Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes

Eukfinder: a pipeline to retrieve microbial eukaryote genome sequences from metagenomic data

Whole-genome shotgun (WGS) metagenomic sequencing of microbial communities enables the discovery of the functions, physiologies, and evolutionary histories of prokaryotic and eukaryotic microbes. However, metagenomic studies of microbial eukaryotes lag due to challenges in identifying and assembling high-quality genomes from WGS data. To address this problem, we developed Eukfinder, a bioinformatics pipeline that identifies potential eukaryotic sequences from WGS metagenomic data, with a complementary binning workflow for recovering nuclear and mitochondrial genomes. Eukfinder uses two specialized databases for read/contig classification, customizable to specific data sets or environments. We tested Eukfinder on simulated gut microbiome data sets which included varying numbers of reads from the protist Blastocystis, a human gut commensal. We also applied Eukfinder to previously published human gut microbiome WGS metagenomic data to recover new genomes of Blastocystis. Compared to other workflows, Eukfinder offers the potential to recover high-quality, near-complete genomes of diverse eukaryotes, including different Blastocystis subtypes, without relying on a reference genome. With sufficient sequencing depth, Eukfinder outperforms similar tools for recovering eukaryotic genomes from metagenomic data. Eukfinder is a valuable tool for reference-independent and cultivation-free studies of eukaryotic microbial genomes from environmental WGS metagenomic samples.

IMPORTANCE

Advancements in next-generation sequencing have made whole-genome shotgun (WGS) metagenomic sequencing an efficient method for de novo reconstruction of microbial genomes from various environments. Thousands of new prokaryotic genomes have been characterized; however, the large size and complexity of protistan genomes have hindered the use of WGS metagenomics to sample microbial eukaryotic diversity. Eukfinder enables the recovery of eukaryotic microbial genomes from environmental WGS metagenomic samples. Retrieval of high-quality protistan genomes from diverse metagenomic samples increases the number of reference genomes available. This aids future metagenomic investigations into the functions, physiologies, and evolutionary histories of eukaryotic microbes in the gut microbiome and other ecosystems.

A new mesophilic member of the Chloroflexota phylum 'Ca. Сhloroploca septentrionalis' from the meromictic lake Bol'shie Khruslomeny separated from the White Sea

A new filamentous phototrophic bacterium Khr17 was isolated as an enrichment culture from the brackish polar lake Bol'shie Khruslomeny. The organism was a halotolerant, strictly anaerobic phototroph possessing photosystem II. Sulfide was required for phototrophic growth. The cells of bacterium Khr17 formed nonmotile, wavy trichomes surrounded by a sheath. The cells contained chlorosomes, gas vesicles, and storage granules. The antenna pigments of bacterium Khr17 were bacteriochlorophyll c and β- and γ-carotenes. The genome of Khr17 bacterium carries all the genes responsible for CO2 fixation via the 3-hydroxypropionate pathway. The genes encoding the proteins of the nitrogenase complex were not found. The DNA G + C content was 59.9%. The 16S rRNA gene sequence of isolate Khr17 exhibited 99.4% similarity to related species. The average nucleotide identity and digital DNA-DNA hybridization values for the isolate showed 91.9% and 46.9% similarity, respectively, to other 'Ca. Chloroploca' species. Based on its phenotypic and phylogenetic characteristics, classification of Khr17 as member of a new species, 'Ca. Chloroploca septentrionalis' sp. nov., was proposed. Members of the genus 'Ca. Chloroploca' have previously not been found in Arctic areas and in the plankton of meromictic lakes.

Visualizing metagenomic and metatranscriptomic data: A comprehensive review

The fields of Metagenomics and Metatranscriptomics involve the examination of complete nucleotide sequences, gene identification, and analysis of potential biological functions within diverse organisms or environmental samples. Despite the vast opportunities for discovery in metagenomics, the sheer volume and complexity of sequence data often present challenges in processing analysis and visualization. This article highlights the critical role of advanced visualization tools in enabling effective exploration, querying, and analysis of these complex datasets. Emphasizing the importance of accessibility, the article categorizes various visualizers based on their intended applications and highlights their utility in empowering bioinformaticians and non-bioinformaticians to interpret and derive insights from meta-omics data effectively.

Unveiling the role of emerging metagenomics for the examination of hypersaline environments

Hypersaline ecosystems are distributed all over the globe. They are subjected to poly-extreme stresses and are inhabited by halophilic microorganisms possessing multiple adaptations. The halophiles have many biotechnological applications such as nutrient supplements, antioxidant synthesis, salt tolerant enzyme production, osmolyte synthesis, biofuel production, electricity generation etc. However, halophiles are still underexplored in terms of complex ecological interactions and functions as compared to other niches. The advent of metagenomics and the recent advancement of next-generation sequencing tools have made it feasible to investigate the microflora of an ecosystem, its interactions and functions. Both target gene and shotgun metagenomic approaches are commonly employed for the taxonomic, phylogenetic, and functional analyses of the hypersaline microbial communities. This review discusses different types of hypersaline niches, their residential microflora, and an overview of the metagenomic approaches used to investigate them. Various applications, hurdles and the recent advancements in metagenomic approaches have also been focused on here for their better understanding and utilization in the study of hypersaline microbiome.

Molecular diversity of green-colored microbial mats from hot springs of northern Japan

We acquired and analyzed metagenome and 16S/18S rRNA gene amplicon data of green-colored microbial mats from two hot springs within the Onikobe geothermal region (Miyagi Prefecture, Japan). The two collection sites-Tamago and Warabi-were in proximity and had the same temperature (40 °C), but the Tamago site was connected to a nearby stream, whereas the Warabi site was isolated. Both the amplicon and metagenome data suggest the bacterial, especially cyanobacterial, dominance of the mats; other abundant groups include Chloroflexota, Pseudomonadota, Bacteroidota/Chlorobiota, and Deinococcota. At finer resolution, however, the taxonomic composition entirely differed between the mats. A total of 5 and 21 abundant bacterial 16S rRNA gene OTUs were identified for Tamago and Warabi, respectively; of these, 12 are putative chlorophyll- or rhodopsin-based phototrophs. The presence of phylogenetically diverse microbial eukaryotes was noted, with ciliates and amoebozoans being the most abundant eukaryote groups for Tamago and Warabi, respectively. Fifteen metagenome-assembled genomes (MAGs) were obtained, represented by 13 bacteria, one ciliate (mitochondrion), and one giant virus. A total of 15 novel taxa, including a new deeply branching Chlorobiota species, is noted from the amplicon and MAG data, highlighting the importance of environmental sequencing in uncovering hidden microorganisms.

Metagenome-assembled microbial genomes from Parkinson's disease fecal samples

The human gut microbiome composition has been linked to Parkinson's disease (PD). However, knowledge of the gut microbiota on the genome level is still limited. Here we performed deep metagenomic sequencing and binning to build metagenome-assembled genomes (MAGs) from 136 human fecal microbiomes (68 PD samples and 68 control samples). We constructed 952 non-redundant high-quality MAGs and compared them between PD and control groups. Among these MAGs, there were 22 different genomes of Collinsella and Prevotella, indicating high variability of those genera in the human gut environment. Microdiversity analysis indicated that Ruminococcus bromii was statistically significantly (p < 0.002) more diverse on the strain level in the control samples compared to the PD samples. In addition, by clustering all genes and performing presence-absence analysis between groups, we identified several control-specific (p < 0.05) related genes, such as speF and Fe-S oxidoreductase. We also report detailed annotation of MAGs, including Clusters of Orthologous Genes (COG), Cas operon type, antiviral gene, prophage, and secondary metabolites biosynthetic gene clusters, which can be useful for providing a reference for future studies.

Solving genomic puzzles: computational methods for metagenomic binning

Metagenomics involves the study of genetic material obtained directly from communities of microorganisms living in natural environments. The field of metagenomics has provided valuable insights into the structure, diversity and ecology of microbial communities. Once an environmental sample is sequenced and processed, metagenomic binning clusters the sequences into bins representing different taxonomic groups such as species, genera, or higher levels. Several computational tools have been developed to automate the process of metagenomic binning. These tools have enabled the recovery of novel draft genomes of microorganisms allowing us to study their behaviors and functions within microbial communities. This review classifies and analyzes different approaches of metagenomic binning and different refinement, visualization, and evaluation techniques used by these methods. Furthermore, the review highlights the current challenges and areas of improvement present within the field of research.

AFITbin: a metagenomic contig binning method using aggregate l-mer frequency based on initial and terminal nucleotides

BACKGROUND

Using next-generation sequencing technologies, scientists can sequence complex microbial communities directly from the environment. Significant insights into the structure, diversity, and ecology of microbial communities have resulted from the study of metagenomics. The assembly of reads into longer contigs, which are then binned into groups of contigs that correspond to different species in the metagenomic sample, is a crucial step in the analysis of metagenomics. It is necessary to organize these contigs into operational taxonomic units (OTUs) for further taxonomic profiling and functional analysis. For binning, which is synonymous with the clustering of OTUs, the tetra-nucleotide frequency (TNF) is typically utilized as a compositional feature for each OTU.

RESULTS

In this paper, we present AFIT, a new l-mer statistic vector for each contig, and AFITBin, a novel method for metagenomic binning based on AFIT and a matrix factorization method. To evaluate the performance of the AFIT vector, the t-SNE algorithm is used to compare species clustering based on AFIT and TNF information. In addition, the efficacy of AFITBin is demonstrated on both simulated and real datasets in comparison to state-of-the-art binning methods such as MetaBAT 2, MaxBin 2.0, CONCOT, MetaCon, SolidBin, BusyBee Web, and MetaBinner. To further analyze the performance of the purposed AFIT vector, we compare the barcodes of the AFIT vector and the TNF vector.

CONCLUSION

The results demonstrate that AFITBin shows superior performance in taxonomic identification compared to existing methods, leveraging the AFIT vector for improved results in metagenomic binning. This approach holds promise for advancing the analysis of metagenomic data, providing more reliable insights into microbial community composition and function.

AVAILABILITY

A python package is available at: https://github.com/SayehSobhani/AFITBin .

New avenues for potentially seeking microbial responses to climate change beneath Antarctic ice shelves

The signs of climate change are undeniable, and the impact of these changes on ecosystem function heavily depends on the response of microbes that underpin the food web. Antarctic ice shelf is a massive mass of floating ice that extends from the continent into the ocean, exerting a profound influence on global carbon cycles. Beneath Antarctic ice shelves, marine ice stores valuable genetic information, where marine microbial communities before the industrial revolution are archived. Here, in this proof-of-concept, by employing a combination of single-cell technologiesand metagenomics, we have been able to sequence frozen microbial DNA (≈300 years old) stored in the marine ice core B15 collected from the Filchnner-Ronne Ice Shelf. Metagenomic data indicated that Proteobacteria and Thaumarchaeota (e.g., Nitrosopumilus spp.), followed by Actinobacteria (e.g., Actinomarinales), were abundant. Remarkably, our data allow us to "travel to the past" and calibrate genomic and genetic evolutionary changes for ecologically relevant microbes and functions, such as Nitrosopumilus spp., preserved in the marine ice (≈300 years old) with those collected recently in seawater under an ice shelf (year 2017). The evolutionary divergence for the ammonia monooxygenase gene amoA involved in chemolithoautotrophy was about 0.88 amino acid and 2.8 nucleotide substitution rate per 100 sites in a century, while the accumulated rate of genomic SNPs was 2,467 per 1 Mb of genome and 100 years. Whether these evolutionary changes remained constant over the last 300 years or accelerated during post-industrial periods remains an open question that will be further elucidated.

IMPORTANCE

Several efforts have been undertaken to predict the response of microbes under climate change, mainly based on short-term microcosm experiments under forced conditions. A common concern is that manipulative experiments cannot properly simulate the response of microbes to climate change, which is a long-term evolutionary process. In this proof-of-concept study with a limited sample size, we demonstrate a novel approach yet to be fully explored in science for accessing genetic information from putative past marine microbes preserved under Antarctic ice shelves before the industrial revolution. This potentially allows us estimating evolutionary changes as exemplified in our study. We advocate for gathering a more comprehensive Antarctic marine ice core data sets across various periods and sites. Such a data set would enable the establishment of a robust baseline, facilitating a better assessment of the potential effects of climate change on key genetic signatures of microbes.

Transcriptomic insights into the dominance of two phototrophs throughout the water column of a tropical hypersaline-alkaline crater lake (Dziani Dzaha, Mayotte)

Saline-alkaline lakes often shelter high biomasses despite challenging conditions, owing to the occurrence of highly adapted phototrophs. Dziani Dzaha (Mayotte) is one such lake characterized by the stable co-dominance of the cyanobacterium Limnospira platensis and the picoeukaryote Picocystis salinarum throughout its water column. Despite light penetrating only into the uppermost meter, the prevailing co-dominance of these species persists even in light- and oxygen-deprived zones. Here, a depth profile of phototrophs metatranscriptomes, annotated using genomic data from isolated strains, is employed to identify expression patterns of genes related to carbon processing pathways including photosynthesis, transporters and fermentation. The findings indicate a prominence of gene expression associated with photosynthesis, with a peak of expression around 1 m below the surface, although the light intensity is very low and only red and dark red wavelengths can reach it, given the very high turbidity linked to the high biomass of L. platensis. Experiments on strains confirmed that both species do grow under these wavelengths, at rates comparable to those obtained under white light. A decrease in the expression of photosynthesis-related genes was observed in L. platensis with increasing depth, whereas P. salinarum maintained a very high pool of psbA transcripts down to the deepest point as a possible adaptation against photodamage, in the absence and/or very low levels of expression of genes involved in protection. In the aphotic/anoxic zone, expression of genes involved in fermentation pathways suggests active metabolism of reserve or available dissolved carbon compounds. Overall, L. platensis seems to be adapted to the uppermost water layer, where it is probably maintained thanks to gas vesicles, as evidenced by high expression of the gvpA gene. In contrast, P. salinarum occurs at similar densities throughout the water column, with a peak in abundance and gene expression levels which suggests a better adaptation to lower light intensities. These slight differences may contribute to limited inter-specific competition, favoring stable co-dominance of these two phototrophs.

Microbiological insights into anaerobic phenol degradation mechanisms and bulking phenomenon in a mesophilic upflow anaerobic sludge blanket reactor in long-term operation

In this study, a long-term operation of 2,747 days was conducted to evaluate the performance of the upflow anaerobic sludge blanket (UASB) reactor and investigated the degradation mechanisms of high-organic loading phenol wastewater. During the reactor operation, the maximum chemical oxygen demand (COD) removal rate of 6.1 ± 0.6 kg/m3/day under 1,680 mg/L phenol concentration was achieved in the mesophilic UASB reactor. After a significant change in the operating temperature from 24.0 ± 4.1 °C to 35.9 ± 0.6 °C, frequent observations of floating and washout of the bloated granular sludge (novel types of the bulking phenomenon) were made in the UASB reactor, suggesting that the change in operating temperature could be a trigger for the bulking phenomenon. Through the metagenomic analysis, phenol degradation mechanisms were predicted that phenol was converted to 4-hydroxybenzoate via two possible routes by Syntrophorhabdaceae and Pelotomaculaceae bacteria. Furthermore, the degradation of 4-hydroxybenzoate to benzoyl-CoA was carried out by members of Syntrophorhabdaceae and Smithellaceae. In the bulking sludge, a predominant presence of Nanobdellota, belonging to DPANN archaea, was detected. The metagenome-assembled genome of the Nanobdellota lacks many biosynthetic pathways and has several genes for the symbiotic lifestyle such as trimeric autotransporter adhesin-related protein. Furthermore, the Nanobdellota have significant correlations with several methanogenic archaea that are predominantly present in the UASB reactor. Considering the results of this study, the predominant Nanobdellota may negatively affect the growth of the methanogens through the parasitic lifestyle and change the balance of microbial interactions in the granular sludge ecosystem.

Facultative endosymbiosis between cellulolytic protists and methanogenic archaea in the gut of the Formosan termite Coptotermes formosanus

Anaerobic protists frequently harbour methanogenic archaea, which apparently contribute to the hosts' fermentative metabolism by consuming excess H2. However, the ecological properties of endosymbiotic methanogens remain elusive in many cases. Here we investigated the ecology and genome of the endosymbiotic methanogen of the Cononympha protists in the hindgut of the termite Coptotermes formosanus. Microscopic and 16S rRNA amplicon sequencing analyses revealed that a single species, designated here "Candidatus Methanobrevibacter cononymphae", is associated with both Cononympha leidyi and Cononympha koidzumii and that its infection rate in Cononympha cells varied from 0.0% to 99.8% among termite colonies. Fine-scale network analysis indicated that multiple 16S rRNA sequence variants coexisted within a single host cell and that identical variants were present in both Cononympha species and also on the gut wall. Thus, "Ca. Methanobrevibacter cononymphae" is a facultative endosymbiont, transmitted vertically with frequent exchanges with the gut environment. Indeed, transmission electron microscopy showed escape or uptake of methanogens from/by a Cononympha cell. The genome of "Ca. Methanobrevibacter cononymphae" showed features consistent with its facultative lifestyle: i.e., the genome size (2.7 Mbp) comparable to those of free-living relatives; the pseudogenization of the formate dehydrogenase gene fdhA, unnecessary within the non-formate-producing host cell; the dependence on abundant acetate in the host cell as an essential carbon source; and the presence of a catalase gene, required for colonization on the microoxic gut wall. Our study revealed a versatile endosymbiosis between the methanogen and protists, which may be a strategy responding to changing conditions in the termite gut.

Comprehensive Insights into Potential Metabolic Functions of Myxococcota in Activated Sludge Systems

Myxobacteria, belonging to the phylum Myxococcota, are ubiquitous in soil, marine, and other environments. A recent metagenomic sequencing ana-lysis showed that Myxococcota are predominant in activated sludge systems; however, their metabolic traits remain unclear. In the present study, we exami-ned the potential biological functions of 46 metagenomic bins of Myxococcota reconstructed from activated sludge samples from four municipal sewage treatment plants. The results obtained showed that most Myxococcota bins had an almost complete set of genes associated with glycolysis and the TCA cycle. The Palsa-1104 and Polyangiales bins contained the glycoside hydrolase GH5 and peptidase M23, which are presumably involved in lysis of the cell wall and cellular cytoplasm, suggesting that some Myxococcota from activated sludge prey on other microorganisms. The cell contact-dependent predatory functions of Myxococcus xanthus are conserved in the family Myxococcaceae, but not in other families. Two bins belonging to Palsa-1104 had phototrophic gene clusters, indicating the potential for heterotrophic and autotrophic metabolism by these microbes. In assessments of the social behavior of Myxococcota in activated sludge, the FruA gene and C-signal gene, which are involved in the regulation of fruiting body formation, were lacking in Myxococcota bins, suggesting their inability to form fruiting bodies. In addition, multiple bins of Myxococcota had novel secondary metabolite biosynthesis gene clusters that may be used for the predation of other bacteria in activated sludge. Our metagenome-based ana-lyses provide novel insights into the microbial interactions associated with Myxococcota in activated sludge ecosystems.

Functional guilds and drivers of diversity in seaweed-associated bacteria

Comparisons of functional and taxonomic profiles from bacterial communities in different habitats have suggested the existence of functional guilds composed of taxonomically or phylogenetically distinct members. Such guild membership is, however, rarely defined and the factors that drive functional diversity in bacteria remain poorly understood. We used seaweed-associated bacteria as a model to shed light on these important aspects of community ecology. Using a large dataset of over 1300 metagenome-assembled genomes from 13 seaweed species we found substantial overlap in the functionality of bacteria coming from distinct taxa, thus supporting the existence of functional guilds. This functional equivalence between different taxa was particularly pronounced when only functions involved in carbohydrate degradation were considered. We further found that bacterial taxonomy is the dominant driver of functional differences between bacteria and that seaweed species or seaweed type (i.e. brown, red and green) had relatively stronger impacts on genome functionality for carbohydrate-degradation functions when compared to all other cellular functions. This study provides new insight into the factors underpinning the functional diversity of bacteria and contributes to our understanding how community function is generated from individual members.

Cost-effective complete genome sequencing using the MinION platform for identification of recombinant enteroviruses

IMPORTANCE

By employing a cost-effective approach for complete genome sequencing, the study has enabled the identification of novel enterovirus strains and shed light on the genetic exchange events during outbreaks. The success rate of genome sequencing and the scalability of the protocol demonstrate its practical utility for routine enterovirus surveillance. Moreover, the study's findings of recombinant strains of EVA71 and CVA2 contributing to epidemics in Malaysia and Taiwan emphasize the need for accurate detection and characterization of enteroviruses. The investigation of the whole genome and upstream ORF sequences has provided insights into the evolution and spread of enterovirus subgenogroups. These findings have important implications for the prevention, control, and surveillance of enteroviruses, ultimately contributing to the understanding and management of enterovirus-related illnesses.

Long-Read-Based Genome Assembly Reveals Numerous Endogenous Viral Elements in the Green Algal Bacterivore Cymbomonas tetramitiformis

The marine tetraflagellate Cymbomonas tetramitiformis has drawn attention as an early diverging green alga that uses a phago-mixotrophic mode of nutrition (i.e., the ability to derive nourishment from both photosynthesis and bacterial prey). The Cymbomonas nuclear genome was sequenced previously, but due to the exclusive use of short-read (Illumina) data, the assembly suffered from missing a large proportion of the genome's repeat regions. For this study, we generated Oxford Nanopore long-read and additional short-read Illumina data and performed a hybrid assembly that significantly improved the total assembly size and contiguity. Numerous endogenous viral elements were identified in the repeat regions of the new assembly. These include the complete genome of a giant Algavirales virus along with many genomes of integrated Polinton-like viruses (PLVs) from two groups: Gezel-like PLVs and a novel group of prasinophyte-specific PLVs. The integrated ∼400 kb genome of the giant Algavirales virus is the first account of the association of the uncultured viral family AG_03 with green algae. The complete PLV genomes from C. tetramitiformis ranged between 15 and 25 kb in length and showed a diverse gene content. In addition, heliorhodopsin gene-containing repeat elements of putative mirusvirus origin were identified. These results illustrate past (and possibly ongoing) multiple alga-virus interactions that accompanied the genome evolution of C. tetramitiformis.

One high quality genome and two transcriptome datasets for new species of Mantamonas, a deep-branching eukaryote clade

Mantamonads were long considered to represent an "orphan" lineage in the tree of eukaryotes, likely branching near the most frequently assumed position for the root of eukaryotes. Recent phylogenomic analyses have placed them as part of the "CRuMs" supergroup, along with collodictyonids and rigifilids. This supergroup appears to branch at the base of Amorphea, making it of special importance for understanding the deep evolutionary history of eukaryotes. However, the lack of representative species and complete genomic data associated with them has hampered the investigation of their biology and evolution. Here, we isolated and described two new species of mantamonads, Mantamonas vickermani sp. nov. and Mantamonas sphyraenae sp. nov., for each of which we generated transcriptomic sequence data, as well as a high-quality genome for the latter. The estimated size of the M. sphyraenae genome is 25 Mb; our de novo assembly appears to be highly contiguous and complete with 9,416 predicted protein-coding genes. This near-chromosome-scale genome assembly is the first described for the CRuMs supergroup.

BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

BACKGROUND

Exploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure.

RESULTS

We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset.

CONCLUSIONS

BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.

(m, n)-mer-a simple statistical feature for sequence classification

Summary

The (m, n)-mer is a simple alternative classification feature based on conditional probability distributions. In this application note, we compared k-mer and (m, n)-mer frequency features in 11 distinct datasets used for binary, multiclass and clustering classifications. Our findings show that the (m, n)-mer frequency features are related to the highest performance metrics and often statistically outperformed the k-mers. Here, the (m, n)-mer frequencies improved performance for classifying smaller sequence lengths (as short as 300 bp) and yielded higher metrics when using short values of k (ranging from 2 to 4). Therefore, we present the (m, n)-mers frequencies to the scientific community as a feature that seems to be quite effective in identifying complex discriminatory patterns and classifying polyphyletic sequence groups.

Availability and implementation

The (m, n)-mer algorithm is released as an R package within the CRAN project (https://cran.r-project.org/web/packages/mnmer) and is also available at https://github.com/labinfo-lncc/mnmer.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Disruption of fish gut microbiota composition and holobiont's metabolome during a simulated Microcystis aeruginosa (Cyanobacteria) bloom

BACKGROUND

Cyanobacterial blooms are one of the most common stressors encountered by metazoans living in freshwater lentic systems such as lakes and ponds. Blooms reportedly impair fish health, notably through oxygen depletion and production of bioactive compounds including cyanotoxins. However, in the times of the "microbiome revolution", it is surprising that so little is still known regarding the influence of blooms on fish microbiota. In this study, an experimental approach is used to demonstrate that blooms affect fish microbiome composition and functions, as well as the metabolome of holobionts. To this end, the model teleost Oryzias latipes is exposed to simulated Microcystis aeruginosa blooms of various intensities in a microcosm setting, and the response of bacterial gut communities is evaluated in terms of composition and metabolome profiling. Metagenome-encoded functions are compared after 28 days between control individuals and those exposed to highest bloom level.

RESULTS

The gut bacterial community of O. latipes exhibits marked responses to the presence of M. aeruginosa blooms in a dose-dependent manner. Notably, abundant gut-associated Firmicutes almost disappear, while potential opportunists increase. The holobiont's gut metabolome displays major changes, while functions encoded in the metagenome of bacterial partners are more marginally affected. Bacterial communities tend to return to original composition after the end of the bloom and remain sensitive in case of a second bloom, reflecting a highly reactive gut community.

CONCLUSION

Gut-associated bacterial communities and holobiont functioning are affected by both short and long exposure to M. aeruginosa, and show evidence of post-bloom resilience. These findings point to the significance of bloom events to fish health and fitness, including survival and reproduction, through microbiome-related effects. In the context of increasingly frequent and intense blooms worldwide, potential outcomes relevant to conservation biology as well as aquaculture warrant further investigation. Video Abstract.

Identification, classification, and functional characterization of novel sponge-associated acidimicrobiial species

Sponges are known to harbour an exceptional diversity of uncultured microorganisms, including members of the phylum Actinobacteriota. While members of the actinobacteriotal class Actinomycetia have been studied intensively due to their potential for secondary metabolite production, the sister class of Acidimicrobiia is often more abundant in sponges. However, the taxonomy, functions, and ecological roles of sponge-associated Acidimicrobiia are largely unknown. Here, we reconstructed and characterized 22 metagenome-assembled genomes (MAGs) of Acidimicrobiia from three sponge species. These MAGs represented six novel species, belonging to five genera, four families, and two orders, which are all uncharacterized (except the order Acidimicrobiales) and for which we propose nomenclature. These six uncultured species have either only been found in sponges and/or corals and have varying degrees of specificity to their host species. Functional gene profiling indicated that these six species shared a similar potential to non-symbiotic Acidimicrobiia with respect to amino acid biosynthesis and utilization of sulfur compounds. However, sponge-associated Acidimicrobiia differed from their non-symbiotic counterparts by relying predominantly on organic rather than inorganic sources of energy, and their predicted capacity to synthesise bioactive compounds or their precursors implicated in host defence. Additionally, the species possess the genetic capacity to degrade aromatic compounds that are frequently found in sponges. The novel Acidimicrobiia may also potentially mediate host development by modulating Hedgehog signalling and by the production of serotonin, which can affect host body contractions and digestion. These results highlight unique genomic and metabolic features of six new acidimicrobiial species that potentially support a sponge-associated lifestyle.

Functional characterization and taxonomic classification of novel gammaproteobacterial diversity in sponges

Sponges harbour exceptionally diverse microbial communities, whose members are largely uncultured. The class Gammaproteobacteria often dominates the microbial communities of various sponge species, but most of its diversity remains functional and taxonomically uncharacterised. Here we reconstructed and characterised 32 metagenome-assembled genomes (MAGs) derived from three sponge species. These MAGs represent ten novel species and belong to seven orders, of which one is new. We propose nomenclature for all these taxa. These new species comprise sponge-specific bacteria with varying levels of host specificity. Functional gene profiling highlights significant differences in metabolic capabilities across the ten species, though each also often exhibited a large degree of metabolic diversity involving various nitrogen- and sulfur-based compounds. The genomic features of the ten species suggest they have evolved to form symbiotic interaction with their hosts or are well-adapted to survive within the sponge environment. These Gammaproteobacteria are proposed to scavenge substrates from the host environment, including metabolites or cellular components of the sponge. Their diverse metabolic capabilities may allow for efficient cycling of organic matter in the sponge environment, potentially to the benefit of the host and other symbionts.

Exploring microbial functional biodiversity at the protein family level-From metagenomic sequence reads to annotated protein clusters

Metagenomics has enabled accessing the genetic repertoire of natural microbial communities. Metagenome shotgun sequencing has become the method of choice for studying and classifying microorganisms from various environments. To this end, several methods have been developed to process and analyze the sequence data from raw reads to end-products such as predicted protein sequences or families. In this article, we provide a thorough review to simplify such processes and discuss the alternative methodologies that can be followed in order to explore biodiversity at the protein family level. We provide details for analysis tools and we comment on their scalability as well as their advantages and disadvantages. Finally, we report the available data repositories and recommend various approaches for protein family annotation related to phylogenetic distribution, structure prediction and metadata enrichment.

Widespread formation of intracellular calcium carbonates by the bloom-forming cyanobacterium Microcystis

The formation of intracellular amorphous calcium carbonates (iACC) has been recently observed in a few cultured strains of Microcystis, a potentially toxic bloom-forming cyanobacterium found worldwide in freshwater ecosystems. If iACC-forming Microcystis are abundant within blooms, they may represent a significant amount of particulate Ca. Here, we investigate the significance of iACC biomineralization by Microcystis. First, the presence of iACC-forming Microcystis cells has been detected in several eutrophic lakes, indicating that this phenomenon occurs under environmental conditions. Second, some genotypic (presence/absence of ccyA, a marker gene of iACC biomineralization) and phenotypic (presence/absence of iACC) diversity have been detected within a collection of strains isolated from one single lake. This illustrates that this trait is frequent but also variable within Microcystis even at a single locality. Finally, one-third of publicly available genomes of Microcystis were shown to contain the ccyA gene, revealing a wide geographic and phylogenetic distribution within the genus. Overall, the present work shows that the formation of iACC by Microcystis is common under environmental conditions. While its biological function remains undetermined, this process should be further considered regarding the biology of Microcystis and implications on the Ca geochemical cycle in freshwater environments.

Genomic and Transcriptomic Insights into Salinity Tolerance-Based Niche Differentiation of Synechococcus Clades in Estuarine and Coastal Waters

Cluster 5 Synechococcus is one of the most important primary producers on earth. However, ecotypes of this genus exhibit complex geographical distributions, and the genetic basis of niche partitioning is still not fully understood. Here, we report distinct distributions of subcluster 5.1 (SC5.1) and subcluster 5.2 (SC5.2) Synechococcus in estuarine waters, and we reveal that salinity is the main factor determining their distribution. Clade III (belonging to SC5.1) and CB4 (belonging to SC5.2) are dominant clades in the study region, with different ecological distributions. We further conducted physiological, genomic, and transcriptomic studies of Synechococcus strains YX04-3 and HK05, which are affiliated with clade III and CB4, respectively. Laboratory tests showed that HK05 could grow at low salinity (13 ppt), whereas the growth of YX04-3 was suppressed when salinity decreased to 13 ppt. Genomic and transcriptomic analysis suggested that euryhaline clade CB4 is capable of dealing with a sudden drop of salinity by releasing compatible solutes through mechanosensitive channels that are coded by the mscL gene, decreasing biosynthesis of organic osmolytes, and increasing expression of heat shock proteins and high light-inducible proteins to protect photosystem. Furthermore, CB4 strain HK05 exhibited a higher growth rate when growing at low salinity than at high salinity. This is likely achieved by reducing its biosynthesis of organic osmolyte activity and increasing its photosynthetic activity at low salinity, which allowed it to enhance the assimilation of inorganic carbon and nitrogen. Together, these results provide new insights regarding the ecological distribution of SC5.2 and SC5.1 ecotypes and their underlying molecular mechanisms. IMPORTANCE Synechococcus is a group of unicellular Cyanobacteria that are widely distributed in global aquatic ecosystems. Salinity is a factor that affects the distribution of microorganisms in estuarine and coastal environments. In this study, we studied the distribution pattern of Synechococcus community along the salinity gradient in a subtropical estuary. By using omic methods, we unveiled genetic traits that determine the niche partitioning of euryhaline and strictly marine Synechococcus. We also explored the strategies employed by euryhaline Synechococcus to cope with a sudden drop of salinity, and revealed possible mechanisms for the higher growth rate of euryhaline Synechococcus in low salinity conditions. This study provides new insight into the genetic basis of niche partitioning of Synechococcus clades.

Draft genomes of Blastocystis subtypes from human samples of Colombia

BACKGROUND

Blastocystis is one of the most common eukaryotic microorganisms colonizing the intestines of both humans and animals, but the conditions under which it may be a pathogen are unclear.

METHODS

To study the genomic characteristics of circulating subtypes (ST) in Colombia, we established nine xenic cultures from Blastocystis isolated from human fecal samples, we identified 10 different subtypes, since one sample had a mixed infection. Thus, the genomes of the subtypes ST1 (n = 3), ST2 (n = 1), ST3 (n = 2), ST6 (n = 1), ST7 (n = 1), and ST8 (n = 2) were sequenced using Illumina and Oxford Nanopore Technologies (ONT).

RESULTS

Analyses of these draft nuclear genomes indicated remarkable diversity in terms of genome size and guanine-cytosine (GC) content among the compared STs. Illumina sequencing-only draft genomes contained 824 to 2077 scaffolds, with total genome size ranging from 12 to 13.2 Mb and N₅₀ values ranging from 10,585 to 29,404 base pairs (bp). The genome of one ST1 isolate was sequenced using ONT. This assembly was more contiguous, with a size of 20 million base pairs (Mb) spread over 116 scaffolds, and an N₅₀ of 248,997 bp.

CONCLUSION

This work represents one of the few large-scale comparative genomic analyses of Blastocystis isolates, providing an additional glimpse into its genomic diversity.

Managing the Transition to Widespread Metagenomic Monitoring: Policy Considerations for Future Biosurveillance

The technological possibilities and future public health importance of metagenomic sequencing have received extensive attention, but there has been little discussion about the policy and regulatory issues that need to be addressed if metagenomic sequencing is adopted as a key technology for biosurveillance. In this article, we introduce metagenomic monitoring as a possible path to eventually replacing current infectious disease monitoring models. Many key enablers are technological, whereas others are not. We therefore highlight key policy challenges and implementation questions that need to be addressed for "widespread metagenomic monitoring" to be possible. Policymakers must address pitfalls like fragmentation of the technological base, private capture of benefits, privacy concerns, the usefulness of the system during nonpandemic times, and how the future systems will enable better response. If these challenges are addressed, the technological and public health promise of metagenomic sequencing can be realized.

MetaBinner: a high-performance and stand-alone ensemble binning method to recover individual genomes from complex microbial communities

Binning aims to recover microbial genomes from metagenomic data. For complex metagenomic communities, the available binning methods are far from satisfactory, which usually do not fully use different types of features and important biological knowledge. We developed a novel ensemble binner, MetaBinner, which generates component results with multiple types of features by k-means and uses single-copy gene information for initialization. It then employs a two-stage ensemble strategy based on single-copy genes to integrate the component results efficiently and effectively. Extensive experimental results on three large-scale simulated datasets and one real-world dataset demonstrate that MetaBinner outperforms the state-of-the-art binners significantly.

Phylogenomics and the first higher taxonomy of Placozoa, an ancient and enigmatic animal phylum

Placozoa is an ancient phylum of extraordinarily unusual animals: miniscule, ameboid creatures that lack most fundamental animal features. Despite high genetic diversity, only recently have the second and third species been named. While prior genomic studies suffer from incomplete placozoan taxon sampling, we more than double the count with protein sequences from seven key genomes and produce the first nuclear phylogenomic reconstruction of all major placozoan lineages. This leads us to the first complete Linnaean taxonomic classification of Placozoa, over a century after its discovery: This may be the only time in the 21st century when an entire higher taxonomy for a whole animal phylum is formalized. Our classification establishes 2 new classes, 4 new orders, 3 new families, 1 new genus, and 1 new species, namely classes Polyplacotomia and Uniplacotomia; orders Polyplacotomea, Trichoplacea, Cladhexea, and Hoilungea; families Polyplacotomidae, Cladtertiidae, and Hoilungidae; and genus Cladtertia with species Cladtertia collaboinventa, nov. Our likelihood and gene content tree topologies refine the relationships determined in previous studies. Adding morphological data into our phylogenomic matrices suggests sponges (Porifera) as the sister to other animals, indicating that modest data addition shifts this node away from comb jellies (Ctenophora). Furthermore, by adding the first genomic protein data of the exceptionally distinct and branching Polyplacotoma mediterranea, we solidify its position as sister to all other placozoans; a divergence we estimate to be over 400 million years old. Yet even this deep split sits on a long branch to other animals, suggesting a bottleneck event followed by diversification. Ancestral state reconstructions indicate large shifts in gene content within Placozoa, with Hoilungia hongkongensis and its closest relatives having the most unique genetics.

Constructing metagenome-assembled genomes for almost all components in a real bacterial consortium for binning benchmarking

BACKGROUND

So far, a lot of binning approaches have been intensively developed for untangling metagenome-assembled genomes (MAGs) and evaluated by two main strategies. The strategy by comparison to known genomes prevails over the other strategy by using single-copy genes. However, there is still no dataset with all known genomes for a real (not simulated) bacterial consortium yet.

RESULTS

Here, we continue investigating the real bacterial consortium F1RT enriched and sequenced by us previously, considering the high possibility to unearth all MAGs, due to its low complexity. The improved F1RT metagenome reassembled by metaSPAdes here utilizes about 98.62% of reads, and a series of analyses for the remaining reads suggests that the possibility of containing other low-abundance organisms in F1RT is greatly low, demonstrating that almost all MAGs are successfully assembled. Then, 4 isolates are obtained and individually sequenced. Based on the 4 isolate genomes and the entire metagenome, an elaborate pipeline is then in-house developed to construct all F1RT MAGs. A series of assessments extensively prove the high reliability of the herein reconstruction. Next, our findings further show that this dataset harbors several properties challenging for binning and thus is suitable to compare advanced binning tools available now or benchmark novel binners. Using this dataset, 8 advanced binning algorithms are assessed, giving useful insights for developing novel approaches. In addition, compared with our previous study, two novel MAGs termed FC8 and FC9 are discovered here, and 7 MAGs are solidly unearthed for species without any available genomes.

CONCLUSION

To our knowledge, it is the first time to construct a dataset with almost all known MAGs for a not simulated consortium. We hope that this dataset will be used as a routine toolkit to complement mock datasets for evaluating binning methods to further facilitate binning and metagenomic studies in the future.

binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets

The reconstruction of genomes is a critical step in genome-resolved metagenomics and for multi-omic data integration from microbial communities. Here, we present binny, a binning tool that produces high-quality metagenome-assembled genomes (MAG) from both contiguous and highly fragmented genomes. Based on established metrics, binny outperforms or is highly competitive with commonly used and state-of-the-art binning methods and finds unique genomes that could not be detected by other methods. binny uses k-mer-composition and coverage by metagenomic reads for iterative, nonlinear dimension reduction of genomic signatures as well as subsequent automated contig clustering with cluster assessment using lineage-specific marker gene sets. When compared with seven widely used binning algorithms, binny provides substantial amounts of uniquely identified MAGs and almost always recovers the most near-complete ($\gt 95\%$ pure, $\gt 90\%$ complete) and high-quality ($\gt 90\%$ pure, $\gt 70\%$ complete) genomes from simulated datasets from the Critical Assessment of Metagenome Interpretation initiative, as well as substantially more high-quality draft genomes, as defined by the Minimum Information about a Metagenome-Assembled Genome standard, from a real-world benchmark comprised of metagenomes from various environments than any other tested method.

Microbial communities of stratified aquatic ecosystems of Kandalaksha Bay (White Sea) shed light on the evolutionary history of green and brown morphotypes of Chlorobiota

Anoxygenic photoautotrophic metabolism of green sulfur bacteria of the family Chlorobiaceae played a significant role in establishing the Earth's biosphere. Two known major ecological forms of these phototrophs differ in their pigment composition and, therefore, in color: the green and brown forms. The latter form often occurs in low-light environments and is specialized to harvest blue light, which can penetrate to the greatest depth in the water column. In the present work, metagenomic sequencing was used to investigate the natural population of brown Chl. phaeovibrioides ZM in a marine stratified Zeleny Mys lagoon in the Kandalaksha Bay (the White Sea) to supplement the previously obtained genomes of brown Chlorobiaceae. The genomes of brown and green Chlorobiaceae were investigated using comparative genome analysis and phylogenetic and reconciliation analysis to reconstruct the evolution of these ecological forms. Our results support the suggestion that the last common ancestor of Chlorobiaceae belonged to the brown form, i.e. it was adapted to the conditions of low illumination. However, despite the vertical inheritance of these characteristics, among modern Chlorobiaceae populations, the genes responsible for synthesizing the pigments of the brown form are subject to active horizontal transfer.

Metagenome-Assembled Genome Sequence of Marine Rhizobiaceae sp. Strain MnEN-MB40S, Obtained from Manganese-Oxidizing Enrichment Culture

Here, we report a new metagenome-assembled genome (MAG) from a marine Rhizobiaceae species. The MnEN-MB40S genome was assembled from a manganese-oxidizing enrichment culture metagenome. A 4.1-Mb MAG comprising 26 contigs, with a GC content of 60.0%, was obtained. This MAG contributes to the genomic information regarding the family Rhizobiaceae.

Metric learning for comparing genomic data with triplet network

Many biological applications are essentially pairwise comparison problems, such as evolutionary relationships on genomic sequences, contigs binning on metagenomic data, cell type identification on gene expression profiles of single-cells, etc. To make pair-wise comparison, it is necessary to adopt suitable dissimilarity metric. However, not all the metrics can be fully adapted to all possible biological applications. It is necessary to employ metric learning based on data adaptive to the application of interest. Therefore, in this study, we proposed MEtric Learning with Triplet network (MELT), which learns a nonlinear mapping from original space to the embedding space in order to keep similar data closer and dissimilar data far apart. MELT is a weakly supervised and data-driven comparison framework that offers more adaptive and accurate dissimilarity learned in the absence of the label information when the supervised methods are not applicable. We applied MELT in three typical applications of genomic data comparison, including hierarchical genomic sequences, longitudinal microbiome samples and longitudinal single-cell gene expression profiles, which have no distinctive grouping information. In the experiments, MELT demonstrated its empirical utility in comparison to many widely used dissimilarity metrics. And MELT is expected to accommodate a more extensive set of applications in large-scale genomic comparisons. MELT is available at https://github.com/Ying-Lab/MELT.

Metagenomic binning with assembly graph embeddings

MOTIVATION

Despite recent advancements in sequencing technologies and assembly methods, obtaining high-quality microbial genomes from metagenomic samples is still not a trivial task. Current metagenomic binners do not take full advantage of assembly graphs and are not optimized for long-read assemblies. Deep graph learning algorithms have been proposed in other fields to deal with complex graph data structures. The graph structure generated during the assembly process could be integrated with contig features to obtain better bins with deep learning.

RESULTS

We propose GraphMB, which uses graph neural networks to incorporate the assembly graph into the binning process. We test GraphMB on long-read datasets of different complexities, and compare the performance with other binners in terms of the number of High Quality (HQ) genome bins obtained. With our approach, we were able to obtain unique bins on all real datasets, and obtain more bins on most datasets. In particular, we obtained on average 17.5% more HQ bins when compared with state-of-the-art binners and 13.7% when aggregating the results of our binner with the others. These results indicate that a deep learning model can integrate contig-specific and graph-structure information to improve metagenomic binning.

AVAILABILITY AND IMPLEMENTATION

GraphMB is available from https://github.com/MicrobialDarkMatter/GraphMB.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

vRhyme enables binning of viral genomes from metagenomes

Genome binning has been essential for characterization of bacteria, archaea, and even eukaryotes from metagenomes. Yet, few approaches exist for viruses. We developed vRhyme, a fast and precise software for construction of viral metagenome-assembled genomes (vMAGs). vRhyme utilizes single- or multi-sample coverage effect size comparisons between scaffolds and employs supervised machine learning to identify nucleotide feature similarities, which are compiled into iterations of weighted networks and refined bins. To refine bins, vRhyme utilizes unique features of viral genomes, namely a protein redundancy scoring mechanism based on the observation that viruses seldom encode redundant genes. Using simulated viromes, we displayed superior performance of vRhyme compared to available binning tools in constructing more complete and uncontaminated vMAGs. When applied to 10,601 viral scaffolds from human skin, vRhyme advanced our understanding of resident viruses, highlighted by identification of a Herelleviridae vMAG comprised of 22 scaffolds, and another vMAG encoding a nitrate reductase metabolic gene, representing near-complete genomes post-binning. vRhyme will enable a convention of binning uncultivated viral genomes and has the potential to transform metagenome-based viral ecology.

Discovery of lignin-transforming bacteria and enzymes in thermophilic environments using stable isotope probing

Characterizing microorganisms and enzymes involved in lignin biodegradation in thermal ecosystems can identify thermostable biocatalysts. We integrated stable isotope probing (SIP), genome-resolved metagenomics, and enzyme characterization to investigate the degradation of high-molecular weight, ¹³C-ring-labeled synthetic lignin by microbial communities from moderately thermophilic hot spring sediment (52 °C) and a woody "hog fuel" pile (53 and 62 °C zones). ¹³C-Lignin degradation was monitored using IR-GCMS of ¹³CO₂, and isotopic enrichment of DNA was measured with UHLPC-MS/MS. Assembly of 42 metagenomic libraries (72 Gb) yielded 344 contig bins, from which 125 draft genomes were produced. Fourteen genomes were significantly enriched with ¹³C from lignin, including genomes of Actinomycetes (Thermoleophilaceae, Solirubrobacteraceae, Rubrobacter sp.), Firmicutes (Kyrpidia sp., Alicyclobacillus sp.) and Gammaproteobacteria (Steroidobacteraceae). We employed multiple approaches to screen genomes for genes encoding putative ligninases and pathways for aromatic compound degradation. Our analysis identified several novel laccase-like multi-copper oxidase (LMCO) genes in ¹³C-enriched genomes. One of these LMCOs was heterologously expressed and shown to oxidize lignin model compounds and minimally transformed lignin. This study elucidated bacterial lignin depolymerization and mineralization in thermal ecosystems, establishing new possibilities for the efficient valorization of lignin at elevated temperature.

Phylogenomic analysis and metabolic role reconstruction of mutualistic Rhizobiales hindgut symbionts of Acromyrmex leaf-cutting ants

Rhizobiales are well-known plant-root nitrogen-fixing symbionts, but the functions of insect-associated Rhizobiales are poorly understood. We obtained genomes of three strains associated with Acromyrmex leaf-cutting ants and show that, in spite of being extracellular gut symbionts, they lost all pathways for essential amino acid biosynthesis, making them fully dependent on their hosts. Comparison with 54 Rhizobiales genomes showed that all insect-associated Rhizobiales lost the ability to fix nitrogen and that the Acromyrmex symbionts had exceptionally also lost the urease genes. However, the Acromyrmex strains share biosynthesis pathways for riboflavin vitamin, queuosine and a wide range of antioxidant enzymes likely to be beneficial for the ant fungus-farming symbiosis. We infer that the Rhizobiales symbionts catabolize excess of fungus-garden-derived arginine to urea, supplementing complementary Mollicutes symbionts that turn arginine into ammonia and infer that these combined symbiont activities stabilize the fungus-farming mutualism. Similar to the Mollicutes symbionts, the Rhizobiales species have fully functional CRISPR/Cas and R-M phage defenses, suggesting that these symbionts are important enough for the ant hosts to have precluded the evolution of metabolically cheaper defenseless strains.

Binning long reads in metagenomics datasets using composition and coverage information

Background

Advancements in metagenomics sequencing allow the study of microbial communities directly from their environments. Metagenomics binning is a key step in the species characterisation of microbial communities. Next-generation sequencing reads are usually assembled into contigs for metagenomics binning mainly due to the limited information within short reads. Third-generation sequencing provides much longer reads that have lengths similar to the contigs assembled from short reads. However, existing contig-binning tools cannot be directly applied on long reads due to the absence of coverage information and the presence of high error rates. The few existing long-read binning tools either use only composition or use composition and coverage information separately. This may ignore bins that correspond to low-abundance species or erroneously split bins that correspond to species with non-uniform coverages. Here we present a reference-free binning approach, LRBinner, that combines composition and coverage information of complete long-read datasets. LRBinner also uses a distance-histogram-based clustering algorithm to extract clusters with varying sizes.

Results

The experimental results on both simulated and real datasets show that LRBinner achieves the best binning accuracy in most cases while handling the complete datasets without any sampling. Moreover, we show that binning reads using LRBinner prior to assembly reduces computational resources required for assembly while attaining satisfactory assembly qualities.

Conclusion

LRBinner shows that deep-learning techniques can be used for effective feature aggregation to support the metagenomics binning of long reads. Furthermore, accurate binning of long reads supports improvements in metagenomics assembly, especially in complex datasets. Binning also helps to reduce the resources required for assembly. Source code for LRBinner is freely available at https://github.com/anuradhawick/LRBinner.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13015-022-00221-z.

Methanol utilizers of the rhizosphere and phyllosphere of a common grass and forb host species

BACKGROUND

Managed grasslands are global sources of atmospheric methanol, which is one of the most abundant volatile organic compounds in the atmosphere and promotes oxidative capacity for tropospheric and stratospheric ozone depletion. The phyllosphere is a favoured habitat of plant-colonizing methanol-utilizing bacteria. These bacteria also occur in the rhizosphere, but their relevance for methanol consumption and ecosystem fluxes is unclear. Methanol utilizers of the plant-associated microbiota are key for the mitigation of methanol emission through consumption. However, information about grassland plant microbiota members, their biodiversity and metabolic traits, and thus key actors in the global methanol budget is largely lacking.

RESULTS

We investigated the methanol utilization and consumption potentials of two common plant species (Festuca arundinacea and Taraxacum officinale) in a temperate grassland. The selected grassland exhibited methanol formation. The detection of ¹³C derived from ¹³C-methanol in 16S rRNA of the plant microbiota by stable isotope probing (SIP) revealed distinct methanol utilizer communities in the phyllosphere, roots and rhizosphere but not between plant host species. The phyllosphere was colonized by members of Gamma- and Betaproteobacteria. In the rhizosphere, ¹³C-labelled Bacteria were affiliated with Deltaproteobacteria, Gemmatimonadates, and Verrucomicrobiae. Less-abundant ¹³C-labelled Bacteria were affiliated with well-known methylotrophs of Alpha-, Gamma-, and Betaproteobacteria. Additional metagenome analyses of both plants were consistent with the SIP results and revealed Bacteria with methanol dehydrogenases (e.g., MxaF1 and XoxF1-5) of known but also unusual genera (i.e., Methylomirabilis, Methylooceanibacter, Gemmatimonas, Verminephrobacter). ¹⁴C-methanol tracing of alive plant material revealed divergent potential methanol consumption rates in both plant species but similarly high rates in the rhizosphere and phyllosphere.

CONCLUSIONS

Our study revealed the rhizosphere as an overlooked hotspot for methanol consumption in temperate grasslands. We further identified unusual new but potentially relevant methanol utilizers besides well-known methylotrophs in the phyllosphere and rhizosphere. We did not observe a plant host-specific methanol utilizer community. Our results suggest that our approach using quantitative SIP and metagenomics may be useful in future field studies to link gross methanol consumption rates with the rhizosphere and phyllosphere microbiome.

High-rate cotreatment of purified terephthalate and dimethyl terephthalate manufacturing wastewater by a mesophilic upflow anaerobic sludge blanket reactor and the microbial ecology relevant to aromatic compound degradation

Polyethylene terephthalate (PET) is produced worldwide, mainly as material for plastic drink bottles. PET is produced by polymerization of purified terephthalate (PTA) or dimethyl terephthalate (DMT) with ethylene glycol. During the synthetic manufacturing processes of PTA and DMT, high organic loading wastewater is produced, which is typically treated separately by anaerobic wastewater treatment technologies. Given the high demand for PET, manufacturing plants are expanding globally, which will result in an increase in the amounts of PTA and DMT wastewater in need of treatment. In terms of effective treatment, the cotreatment of PTA and DMT wastewater has several advantages, including lower area and energy requirements. In this study, we examined the performance of an upflow anaerobic sludge blanket (UASB) reactor in cotreating PTA and DMT wastewater with high organic loading, evaluating its removal characteristics after 518 days of continuous operation. In addition, we performed a microbiome analysis of the UASB granular sludge to uncover the microbial interactions and metabolic functions within the reactor. By continuous operation, we achieved an organic removal rate of 6.6 kg m^-3 day^-1. In addition, we confirmed that aromatic compounds in the complex wastewater from the PTA and DMT manufacturing processes are biodegradable in the following order: benzoate > orthophthalate > terephthalate > isophthalate > p-toluic acid. 16S rRNA gene-based network analysis shows that anaerobic Woesearchaeales belonging to phylum Nanoarchaeota has a positive correlation with Methanoregula, Candidatus Methanofastidiosum, and Methanosarcina, suggesting a symbiotic relationship with methanogens in granular sludge. Shotgun metagenomic analysis revealed that terephthalate, isophthalate/orthophthalate, and benzoate were degraded by different members of Pelotomaculaceae and Syntrophorhabdaceae. According to the genomic information, we propose two new possible routes for orthophthalate degradation by the Syntrophorhabdaceae organism.

The in-situ release of algal bloom populations and the role of prokaryotic communities in their establishment and growth

Harmful algal blooms (HABs) may quickly travel and inoculate new water bodies via currents and runoff in estuaries. The role of in-situ prokaryotic communities in the re-establishment and growth of inoculated algal blooms remains unknown. A novel on-board incubation experiment was employed to simulate the sudden surge of algal blooms to new estuarine waters and reveal possible outcomes. A dinoflagellate (Amphidinium carterae) and a diatom species (Thalassiosira weissflogii) which had bloomed in the Pearl River Estuary (PRE) area were cultured to bloom densities and reintroduced back into PRE natural seawaters. The diatom showed better adaptation ability to the new environment and increased significantly after the incubation. Simultaneously, particle-attached (PA) prokaryotic community structure was strongly influenced by adding of the diatom, with some opportunistic prokaryotes significantly enhanced in the diatom treatment. Whereas the dinoflagellate population did not increase following incubation, and their PA prokaryotic community showed no significant differences relative to the control. Metagenomic analyzes revealed that labile carbohydrates and organic nitrogen produced by the diatom contributed to the surge of certain PA prokaryotes. Genomic properties of a bacteria strain, which is affiliated with genus GMD16E07 (Planctomycetaceae) and comprised up to 50% of PA prokaryotes in the diatom treatment, was described here for the first time. Notably, the association of Planctomycetaceae and T. weissflogii likely represents symbiotic mutualism, with the diatom providing organic matter for Planctomycetaceae and the bacteria supplying vitamins and detoxifying nitriles and hydrogen peroxides in exchange. Therefore, the close association between Planctomycetaceae and T. weissflogii promoted the growth of both populations, and eventually facilitated the diatom bloom establishment.

MarkerMAG: linking metagenome-assembled genomes (MAGs) with 16S rRNA marker genes using paired-end short reads

MOTIVATION

Metagenome-assembled genomes (MAGs) have substantially extended our understanding of microbial functionality. However, 16S rRNA genes, which are commonly used in phylogenetic analysis and environmental surveys, are often missing from MAGs. Here, we developed MarkerMAG, a pipeline that links 16S rRNA genes to MAGs using paired-end sequencing reads.

RESULTS

Assessment of MarkerMAG on three benchmarking metagenomic datasets with various degrees of complexity shows substantial increases in the number of MAGs with 16S rRNA genes and a 100% assignment accuracy. MarkerMAG also estimates the copy number of 16S rRNA genes in MAGs with high accuracy. Assessments on three real metagenomic datasets demonstrates 1.1- to 14.2-fold increases in the number of MAGs with 16S rRNA genes. We also show that MarkerMAG-improved MAGs increase the accuracy of functional prediction from 16S rRNA gene amplicon data. MarkerMAG is helpful in connecting information in MAG database with those in 16S rRNA databases and surveys and hence contributes to our increasing understanding of microbial diversity, function, and phylogeny.

AVAILABILITY

MarkerMAG is implemented in Python3 and freely available at https://github.com/songweizhi/MarkerMAG.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MetaConClust - Unsupervised Binning of Metagenomics Data using Consensus Clustering

Background: Binning of metagenomic reads is an active area of research, and many unsupervised machine learning-based techniques have been used for taxonomic independent binning of metagenomic reads. Objective: It is important to find the optimum number of the cluster as well as develop an efficient pipeline for deciphering the complexity of the microbial genome. Methods: Applying unsupervised clustering techniques for binning requires finding the optimal number of clusters beforehand and is observed to be a difficult task. This paper describes a novel method, MetaConClust, using coverage information for grouping of contigs and automatically finding the optimal number of clusters for binning of metagenomics data using a consensus-based clustering approach. The coverage of contigs in a metagenomics sample has been observed to be directly proportional to the abundance of species in the sample and is used for grouping of data in the first phase by MetaConClust. The Partitioning Around Medoid (PAM) method is used for clustering in the second phase for generating bins with the initial number of clusters determined automatically through a consensus-based method. Results: Finally, the quality of the obtained bins is tested using silhouette index, rand Index, recall, precision, and accuracy. Performance of MetaConClust is compared with recent methods and tools using benchmarked low complexity simulated and real metagenomic datasets and is found better for unsupervised and comparable for hybrid methods. Conclusion: This is suggestive of the proposition that the consensus-based clustering approach is a promising method for automatically finding the number of bins for metagenomics data.

Growth of nitrite-oxidizing Nitrospira and ammonia-oxidizing Nitrosomonas in marine recirculating trickling biofilter reactors

Aerobic ammonia and nitrite oxidation reactions are fundamental biogeochemical reactions contributing to the global nitrogen cycle. Although aerobic nitrite oxidation yields 4.8-folds less Gibbs free energy (∆G_r ) than aerobic ammonia oxidation in the NH₄ ⁺ -feeding marine recirculating trickling biofilter reactors operated in the present study, nitrite-oxidizing and not ammonia-oxidizing Nitrospira (sublineage IV) outnumbered ammonia-oxidizing Nitrosomonas (relative abundance; 53.8% and 7.59% respectively). CO₂ assimilation efficiencies during ammonia or nitrite oxidation were 0.077 μmol-¹⁴ CO₂ /μmol-NH₃ and 0.053-0.054 μmol-¹⁴ CO₂ /μmol-NO₂ ^- respectively, and the difference between ammonia and nitrite oxidation was much smaller than the difference of ∆G_r . Free-energy efficiency of nitrite oxidation was higher than ammonia oxidation (31%-32% and 13% respectively), and high CO₂ assimilation and free-energy efficiencies were a determinant for the dominance of Nitrospira over Nitrosomonas. Washout of Nitrospira and Nitrosomonas from the trickling biofilter reactors was also examined by quantitative PCR assay. Normalized copy numbers of Nitrosomonas amoA were 1.5- to 1.7-folds greater than Nitrospira nxrB and 16S rRNA gene in the reactor effluents. Nitrosomonas was more susceptible for washout than Nitrospira in the trickling biofilter reactors, which was another determinant for the dominance of Nitrospira in the trickling biofilter reactors.

Introduction to the principles and methods underlying the recovery of metagenome-assembled genomes from metagenomic data

The rise of metagenomics offers a leap forward for understanding the genetic diversity of microorganisms in many different complex environments by providing a platform that can identify potentially unlimited numbers of known and novel microorganisms. As such, it is impossible to imagine new major initiatives without metagenomics. Nevertheless, it represents a relatively new discipline with various levels of complexity and demands on bioinformatics. The underlying principles and methods used in metagenomics are often seen as common knowledge and often not detailed or fragmented. Therefore, we reviewed these to guide microbiologists in taking the first steps into metagenomics. We specifically focus on a workflow aimed at reconstructing individual genomes, that is, metagenome-assembled genomes, integrating DNA sequencing, assembly, binning, identification and annotation.

MetaDecoder: a novel method for clustering metagenomic contigs

BACKGROUND

Clustering the metagenomic contigs into potential genomes is a key step to investigate the functional roles of microbial populations. Existing algorithms have achieved considerable success with simulated or real sequencing datasets. However, accurately classifying contigs from complex metagenomes is still a challenge.

RESULTS

We introduced a novel clustering algorithm, MetaDecoder, which can classify metagenomic contigs based on the frequencies of k-mers and coverages. MetaDecoder was built as a two-layer model with the first layer being a GPU-based modified Dirichlet process Gaussian mixture model (DPGMM), which controls the weight of each DPGMM cluster to avoid over-segmentation by dynamically dissolving contigs in small clusters and reassigning them to the remaining clusters. The second layer comprises a semi-supervised k-mer frequency probabilistic model and a modified Gaussian mixture model for modeling the coverage based on single copy marker genes. Benchmarks on simulated and real-world datasets demonstrated that MetaDecoder can be served as a promising approach for effectively clustering metagenomic contigs.

CONCLUSIONS

In conclusion, we developed the GPU-based MetaDecoder for effectively clustering metagenomic contigs and reconstructing microbial communities from microbial data. Applying MetaDecoder on both simulated and real-world datasets demonstrated that it could generate more complete clusters with lower contamination. Using MetaDecoder, we identified novel high-quality genomes and expanded the existing catalog of bacterial genomes. Video Abstract.

Evolutionary Ecology of Natural Comammox Nitrospira Populations

Microbes commonly exist in diverse and complex communities where species interact, and their genomic repertoires evolve over time. Our understanding of species interaction and evolution has increased during the last decades, but most studies of evolutionary dynamics are based on single species in isolation or in experimental systems composed of few interacting species. Here, we use the microbial ecosystem found in groundwater-fed sand filter as a model to avoid this limitation. In these open systems, diverse microbial communities experience relatively stable conditions, and the coupling between chemical and biological processes is generally well defined. Metagenomic analysis of 12 sand filters communities revealed systematic co-occurrence of at least five comammox Nitrospira species, likely promoted by low ammonium concentrations. These Nitrospira species showed intrapopulation sequence diversity, although possible clonal expansion was detected in a few abundant local comammox populations. Nitrospira species showed low homologous recombination and strong purifying selection, the latter process being especially strong in genes essential in energy metabolism. Positive selection was detected for genes related to resistance to foreign DNA and phages. We found that, compared to other habitats, groundwater-fed sand filters impose strong purifying selection and low recombination on comammox Nitrospira populations. These results suggest that evolutionary processes are more affected by habitat type than by species identity. Together, this study improves our understanding of species interaction and evolution in complex microbial communities and sheds light on the environmental dependency of evolutionary processes. IMPORTANCE Microbial species interact with each other and their environment (ecological processes) and undergo changes in their genomic repertoire over time (evolutionary processes). How these two classes of processes interact is largely unknown, especially for complex communities, as most studies of microbial evolutionary dynamics consider single species in isolation or a few interacting species in simplified experimental systems. In this study, these limitations are circumvented by examining the microbial communities found in stable and well-described groundwater-fed sand filters. Combining metagenomics and strain-level analyses, we identified the microbial interactions and evolutionary processes affecting comammox Nitrospira, a recently discovered bacterial type capable of performing the whole nitrification process. We found that abundant and co-occurrent Nitrospira populations in groundwater-fed sand filters are characterized by low recombination and strong purifying selection. In addition, by comparing these observations with those obtained from Nitrospira species inhabiting other environments, we revealed that evolutionary processes are more affected by habitat type than by species identity.

Computational analyses of bacterial strains from shotgun reads

Shotgun sequencing is routinely employed to study bacteria in microbial communities. With the vast amount of shotgun sequencing reads generated in a metagenomic project, it is crucial to determine the microbial composition at the strain level. This study investigated 20 computational tools that attempt to infer bacterial strain genomes from shotgun reads. For the first time, we discussed the methodology behind these tools. We also systematically evaluated six novel-strain-targeting tools on the same datasets and found that BHap, mixtureS and StrainFinder performed better than other tools. Because the performance of the best tools is still suboptimal, we discussed future directions that may address the limitations.

MetaCRS: unsupervised clustering of contigs with the recursive strategy of reducing metagenomic dataset's complexity

Background

Metagenomics technology can directly extract microbial genetic material from the environmental samples to obtain their sequencing reads, which can be further assembled into contigs through assembly tools. Clustering methods of contigs are subsequently applied to recover complete genomes from environmental samples. The main problems with current clustering methods are that they cannot recover more high-quality genes from complex environments. Firstly, there are multiple strains under the same species, resulting in assembly of chimeras. Secondly, different strains under the same species are difficult to be classified. Thirdly, it is difficult to determine the number of strains during the clustering process.

Results

In view of the shortcomings of current clustering methods, we propose an unsupervised clustering method which can improve the ability to recover genes from complex environments and a new method for selecting the number of sample’s strains in clustering process. The sequence composition characteristics (tetranucleotide frequency) and co-abundance are combined to train the probability model for clustering. A new recursive method that can continuously reduce the complexity of the samples is proposed to improve the ability to recover genes from complex environments. The new clustering method was tested on both simulated and real metagenomic datasets, and compared with five state-of-the-art methods including CONCOCT, Maxbin2.0, MetaBAT, MyCC and COCACOLA. In terms of the number and quality of recovered genes from metagenomic datasets, the results show that our proposed method is more effective.

Conclusions

A new contigs clustering method is proposed, which can recover more high-quality genes from complex environmental samples.