Prospects for Integrating Disturbances, Biodiversity and Ecosystem Functioning Using Microbial Systems

Biodiversity is a key driver of ecosystem functioning, while disturbances are a key driver of biodiversity. Consequently, disturbances crucially influence ecosystem functioning– both directly via affecting ecosystem processes but also indirectly via altering biodiversity. We thus need to disclose the joint relationships between disturbances, biodiversity and functioning (DBF) to understand and predict ecosystem dynamics under realistic conditions. However, biodiversity responses to disturbances have so far insufficiently been studied together with biodiversity effects on functions. For many ecosystems, such integrative exploration of DBF relationships would require too extensive manipulations and observations over unfeasible spatial and temporal scales. We argue that microbial systems offer a bright perspective to overcome these limitations, and present a roadmap for doing so. Microbial systems allow us exposing different, well characterized communities to multiple, reproducible disturbance regimes, and precisely measuring both biodiversity and associated functions over time. Comprehensive data can be obtained by systematically varying and replicating representative environmental scenarios. These data can further be explored and explained with computational models. Microbial systems thus reveal mechanisms that underlie DBF relationships and allow scrutinizing ecological hypotheses. This advancement of theory will be essential for ecology as a whole. It is particularly relevant in the context of global change, which is expected to promote disturbances as well as loss of biodiversity and functions in many ecosystem

Cultivation-independent analysis reveals a shift in ciliate 18S rRNA gene diversity in a polycyclic aromatic hydrocarbon-polluted soil

Using cultivation-independent methods the ciliate communities of a clay-rich soil with a 90-year record of pollution by polycyclic aromatic hydrocarbons (PAH) (4.5 g kg−1 PAH) were compared with that of a nonpolluted soil collected in its vicinity and with similar properties. A ciliate-specific set of 18S rRNA gene targeting primers was designed and used to amplify DNA extracted from both soils (surface and 20 cm depth). Four clone libraries were generated with PCR products that covered an 18S rRNA gene fragment of up to 670 bp. Comparative sequence analysis of representative clones proved that the primer set was highly specific for ciliates. Calculation of similarity indices based on operational taxonomic units after amplified ribosomal DNA restriction analysis of the clones showed that the community from the nonpolluted surface soil was highly dissimilar to the other communities. The presence of several taxa, namely sequences affiliated to the orders Phyllopharyngia, Haptoria, Nassophorea, Peniculida and Scuticociliatia in samples from nonpolluted soil, points to the existence of various trophic functional groups. In contrast, the 18S rRNA gene diversity was much lower in the clone libraries from the polluted soil. More than 90% of these sequences belonged to the class Colpodea, a well-known clade of mainly bacterivorous and r-selected species, thus potentially also indicating a lower functional diversit

Complete Genome Sequence of Alteromonas Virus vB_AspP-H4/4

Alteromonas virus vB_AspP-H4/4 is a member of the Podoviridae family and was isolated from North Sea water in the 1970s. The complete double-stranded DNA genome has 47,631 bp with 49 predicted genes

Impacts of heavy metal contamination and phytoremediation on a microbial community during a twelve-month microcosm experiment

The effects of heavy metals and phytoextraction practices on a soil microbial community were studied during 12 months using a hyperaccumulating plant (Thlaspi caerulescens) grown in an artificially contaminated soil. The 16S ribosomal RNA genes of the Bacteria and the β-Proteobacteria and the amoA gene (encoding the α-subunit of ammonia monooxygenase) were PCR-amplified and analysed by denaturing gradient gel electrophoresis (DGGE). Principal component analysis (PCA) of the DGGE data revealed that: (i) the heavy metals had the most drastic effects on the bacterial groups targeted, (ii) the plant induced changes which could be observed in the amoA and in the Bacteria 16S rRNA gene patterns, (iii) the changes observed during 12 months in the DGGE-patterns of the planted contaminated soil did not indicate recovery of the initial bacterial community present in the non-contaminated soil. The potential function of the microbial community was assessed recording community level physiological profiles (CLPP) and analysing them by PCA. The lower capability of the bacterial community to degrade the substrates provided in the BIOLOG plates, in particular the amino acids, amides and amines, as well as a delay in the average well colour development (AWCD) differentiated the bacterial community of the contaminated samples from that of the non-contaminated ones. However, the plant had a positive effect on substrate utilization as shown by the greater number of substrates used in all planted samples compared to unplanted ones. Finally, the measurement of the potential ammonia oxidation indicated that ammonia oxidising bacteria were completely inhibited in the contaminated soil. The stimulation of ammonia oxidation by the plant observed in the non-contaminated samples was surpassed by the inhibitory effect of the heavy metals in the contaminated soil. This study emphasises the combined use of culture-independent techniques with conventional methods to investigate the ecology of bacteria in their natural habitat

Tracing toluene-assimilating sulfate-reducing bacteria using 13C-incorporation in fatty acids and whole-cell hybridization

Polar lipid-derived fatty acids (PLFA) commonly found in sulfate-reducing bacteria were detected in high abundance in the sediment harvested from a monitoring well of a petroleum-hydrocarbon (PHC)-contaminated aquifer. Aquifer microcosms were incubated under sulfate-reducing conditions with [methyl-14C]toluene to determine the 14C-mass balances and with [methyl-13C]toluene to follow the flow of carbon from toluene into biomarker fatty acids. An aliquot was used to establish an aquifer-derived toluene-degrading sulfate-reducing consortium, which grew well in liquid medium. Whole-cell hybridization using 16S rRNA-targeted oligonucleotide probes specific for different phylogenetic levels within the sulfate-reducing bacteria was applied in order to characterize the sulfate-reducing populations in the original sediment, the aquifer microcosms, and the aquifer-derived consortium. In the aquifer microcosms, the 14C quantification revealed that 61.6% of the [methyl-14C]toluene was mineralized and 2.7% was assimilated. Following [methyl-13C]toluene depletion (<1 μM), the highest 13C-enrichment was found in PLFA 16:1ω5c. In addition, biomarker fatty acids characteristic for the genera Desulfobacter and Desulfobacula (cy17:0 and 10Me16:0) were also 13C-enriched, contrary to those of other sulfate-reducing genera, e.g. Desulfovibrio and Synthrophobacter (i17:1ω7c), Desulfobulbus and Desulforhabdus (15:1ω6c and 17:1ω6c). Although hybridization detection rates remained low, indicating low bacterial activities, 43% (aquifer sediment) and 30% (aquifer microcosm) of the total active bacteria belonged to the Desulfobacteriaceae thus supporting the PLFA-based results. Desulfobacter-species (42%), which belong to the Desulfobacteriaceae, dominated the community of the consortium. Our study showed that carbon stable isotope analysis in combination with whole-cell hybridization could link toluene degradation in aquifer microcosms to the metabolic activity of the Desulfobacter-like populations. These populations could play an important role in the clean up of aromatic PHC-contaminated aquifer

Mining Synergistic Microbial Interactions: A Roadmap on How to Integrate Multi-Omics Data

Mining interspecies interactions remain a challenge due to the complex nature of microbial communities and the need for computational power to handle big data. Our meta-analysis indicates that genetic potential alone does not resolve all issues involving mining of microbial interactions. Nevertheless, it can be used as the starting point to infer synergistic interspecies interactions and to limit the search space (i.e., number of species and metabolic reactions) to a manageable size. A reduced search space decreases the number of additional experiments necessary to validate the inferred putative interactions. As validation experiments, we examine how multi-omics and state of the art imaging techniques may further improve our understanding of species interactions’ role in ecosystem processes. Finally, we analyze pros and cons from the current methods to infer microbial interactions from genetic potential and propose a new theoretical framework based on: (i) genomic information of key members of a community; (ii) information of ecosystem processes involved with a specific hypothesis or research question; (iii) the ability to identify putative species’ contributions to ecosystem processes of interest; and, (iv) validation of putative microbial interactions through integration of other data sources

Where less may be more: how the rare biosphere pulls ecosystems strings

Rare species are increasingly recognized as crucial, yet vulnerable components of Earth’s ecosystems. This is also true for microbial communities, which are typically composed of a high number of relatively rare species. Recent studies have demonstrated that rare species can have an over-proportional role in biogeochemical cycles and may be a hidden driver of microbiome function. In this review, we provide an ecological overview of the rare microbial biosphere, including causes of rarity and the impacts of rare species on ecosystem functioning. We discuss how rare species can have a preponderant role for local biodiversity and species turnover with rarity potentially bound to phylogenetically conserved features. Rare microbes may therefore be overlooked keystone species regulating the functioning of host-associated, terrestrial and aquatic environments. We conclude this review with recommendations to guide scientists interested in investigating this rapidly emerging research area

OrtSuite: from genomes to prediction of microbial interactions within targeted ecosystem processes

Published Online: 27 September, 2021The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96% of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. We evaluated the identification of putative synergistic species interactions using the sequenced genomes of an independent study that had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy-to-use workflow that allows for rapid functional annotation based on a user-curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known.This work was funded by the Helmholtz Young Investigator grant VH-NG-1248 Micro “Big Data.”info:eu-repo/semantics/publishedVersio

Molecular quantification and differentiation of Candida species in biological specimens of patients with liver cirrhosis

Patients with liver cirrhosis are susceptible to fungal infections. Due to low sensitivity of culture-based methods, we applied a real-time PCR assay targeting the 18S rRNA gene in combination with direct sequencing and terminal-restriction fragment length polymorphism (T-RFLP) in order to establish a novel tool to detect fungal DNA and to quantify and differentiate Candida DNA, also in polyfungal specimens. In total, 281 samples (blood n=135, ascites n=92, duodenal fluid n=54) from 135 patients with liver cirrhosis and 52 samples (blood n=26, duodenal fluid n=26) from 26 control patients were collected prospectively. Candida DNA was quantified in all samples. Standard microbiological culture was performed for comparison. Blood and ascites samples, irrespective of the patient cohort, showed a method-independent low fungal detection rate of approximately 1%, and the Candida DNA content level did not exceed 3.0x101 copies ml-1 in any sample. In contrast, in duodenal fluid of patients with liver cirrhosis high fungal detection rates were discovered by using both PCR- and culture-based techniques (81.5% vs. 66.7%; p=0.123) and the median level of Candida DNA was 3.8x105 copies ml-1 (2.3x102-6.3x109). In cirrhosis and controls, fungal positive culture results were confirmed by PCR in 96% and an additional amount of 44% of culture negative duodenal samples were PCR positive. Using T-RFLP analysis in duodenal samples, overall 85% of results from microbial culture were confirmed and in 75% of culture-negative but PCR-positive samples additional Candida species could be identified. In conclusion, PCR-based methods and subsequent differentiation of Candida DNA might offer a quick approach to identifying Candida species without prior cultivation