ArticleGoogle Scholar
- González-Rodríguez I, Sánchez B, Ruiz L, Turroni F, Ventura M, Ruas-Madiedo P, et al. Role of extracellular transaldolase from Bifidobacterium bifidum in mucin adhesion and aggregation. Appl Environ Microbiol. 2012;78:3992–8.View ArticleGoogle Scholar
- Hackstein JHP, Van Alen TA. Fecal methanogens and vertebrate evolution. Evolution. 2016;50:559–72.View ArticleGoogle Scholar
- Repeta DJ, Ferrón S, Sosa OA, Johnson CG, Repeta LD, Acker M, et al. Marine methane paradox explained by bacterial degradation of dissolved organic matter. Nat Geosci. 2016;9:884–7.View ArticleGoogle Scholar
- Towne G, Nagaraja TG, Brandt RT, Kemp KE. Dynamics of ruminal ciliated protozoa in feedlot cattle. Appl Environ Microbiol. 1990;56:3174–8.PubMedPubMed CentralGoogle Scholar
- Abraham JV, Butler RD, Sigee DC. Ciliate populations and metals in an activated-sludge plant. Water Res. 1997;31:1103–11.View ArticleGoogle Scholar
- Pitsch G, Adamec L, Dirren S, Nitsche F, Šimek K, Sirová D, et al. The green Tetrahymena utriculariae n. sp. (Ciliophora, Oligohymenophorea) with its endosymbiotic algae (Micractinium sp.), living in traps of a carnivorous aquatic plant. J Eukaryot Microbiol. 2017;64:322–35.View ArticleGoogle Scholar
- Šimek K, Pitsch G, Salcher MM, Sirová D, Shabarova T, Adamec L, et al. Ecological traits of the algae-bearing Tetrahymena utriculariae (Ciliophora) from traps of the aquatic carnivorous plant Utricularia reflexa. J Eukaryot Microbiol. 2017;64:336–48.View ArticleGoogle Scholar
- Šimek K, Jürgens K, Nedoma J, Comerma M, Armengol J. Ecological role and bacterial grazing of Halteria spp.: small freshwater oligotrichs as dominant pelagic ciliate bacterivores. Aquat Microb Ecol. 2000;22:43–56.View ArticleGoogle Scholar
- Simek K, Armengol J, Comerma M, Garcia JC, Chrzanowski TH, Macek M, et al. Characteristics of protistan control of bacterial production in three reservoirs of different trophy. Int Rev Hydrobiol. 1998;83:485–94.View ArticleGoogle Scholar
- Thouvenot A. Bacterivory of metazooplankton, ciliates and flagellates in a newly flooded reservoir. J Plankton Res. 1999;21:1659–79.View ArticleGoogle Scholar
- Laybourn-Parry J. Protozoan plankton ecology. London: Chapman and Hall; 1992.Google Scholar
- Neuer S, Cowles TJ. Comparative size-specific grazing rates in field populations of ciliates and dinoflagellates. Mar Ecol Prog Ser. 1995;61:99–103.Google Scholar
- Koeck DE, Pechtl A, Zerlov VV, et al. Genomics of cellulolytic bacteria. Curr Opin Biotech. 2014;29:171–83.Google Scholar
- Adamec L, Sirová D, Vrba J. Contrasting growth effects of prey capture in two aquatic carnivorous plant species. Fundam Appl Limnol / Arch für Hydrobiol. 2010;176:153–60.View ArticleGoogle Scholar
- Borovec J, Sirová D, Adamec L. Light as a factor affecting the concentration of simple organics in the traps of aquatic carnivorous Utricularia species. Fundam Appl Limnol / Arch für Hydrobiol. 2012;181:159–66.View ArticleGoogle Scholar
- Urich T, Lanzen A, Qi J, Huson DH, Schleper C, Schuster SC. Simultaneous assessment of soil microbial community structure and function through analysis of the meta-transcriptome. PLoS One. 2008;3:e2527.View ArticleGoogle Scholar
- Leininger S, Urich T, Schloter M, Schwark L, Qi J, Nicol GW, et al. Archaea predominate among ammonia-oxidizing prokaryotes in soils. Nature. 2006;442:806–9.View ArticleGoogle Scholar
- Liu Z, Lozupone C, Hamady M, Bushman FD, Knight R. Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic Acids Res. 2007;35:e120.View ArticleGoogle Scholar
- Bates ST, Berg-Lyons D, Caporaso JG, Walters WA, Knight R, Fierer N. Examining the global distribution of dominant archaeal populations in soil. ISME J. 2011;5:908–17.View ArticleGoogle Scholar
- Bergmann GT, Bates ST, Eilers KG, Lauber CL, Caporaso JG, Walters WA, et al. The under-recognized dominance of Verrucomicrobia in soil bacterial communities. Soil Biol Biochem. 2011;43:1450–5.View ArticleGoogle Scholar
- Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6.View ArticleGoogle Scholar
- Segata N, Izard J, Walron L, Gevers D, Miropolsky L, Garrett W, Huttenhower C. Metagenomic biomarker discovery and explanation. Gen Biol. 2011;12:R60.View ArticleGoogle Scholar
- Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res. 2008;15:78.Google Scholar
- Bárta J, Stone JD, Pech J, Sirová D, Adamec L, Campbell MA, et al. The transcriptome of Utricularia vulgaris, a rootless plant with minimalist genome, reveals extreme alternative splicing and only moderate sequence similarity with Utricularia gibba. BMC Plant Biol. 2015;15:78.View ArticleGoogle Scholar
- Haas BJ, Papanicolaou A, Yassour M, Grabherr M, Blood PD, Bowden J, et al. De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis. Nat Protoc. 2013;8:1494–512.View ArticleGoogle Scholar
- Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12:59–60.View ArticleGoogle Scholar
- Huson DH, Beier S, Flade I, Górska A, El-Hadidi M, Mitra S, et al. MEGAN Community Edition - interactive exploration and analysis of large-scale microbiome sequencing data. PLoS Comput Biol. 2016;12:e1004957.View ArticleGoogle Scholar
- Fish JA, Chai B, Wang Q, Sun Y, Brown CT, Tiedje JM, et al. FunGene: the functional gene pipeline and repository. Front Microbiol. 2013;4:291.Google Scholar
- Berry D, Widder S. Deciphering microbial interactions and detecting keystone species with co-occurrence networks. Front Microbiol. 2014;5:219.View ArticleGoogle Scholar
- Weiss S, Van Treuren W, Lozupone C, Faust K, Friedman J, Deng Y, et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J. 2016;10:1669–81.View ArticleGoogle Scholar
- Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504.View ArticleGoogle Scholar
- Faust K, Sathirapongsasuti JF, Izard J, Segata N, Gevers D, Raes J, et al. Microbial co-occurrence relationships in the human microbiome. PLoS Comput Biol. 2012;8:e1002606.Google Scholar