Joint Analysis of Long and Short Reads Enables Accurate Estimates of Microbiome Complexity

A microcystin synthesis mcyE/ndaF gene assay enables early detection of microcystin production in a tropical wastewater pond

Cyanobacteria can dominate the algal community in wastewater ponds, which can lead to the production of cyanotoxins and their release into the environment. We applied traditional and molecular techniques to identify cyanotoxin hazards and high-risk periods in a tropical wastewater treatment system. Potentially toxic cyanobacteria were identified by microscopy and amplicon sequencing over the course of a year. Toxin gene levels were monitored and compared to toxin production to identify likely toxin producing species and high-risk periods. Cyanobacteria were persistent in the effluent year-round, with Planktothrix and Microcystis the most abundant genera; Microcystis could not be resolved beyond genus using amplicon sequencing, but M. flos-aquae was identified as a dominant species by microscopy. Microcystin toxin was detected for the first time in treated effluent at the beginning of the wet season (December 2018), which correlated with an increase in Microcystis amplicon sequence abundance and elevated microcystin toxin gene (mcyE/ndaF) levels. Concomitantly, microscopy data showed an increase in M. flos-aquae but not M. aeruginosa. These data informed a refined sampling campaign in 2019 and results showed a strong correlation between mcyE/ndaF gene abundance, microcystin toxin levels and Microcystis amplicon sequence abundance. Microscopy data showed that in addition to M. flos-aquae, M. aeruginosa was also abundant in February and March 2019, with highest levels coinciding with toxin detection and toxin gene levels. M. aeruginosa was the most abundant Microcystis species detected in selected treated effluent samples by metagenomics analysis, and elevated levels coincided with toxin production. All microcystin genes in the biosynthesis pathway were detected, but microcystin genes from Planktothrix agardhii were not detected. Gene toxin assays were successfully used to predict microcystin production in this wastewater system. Changes in amplicon sequence relative abundance were a useful indicator of changes in the cyanobacterial community. We found that metagenomics was useful not just for identifying the most abundant Microcystis species, but the detection of microcystin biosynthesis genes helped confirm this genus as the most likely toxin producer in this system. We recommend toxin gene testing for the early detection of potential toxin producing cyanobacteria to manage the risk of toxicity and allow the implementation of risk management strategies.

Those Nematode-Trapping Fungi That are not Everywhere: Hints Towards Soil Microbial Biogeography

The existence of biogeography for microorganisms is a raising topic in ecology and researchers are employing better distinctions between single species, including the most rare ones, to reveal potential hidden patterns. An important volume of evidence supporting heterogeneous distributions for bacteria, archaea and protists is accumulating, and more recently a few efforts have targeted microscopic fungi. We propose an insight into this latter kingdom by looking at a group of soil nematode-trapping fungi whose species are well-known and easily recognizable. We chose a pure culture approach because of its reliable isolation procedures for this specific group. After morphologically and molecularly identifying all species collected from 2250 samples distributed in 228 locations across Yunnan province of China, we analyzed occurrence frequencies and mapped species, genera, and richness. Results showed an apparent cosmopolitan tendency for this group of fungi, including species richness among sites. However, only four species were widespread across the region, while non-random heterogeneous distributions were observed for the remaining 40 species, both in terms of statistical distribution of species richness reflected by a significant variance-to-mean ratio, as well as in terms of visually discernible spatial clusters of rare species and genera on the map. Moreover, several species were restricted to only one location, raising the question of whether endemicity exists for this microbial group. Finally, environmental heterogeneity showed a marginal contribution in explaining restricted distributions, suggesting that other factors such as geographical isolation and dispersal capabilities should be explored. These findings contribute to our understanding of the cryptic geographic distribution of microorganisms and encourage further research in this direction.

Seasonal microbial dynamics in the ocean inferred from assembled and unassembled data: a view on the unknown biosphere

In environmental metagenomic experiments, a very high proportion of the microbial sequencing data (> 70%) remains largely unexploited because rare and closely related genomes are missed in short-read assemblies. The identity and the potential metabolisms of a large fraction of natural microbial communities thus remain inaccessible to researchers. The purpose of this study was to explore the genomic content of unassembled metagenomic data and test their level of novelty. We used data from a three-year microbial metagenomic time series of the NW Mediterranean Sea, and conducted reference-free and database-guided analysis. The results revealed a significant genomic difference between the assembled and unassembled reads. The unassembled reads had a lower mean identity against public databases, and fewer metabolic pathways could be reconstructed. In addition, the unassembled fraction presented a clear temporal pattern, unlike the assembled ones, and a specific community composition that was similar to the rare communities defined by metabarcoding using the 16S rRNA gene. The rare gene pool was characterised by keystone bacterial taxa, and the presence of viruses, suggesting that viral lysis could maintain some taxa in a state of rarity. Our study demonstrates that unassembled metagenomic data can provide important information on the structure and functioning of microbial communities.

Separation of Donor and Recipient Microbial Diversity Allows Determination of Taxonomic and Functional Features of Gut Microbiota Restructuring following Fecal Transplantation

Fecal microbiota transplantation (FMT) is currently used in medicine to treat recurrent clostridial colitis and other intestinal diseases. However, neither the therapeutic mechanism of FMT nor the mechanism that allows the donor bacteria to colonize the intestine of the recipient has yet been clearly described. From a biological point of view, FMT can be considered a useful model for studying the ecology of host-associated microbial communities. FMT experiments can shed light on the relationship features between the host and its gut microbiota. This creates the need for experimentation with approaches to metagenomic data analysis which may be useful for the interpretation of observed biological phenomena. Here, the recipient intestine colonization analysis tool (RECAST) novel computational approach is presented, which is based on the metagenomic read sorting process per their origin in the recipient’s post-FMT stool metagenome. Using the RECAST algorithm, taxonomic/functional annotation, and machine learning approaches, the metagenomes from three FMT studies, including healthy volunteers, patients with clostridial colitis, and patients with metabolic syndrome, were analyzed. Using our computational pipeline, the donor-derived and recipient-derived microbes which formed the recipient post-FMT stool metagenomes (successful microbes) were identified. Their presence is well explained by a higher relative abundance in donor/pre-FMT recipient metagenomes or other metagenomes from the human population. In addition, successful microbes are enriched with gene groups potentially related to antibiotic resistance, including antimicrobial peptides. Interestingly, the observed reorganization features are universal and independent of the disease.

IMPORTANCE We assumed that the enrichment of successful gut microbes by lantibiotic/antibiotic resistance genes can be related to gut microbiota colonization resistance by third-party microbe phenomena and resistance to bacterium-derived or host-derived antimicrobial substances. According to this assumption, competition between the donor-derived and recipient-derived microbes as well as host immunity may play a key role in the FMT-related colonization and redistribution of recipient gut microbiota structure.

Author Video: An author video summary of this article is available.

Computational methods for chromosome-scale haplotype reconstruction

High-quality chromosome-scale haplotype sequences of diploid genomes, polyploid genomes, and metagenomes provide important insights into genetic variation associated with disease and biodiversity. However, whole-genome short read sequencing does not yield haplotype information spanning whole chromosomes directly. Computational assembly of shorter haplotype fragments is required for haplotype reconstruction, which can be challenging owing to limited fragment lengths and high haplotype and repeat variability across genomes. Recent advancements in long-read and chromosome-scale sequencing technologies, alongside computational innovations, are improving the reconstruction of haplotypes at the level of whole chromosomes. Here, we review recent and discuss methodological progress and perspectives in these areas.

Soil Bacterial Communities Exhibit Strong Biogeographic Patterns at Fine Taxonomic Resolution

Bacteria have been inferred to exhibit relatively weak biogeographic patterns. To what extent such findings reflect true biological phenomena or methodological artifacts remains unclear. Here, we addressed this question by analyzing the turnover of soil bacterial communities from three data sets. We applied three methodological innovations: (i) design of a hierarchical sampling scheme to disentangle environmental from spatial factors driving turnover; (ii) resolution of 16S rRNA gene amplicon sequence variants to enable higher-resolution community profiling; and (iii) application of the new metric zeta diversity to analyze multisite turnover and drivers. At fine taxonomic resolution, rapid compositional turnover was observed across multiple spatial scales. Turnover was overwhelmingly driven by deterministic processes and influenced by the rare biosphere. The communities also exhibited strong distance decay patterns and taxon-area relationships, with z values within the interquartile range reported for macroorganisms. These biogeographical patterns were weakened upon applying two standard approaches to process community sequencing data: clustering sequences at 97% identity threshold and/or filtering the rare biosphere (sequences lower than 0.05% relative abundance). Comparable findings were made across local, regional, and global data sets and when using shotgun metagenomic markers. Altogether, these findings suggest that bacteria exhibit strong biogeographic patterns, but these signals can be obscured by methodological limitations. We advocate various innovations, including using zeta diversity, to advance the study of microbial biogeography.IMPORTANCE It is commonly thought that bacterial distributions show lower spatial variation than for multicellular organisms. In this article, we present evidence that these inferences are artifacts caused by methodological limitations. Through leveraging innovations in sampling design, sequence processing, and diversity analysis, we provide multifaceted evidence that bacterial communities in fact exhibit strong distribution patterns. This is driven by selection due to factors such as local soil characteristics. Altogether, these findings suggest that the processes underpinning diversity patterns are more unified across all domains of life than previously thought, which has broad implications for the understanding and management of soil biodiversity.

cloudSPAdes: assembly of synthetic long reads using de Bruijn graphs

Motivation

The recently developed barcoding-based synthetic long read (SLR) technologies have already found many applications in genome assembly and analysis. However, although some new barcoding protocols are emerging and the range of SLR applications is being expanded, the existing SLR assemblers are optimized for a narrow range of parameters and are not easily extendable to new barcoding technologies and new applications such as metagenomics or hybrid assembly.

Results

We describe the algorithmic challenge of the SLR assembly and present a cloudSPAdes algorithm for SLR assembly that is based on analyzing the de Bruijn graph of SLRs. We benchmarked cloudSPAdes across various barcoding technologies/applications and demonstrated that it improves on the state-of-the-art SLR assemblers in accuracy and speed.

Availability and implementation

Source code and installation manual for cloudSPAdes are available at https://github.com/ablab/spades/releases/tag/cloudspades-paper.

Supplementary Information

Supplementary data are available at Bioinformatics online.

Estimating the total genome length of a metagenomic sample using k-mers

Background

Metagenomic sequencing is a powerful technology for studying the mixture of microbes or the microbiomes on human and in the environment. One basic task of analyzing metagenomic data is to identify the component genomes in the community. This task is challenging due to the complexity of microbiome composition, limited availability of known reference genomes, and usually insufficient sequencing coverage.

Results

As an initial step toward understanding the complete composition of a metagenomic sample, we studied the problem of estimating the total length of all distinct component genomes in a metagenomic sample. We showed that this problem can be solved by estimating the total number of distinct k-mers in all the metagenomic sequencing data. We proposed a method for this estimation based on the sequencing coverage distribution of observed k-mers, and introduced a k-mer redundancy index (KRI) to fill in the gap between the count of distinct k-mers and the total genome length. We showed the effectiveness of the proposed method on a set of carefully designed simulation data corresponding to multiple situations of true metagenomic data. Results on real data indicate that the uncaptured genomic information can vary dramatically across metagenomic samples, with the potential to mislead downstream analyses.

Conclusions

We proposed the question of how long the total genome length of all different species in a microbial community is and introduced a method to answer it.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5467-x) contains supplementary material, which is available to authorized users.