Metatranscriptomic data reveal the effect of different community properties on multifunctional redundancy

New index of functional specificity to predict the redundancy of ecosystem functions in microbial communities

An ecosystem function is suggested to be more sensitive to biodiversity loss (i.e. low functional redundancy) when focusing on specific-type functions than broad-type functions. Thus far, specific-type functions have been loosely defined as functions performed by a small number of species (facilitative species) or functions involved in utilizing complex substrates. However, quantitative examination of functional specificity remains underexplored. We quantified the functional redundancy of 33 ecosystem functions in a freshwater system from 76 prokaryotic community samples over three years. For each function, we used a sparse regression model to estimate the number of facilitative Amplicon Sequence Variants (ASVs) and to define taxon-based functional specificity. We also used Bertz structural complexity to determine substrate-based functional specificity. We found that functional redundancy increased with the taxon-based functional specificity defined as the proportion of facilitative ASVs ( = facilitative ASV richness/ facilitative ASV richness + repressive ASV (ASVs reducing functioning) richness). When using substrate-based functional specificity, functional redundancy was influenced by Bertz complexity per se and by substrate acquisition mechanisms. Therefore, taxon-based functional specificity is a better predictive index for evaluating functional redundancy than substrate-based functional specificity. These findings provide a framework to quantitatively predict the consequences of diversity losses on ecosystem functioning.

Microbial Functional Diversity Correlates with Species Diversity along a Temperature Gradient

Microbial community diversity is often correlated with physical environmental stresses like acidity, salinity, and temperature. For example, species diversity usually declines with increasing temperature above 20°C. However, few studies have examined whether the genetic functional diversity of community metagenomes varies in a similar way as species diversity along stress gradients. Here, we investigated bacterial communities in thermal spring sediments ranging from 21 to 88°C, representing communities of 330 to 3,800 bacterial and archaeal species based on 16S rRNA gene amplicon analysis. Metagenomes were sequenced, and Pfam abundances were used as a proxy for metagenomic functional diversity. Significant decreases in both species diversity and Pfam diversity were observed with increasing temperatures. The relationship between Pfam diversity and species diversity followed a power function with the steepest slopes in the high-temperature, low-diversity region of the gradient. Species additions to simple thermophilic communities added many new Pfams, while species additions to complex mesophilic communities added relatively fewer new Pfams, indicating that species diversity does not approach saturation as rapidly as Pfam diversity does. Many Pfams appeared to have distinct temperature ceilings of 60 to 80°C. This study suggests that temperature stress limits both taxonomic and functional diversity of microbial communities, but in a quantitatively different manner. Lower functional diversity at higher temperatures is probably due to two factors, including (i) the absence of many enzymes not adapted to thermophilic conditions, and (ii) the fact that high-temperature communities are comprised of fewer species with smaller average genomes and, therefore, contain fewer rare functions. IMPORTANCE Only recently have microbial ecologists begun to assess quantitatively how microbial species diversity correlates with environmental factors like pH, temperature, and salinity. However, still, very few studies have examined how the number of distinct biochemical functions of microbial communities, termed functional diversity, varies with the same environmental factors. Our study examined 18 microbial communities sampled across a wide temperature gradient and found that increasing temperature reduced both species and functional diversity, but in different ways. Initially, functional diversity increased sharply with increasing species diversity but eventually plateaued, following a power function. This pattern has been previously predicted in theoretical models, but our study validates this predicted power function with field metagenomic data. This study also presents a unique overview of the distribution of metabolic functions along a temperature gradient, demonstrating that many functions have temperature "ceilings" above which they are no longer found.

Anthropogenic activities change the relationship between microbial community taxonomic composition and functional attributes

Functional redundancy is considered common in microbial systems, but recent studies have challenged this idea. The mechanism for this contradictory result is not clear. However, in this study, we hypothesize that strong environmental filtering which links to the anthropogenic activities is able to weaken microbial functional redundancy. We used metagenome and 16S rRNA gene high-throughput sequencing to investigate planktonic microbial communities in a subtropical river. We found that the weak anthropogenic activities might result in a low selection pressure in the river upstream area. Therefore, the microbial community functional attributes were stable although the community composition changed with the water temperature and NO₃ -N in upstream area (this indicates functional redundancy). However, the strong anthropogenic activities in river downstream area selected pollutant-degraded functions (e.g. nitrogen metabolism, toluene, xylenes and ethylbenzene degradation) and potentially pollutant-degraded (tolerant) microbes, and therefore caused the microbial community composition synchronously changed with the variation of community functional attributes. Our results reveal that strong environmental filtering which associates with the anthropogenic activities not only has effects on microbial community composition and community functional attributes but also on their relationships. These results provide a new insight to refine the functional redundancy idea.

Understanding response of microbial communities to saltwater intrusion through microcosms

A central pursuit of microbial ecology is to accurately describe and explain the shifts in microbial community composition and function that occur in response to environmental changes. This goal requires a thorough understanding of the individual responses of different species and of the processes guiding the assembly of microbial populations similar in their response traits and corresponding functional traits. These research topics are addressed and synthesized in this Highlights, in four studies applying a trait-based framework to assess how environmental change affected the composition and functional performance of bacterioplankton of natural origin in microcosm experiments. The salinity of many aquatic environments is currently changing, due to climate change and anthropogenic activities. The mechanisms by which salinity influences community assembly, functional redundancy and functional genes involved in nitrogen cycle, and how dispersal modifies community outcome are explored in the four studies. Together, the findings of these case studies demonstrate the feasibility of using novel experiments in combination with integrative analyses of 16S rRNA and meta-'omic' data to address ecological questions. This combined approach has the potential to elucidate both the processes contributing to bacterial community assembly and the possible links between the compositional and functional changes that occur under shifting environmental conditions.

Tax4Fun2: prediction of habitat-specific functional profiles and functional redundancy based on 16S rRNA gene sequences

BACKGROUND

Sequencing of 16S rRNA genes has become a powerful technique to study microbial communities and their responses towards changing environmental conditions in various ecosystems. Several tools have been developed for the prediction of functional profiles from 16S rRNA gene sequencing data, because numerous questions in ecosystem ecology require knowledge of community functions in addition to taxonomic composition. However, the accuracy of these tools relies on functional information derived from genomes available in public databases, which are often not representative of the microorganisms present in the studied ecosystem. In addition, there is also a lack of tools to predict functional gene redundancy in microbial communities.

RESULTS

To address these challenges, we developed Tax4Fun2, an R package for the prediction of functional profiles and functional gene redundancies of prokaryotic communities from 16S rRNA gene sequences. We demonstrate that functional profiles predicted by Tax4Fun2 are highly correlated to functional profiles derived from metagenomes of the same samples. We further show that Tax4Fun2 has higher accuracies than PICRUSt and Tax4Fun. By incorporating user-defined, habitat-specific genomic information, the accuracy and robustness of predicted functional profiles is substantially enhanced. In addition, functional gene redundancies predicted with Tax4Fun2 are highly correlated to functional gene redundancies determined for simulated microbial communities.

CONCLUSIONS

Tax4Fun2 provides researchers with a unique tool to predict and investigate functional profiles of prokaryotic communities based on 16S rRNA gene sequencing data. It is easy-to-use, platform-independent and highly memory-efficient, thus enabling researchers without extensive bioinformatics knowledge or access to high-performance clusters to predict functional profiles. Another unique feature of Tax4Fun2 is that it allows researchers to calculate the redundancy of specific functions, which is a potentially important measure of how resilient a community will be to environmental perturbation. Tax4Fun2 is implemented in R and freely available at https://github.com/bwemheu/Tax4Fun2.

The Signal and the Noise: Characteristics of Antisense RNA in Complex Microbial Communities

This study systematically evaluated the global patterns of microbial antisense expression across various environments and provides a bird’s-eye view of general patterns observed across data sets, which can provide guidelines in our understanding of antisense expression as well as interpretation of metatranscriptomic data in general. This analysis highlights that in some environments, antisense expression from microbial communities can dominate over regular gene expression. We explored some potential drivers of antisense transcription, but more importantly, this study serves as a starting point, highlighting topics for future research and providing guidelines to include antisense expression in generic bioinformatic pipelines for metatranscriptomic data.

High-throughput sequencing has allowed unprecedented insight into the composition and function of complex microbial communities. With metatranscriptomics, it is possible to interrogate the transcriptomes of multiple organisms simultaneously to get an overview of the gene expression of the entire community. Studies have successfully used metatranscriptomics to identify and describe relationships between gene expression levels and community characteristics. However, metatranscriptomic data sets contain a rich suite of additional information that is just beginning to be explored. Here, we focus on antisense expression in metatranscriptomics, discuss the different computational strategies for handling it, and highlight the strengths but also potentially detrimental effects on downstream analysis and interpretation. We also analyzed the antisense transcriptomes of multiple genomes and metagenome-assembled genomes (MAGs) from five different data sets and found high variability in the levels of antisense transcription for individual species, which were consistent across samples. Importantly, we challenged the conceptual framework that antisense transcription is primarily the product of transcriptional noise and found mixed support, suggesting that the total observed antisense RNA in complex communities arises from the combined effect of unknown biological and technical factors. Antisense transcription can be highly informative, including technical details about data quality and novel insight into the biology of complex microbial communities.

IMPORTANCE This study systematically evaluated the global patterns of microbial antisense expression across various environments and provides a bird’s-eye view of general patterns observed across data sets, which can provide guidelines in our understanding of antisense expression as well as interpretation of metatranscriptomic data in general. This analysis highlights that in some environments, antisense expression from microbial communities can dominate over regular gene expression. We explored some potential drivers of antisense transcription, but more importantly, this study serves as a starting point, highlighting topics for future research and providing guidelines to include antisense expression in generic bioinformatic pipelines for metatranscriptomic data.

AFISsys - An autonomous instrument for the preservation of brackish water samples for microbial metatranscriptome analysis

Microbial communities are the main drivers of biogeochemical cycling of multiple elements sustaining life in the ocean. The rapidity of their response to stressors and abrupt environmental changes implies that even fast and infrequent events can affect local transformations of organic matter and nutrients. Modern molecular techniques now allow for monitoring of microbial activities and functions in the environment through the analysis of genes and expressed genes contained in natural microbial assemblages. However, messenger RNA turnover in cells can be as short as 30 seconds and stability varies greatly between transcripts. Sampling of in situ communities involves an inevitable delay between the collection of seawater and the extraction of its RNA, leaving the bacterial communities plenty of time to alter their gene expression. The characteristics of microbial RNA turnover make time-series very difficult because samples need to be processed immediately to limit alterations to the metatranscriptomes. To address these challenges we designed an autonomous in situ fixation multi-sampler (AFISsys) for the reliable sampling of microbial metatranscriptomes at frequent intervals, for refined temporal resolution. To advance the development of this instrument, we examined the minimal seawater volume necessary for adequate coverage of community gene expression, and the suitability of phenol/ethanol fixation for immediate and long-term preservation of transcripts from a microbial community. We then evaluated the field eligibility of the instrument itself, with two case studies in a brackish system. AFISsys is able to collect, fix, and store water samples independently at a predefined temporal resolution. Phenol/ethanol fixation can conserve metatranscriptomes directly in the environment for up to a week, for later analysis in the laboratory. Thus, the AFISsys constitutes an invaluable tool for the integration of molecular functional analyses in environmental monitoring in brackish waters and in aquatic environments in general.