Environmental Sequence Data Research Articles

Exploring Saccharomycotina Yeast Ecology Through an Ecological Ontology Framework.

Yeasts in the subphylum Saccharomycotina are found across the globe in disparate ecosystems. A major aim of yeast research is to understand the diversity and evolution of ecological traits, such as carbon metabolic breadth, insect association, and cactophily. This includes studying aspects of ecological traits like genetic architecture or association with other phenotypic traits. Genomic resources in the Saccharomycotina have grown rapidly. Ecological data, however, are still limited for many species, especially those only known from species descriptions where usually only a limited number of strains are studied. Moreover, ecological information is recorded in natural language format limiting high throughput computational analysis. To address these limitations, we developed an ontological framework for the analysis of yeast ecology. A total of 1,088 yeast strains were added to the Ontology of Yeast Environments (OYE) and analyzed in a machine-learning framework to connect genotype to ecology. This framework is flexible and can be extended to additional isolates, species, or environmental sequencing data. Widespread adoption of OYE would greatly aid the study of macroecology in the Saccharomycotina subphylum.

Ciliate Grazing on the Bloom-Forming Microalga Gonyostomum semen

The freshwater raphidophyte Gonyostomum semen forms extensive summer blooms in northern European humic lakes. The development of these blooms might be facilitated by a lack of natural top-down control, as few zooplankton species are able to prey on these large algal cells (up to 100 μm) that expel trichocysts upon physical stress. In this study, we describe a small ciliate species (< 17 μm) that preys on G. semen by damaging the cell membrane until cytoplasm and organelles spill out. Sequencing of clonal cultures of the ciliate tentatively identified it as the prostomatid species Urotricha pseudofurcata. Grazing experiments illustrated that feeding by U. cf. pseudofurcata can significantly reduce cell concentrations of the microalga. However, differences in cell size and growth rate between two investigated ciliate strains resulted in noticeably different grazing pressure. Environmental sequencing data from five different lakes supported potential interactions between the two species. Urotricha cf. pseudofurcata might, thus, play an important role in aquatic ecosystems that are regularly dominated by G. semen, reducing the abundance of this bloom-forming microalga and enabling transfer of organic carbon to higher trophic levels.

Revision of Seriphium plumosum (Gnaphalieae: Asteraceae) in southern Africa with description of new species in Seriphium

Seriphium plumosum L. from southern Africa has been shown to comprise at least seven distinct species based on analysis of morphological, environmental, and multilocus DNA sequence data. On that evidence, Stoebe burchellii Levyns, Stoebe virgata Thunb., and Stoebe vulgaris Levyns are reinstated in Seriphium, and four new species are described, viz., Seriphium alto-argillaceum Z.Shaik, Se. burrowsii Z.Shaik, Se. crypticum Z.Shaik, and Se. dunensis Z.Shaik. Four of these species are endemic to the Cape Floristic Region of South Africa, and one is so far known from a single high-elevation locality. We present a key to species in the Seriphium plumosum complex, and for each species provide a formal description with accompanying images, typification and synonymy, with distribution maps based on verified field-collected and herbarium specimens.

Pseudovampyrella gen. nov.: A genus of Vampyrella-like protoplast extractors finds its place in the Leptophryidae.

Vampyrellid amoebae are predatory protists, which consume a variety of eukaryotic prey and inhabit freshwater, marine and terrestrial ecosystems. Although they have been known for almost 150 years, much of their diversity lacks an in-depth characterization. To date, environmental sequencing data hint at several uncharacterized lineages, to which no phenotype is associated. Furthermore, there are numerous historically described species without any molecular information. This study reports on two new vampyrellid strains from moorlands, which extract the protoplasts of Closterium species (Zygnematophyceae). Our data on morphology, prey range specificity and feeding strategy reveal that the studied vampyrellids are very similar to the historically described Vampyrella closterii. However, phylogenetic analyses demonstrate that the two strains do not belong to the genus Vampyrella and, instead, form a distinct clade in the family Leptophryidae. Hence, we introduce a new genus of algivorous protoplast extractors, Pseudovampyrella gen. nov., with the species P. closterii (= V. closterii) and P. minor. Our findings indicate that the genetic diversity of morphologically described vampyrellid species might be hugely underrated.

Interpreting phylogenetic placements for taxonomic assignment of environmental DNA.

Taxonomic assignment of operational taxonomic units (OTUs) is an important bioinformatics step in analyzing environmental sequencing data. Pairwise alignment and phylogenetic-placement methods represent two alternative approaches to taxonomic assignments, but their results can differ. Here we used available colpodean ciliate OTUs from forest soils to compare the taxonomic assignments of VSEARCH (which performs pairwise alignments) and EPA-ng (which performs phylogenetic placements). We showed that when there are differences in taxonomic assignments between pairwise alignments and phylogenetic placements at the subtaxon level, there is a low pairwise similarity of the OTUs to the reference database. We then showcase how the output of EPA-ng can be further evaluated using GAPPA to assess the taxonomic assignments when there exist multiple equally likely placements of an OTU, by taking into account the sum over the likelihood weights of the OTU placements within a subtaxon, and the branch distances between equally likely placement locations. We also inferred the evolutionary and ecological characteristics of the colpodean OTUs using their placements within subtaxa. This study demonstrates how to fully analyze the output of EPA-ng, by using GAPPA in conjunction with knowledge of the taxonomic diversity of the clade of interest.

Infection strategies of different chytrids in a diatom spring bloom

Abstract Diatom blooms are often accompanied by an increase in parasitic chytrids that kill the host cells, which they are infecting, and can contribute to the decline of the bloom. However, host specificity and range of these chytrids are currently poorly understood. Low host specificity would enable the parasites to opportunistically infect any diatom species, while specialisation on infecting specific high‐biomass species could result in high prevalence and rapid spread of infection. We investigated such host–parasite interactions by monitoring the diverse diatom spring bloom in lake Erken using amplicon sequencing. We also performed infection experiments with two different, newly isolated chytrid species and several diatom cultures from the bloom. Chytridiomycota displayed the highest relative abundance of all parasitic lineages and were probably physically attached to larger organisms. Since the chytrids reached maximum abundance shortly after a peak in diatom reads, they were probably infecting these important primary producers. Phylogenetic analyses of the isolated chytrid strains identified them as members of the classes Rhizophydiales and Lobulomycetales. The infection experiments revealed high host specificity in these two chytrids targeting different diatom species. The experimental results supported statistical analyses of the environmental sequencing data, which suggested the presence of two different infection strategies: the most abundant chytrid species were specialised on infecting dominant diatom genera (i.e. Stephanodiscus, Aulacoseira, Asterionella), while rarer chytid species infected a range of less abundant diatoms.

Dual memory scale network for multi-step time series forecasting in thermal environment of aquaculture facility: A case study of recirculating aquaculture water temperature

Multi-step time series forecasting is essential in engineering. However, effective time series prediction of the agricultural environment is still a challenge due to the disturbance of external factors and the complexity of temporal patterns. The objective of this work is to provide an intelligent prediction system with field priori-knowledge for aquaculture facility thermal environment. Specifically, we present a novel network framework that considers the spatial correlation of exogenous environmental factors, the short-term and long-term temporal dependence of the sequence, and the spatio-temporal fusion correlation at different times. Among them, the dual-scale memory components focus on long-term seasonal and trend memory patterns as well as short-term fluctuation memory patterns, respectively. Besides, the attention mechanism coordinates the information flow between the long and short memory components. We applied the model to recirculating water temperature forecasting in the aquaponics greenhouse. The empirical results of global and local metrics indicate that our proposed model outperforms benchmark models. The RMSE of the proposed dual memory scale network (DMSNet) is 0.1631, 0.3206, and 0.3761, respectively, in the next 6 h, 12 h, and 24 h water temperature prediction. Ablation study proved that the components of our proposed network could be targeted to extract different information patterns from aquaponics environmental sequence data. Experimental results show that the thermal environment prediction based on DMSNet has higher precision in short-term and long-term forecasting multi-step prediction.

Biosynthesis of Guanitoxin Enables Global Environmental Detection in Freshwater Cyanobacteria.

Harmful cyanobacterial blooms (cyanoHABs) cause recurrent toxic events in global watersheds. Although public health agencies monitor the causal toxins of most cyanoHABs and scientists in the field continue developing precise detection and prediction tools, the potent anticholinesterase neurotoxin, guanitoxin, is not presently environmentally monitored. This is largely due to its incompatibility with widely employed analytical methods and instability in the environment, despite guanitoxin being among the most lethal cyanotoxins. Here, we describe the guanitoxin biosynthesis gene cluster and its rigorously characterized nine-step metabolic pathway from l-arginine in the cyanobacterium Sphaerospermopsis torques-reginae ITEP-024. Through environmental sequencing data sets, guanitoxin (gnt) biosynthetic genes are repeatedly detected and expressed in municipal freshwater bodies that have undergone past toxic events. Knowledge of the genetic basis of guanitoxin biosynthesis now allows for environmental, biosynthetic gene monitoring to establish the global scope of this neurotoxic organophosphate.

SARS-CoV-2 Outbreak among Malayan Tigers and Humans, Tennessee, USA, 2020.

We report an outbreak of severe acute respiratory syndrome coronavirus 2 involving 3 Malayan tigers (Panthera tigris jacksoni) at a zoo in Tennessee, USA. Investigation identified naturally occurring tiger-to-tiger transmission; genetic sequence change occurred with viral passage. We provide epidemiologic, environmental, and genomic sequencing data for animal and human infections.

The wastewater protist Rhogostoma minus (Thecofilosea, Rhizaria) is abundant, widespread, and hosts Legionellales

Wastewater is treated by concerted actions of the microbial communities within bioreactors. Although protists (unicellular eukaryotes) are good bioindicators and important players influencing denitrification, nitrification, and flocculation, they are the least known organisms in WWTPs. The few recent environmental surveys of the protistan diversity in WWTPs show that the most abundant protistan sequences in WWTPs belong to Thecofilosea (Rhizaria). We re-investigated previously published environmental sequencing data and gathered strains from seven WWTPs to determine which species dominate WWTPs worldwide. We found that all highly abundant thecofilosean sequences represent a single species – Rhogostoma minus. Considering that Thecofilosea are frequent hosts for Legionellales, i.e. bacteria linked to waterborne diseases, we confirm that Rhogostoma minus functions as a host for Legionellales in WWTPs. Whether the highly abundant Rhogostoma minus also serves as a host for known human pathogenic Legionellales requires further attention.

Parasitoid chytridiomycete Ericiomyces syringoforeus gen. et sp. nov. has unique cellular structures to infect the host

Many fungi have been identified as pathogens of marine algae. Among them, Chytridiomycota have been revealed as relatively highly abundant, but much of the diversity known within these groups is almost entirely based on environmental sequencing data. Here, we present a novel chytridiomycete genus and species, characterized by light microscopical observations, ultrastructure, and molecular phylogenetic analysis of the parasitic chytrid of brackish-water dinoflagellate Kryptoperidinium foliaceum from the Baltic Sea. Phylogenetic analysis of rDNA sequences and the ultrastructure of the strain reveals that it represents a new family in the order Rhizophydiales. Ericiomyces syringoforeus gen. et sp. nov. is a parasitoid with a life cycle composed by zoospores, which attach to the host, encyst, and produce a rhizoidal system (haustorium). Unlike typical Rhizophydiales chytrids, sporangium develops as a lateral outgrowth of the encysted zoospore. The ultrastructural study revealed at least two unique traits: the syringe-like organelle in the cyst, which supposed to paralyze the host, and funnel-shaped structure anchoring sporangium in the host wall. Sporangium matures and produces new zoospores within 3 days. Multiple infections are common and then the life cycle is 1–2 days shorter compared to the duration when a single infection occurred. Cross-infection experiments showed that E. syringoforeus could only infect dinoflagellates, being K. foliaceum highly susceptible to infection by the chytrid parasitoid. The effects of some fungal epidemics on populations of Kryptoperidinium are discussed.

ResiDB: An automated database manager for sequence data

The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/.

Functional metagenomics of the thioredoxin superfamily

Environmental sequence data of microbial communities now makes up the majority of public genomic information. The assignment of a function to sequences from these metagenomic sources is challenging because organisms associated with the data are often uncharacterized and not cultivable. To overcome these challenges, we created a rationally designed expression library of metagenomic proteins covering the sequence space of the thioredoxin superfamily. This library of 100 individual proteins represents more than 22,000 thioredoxins found in the Global Ocean Sampling data set. We screened this library for the functional rescue of Escherichia coli mutants lacking the thioredoxin-type reductase (ΔtrxA), isomerase (ΔdsbC), or oxidase (ΔdsbA). We were able to assign functions to more than a quarter of our representative proteins. The in vivo function of a given representative could not be predicted by phylogenetic relation but did correlate with the predicted isoelectric surface potential of the protein. Selected proteins were then purified, and we determined their activity using a standard insulin reduction assay and measured their redox potential. An unexpected gel shift of protein E5 during the redox potential determination revealed a redox cycle distinct from that of typical thioredoxin-superfamily oxidoreductases. Instead of the intramolecular disulfide bond formation typical for thioredoxins, this protein forms an intermolecular disulfide between the attacking cysteines of two separate subunits during its catalytic cycle. Our functional metagenomic approach proved not only useful to assign in vivo functions to representatives of thousands of proteins but also uncovered a novel reaction mechanism in a seemingly well-known protein superfamily.

Fig. S1 &amp; Tables S1-S4

Figure S1. Overview map of the biogeographical regions used for Table 1. Biogeographic regions are based on biogeographic realms (https://ecoregions2017.appspot.com/), with three major differences: Western Palearctic (Western part of the Palearctic realm), Asia (Eastern part of the Palearctic realm combined with the Indo-Malay realm), and Australasia (Australasian realm combined with the Oceanian realm). The Palearctic realm was spilt into Western Palearctic and Eastern Palearctic, Eastern Palearctic and the Indo-Malay realm form together the Asia region, and the Australasian realm is combined with the Oceania realm to form the Australasian region.Table S1. List of described Lactifluus species, together with the year of description, taxonomical classification (subgenus, section), the indication of how this taxonomical position was defined, the source(s) of this classification, and notes.Table S2. Extra information on the preliminary study of metabarcoding data of the genus Lactifluus, retrieved from the GlobalFungi website.Table S3. Overview of the results of the preliminary study of metabarcoding data of the genus Lactifluus, retrieved from the GlobalFungi website. Due to the generally shorter length and lower quality of environmental sequence data, the numbers in the table are to be considered an estimate.Table S4. List of the putative new species found in the environmental sequences. References of studies cited are given in S3.

A Need for Improved Cellulase Identification from Metagenomic Sequence Data

Improved sequencing technologies and the maturation of metagenomic approaches allow the identification of gene variants with potential industrial applications, including cellulases. Cellulase identification from metagenomic environmental surveys is complicated by inconsistent nomenclature and multiple categorization systems. Here, we summarize the current classification and nomenclature systems, with recommendations for improvements to these systems. Addressing the issues described will strengthen the annotation of cellulose-active enzymes from environmental sequence data sets-a rapidly growing resource in environmental and applied microbiology.

Naming the untouchable \u2013 environmental sequences and niche partitioning as taxonomical evidence in fungi

ABSTRACTDue to their submerged and cryptic lifestyle, the vast majority of fungal species are difficult to observe and describe morphologically, and many remain known to science only from sequences detected in environmental samples. The lack of practices to delimit and name most fungal species is a staggering limitation to communication and interpretation of ecology and evolution in kingdom Fungi. Here, we use environmental sequence data as taxonomical evidence and combine phylogenetic and ecological data to generate and test species hypotheses in the class Archaeorhizomycetes (Taphrinomycotina, Ascomycota). Based on environmental amplicon sequencing from a well-studied Swedish pine forest podzol soil, we generate 68 distinct species hypotheses of Archaeorhizomycetes, of which two correspond to the only described species in the class. Nine of the species hypotheses represent 78% of the sequenced Archaeorhizomycetes community, and are supported by long read data that form the backbone for delimiting species hypothesis based on phylogenetic branch lengths.Soil fungal communities are shaped by environmental filtering and competitive exclusion so that closely related species are less likely to co-occur in a niche if adaptive traits are evolutionarily conserved. In soil profiles, distinct vertical horizons represent a testable niche dimension, and we found significantly differential distribution across samples for a well-supported pair of sister species hypotheses. Based on the combination of phylogenetic and ecological evidence, we identify two novel species for which we provide molecular diagnostics and propose names. While environmental sequences cannot be automatically translated to species, they can be used to generate phylogenetically distinct species hypotheses that can be further tested using sequences as ecological evidence. We conclude that in the case of abundantly and frequently observed species, environmental sequences can support species recognition in the absences of physical specimens, while rare taxa remain uncaptured at our sampling and sequencing intensity.

What Drives the Diversity of the Most Abundant Terrestrial Cercozoan Family (Rhogostomidae, Cercozoa, Rhizaria)?

Environmental sequencing surveys of soils and freshwaters revealed high abundance and diversity of the Rhogostomidae, a group of omnivorous thecate amoebae. This is puzzling since only a few Rhogostomidae species have yet been described and only a handful of reports mention them in field surveys. We investigated the putative cryptic diversity of the Rhogostomidae by a critical re-evaluation of published environmental sequencing data and in-depth ecological and morphological trait analyses. The Rhogostomidae exhibit an amazing diversity of genetically distinct clades that occur in a variety of different environments. We further broadly sampled for Rhogostomidae species; based on these isolates, we describe eleven new species and highlight important morphological traits for species delimitation. The most important environmental drivers that shape the Rhogostomidae community were soil moisture, soil pH, and total plant biomass. The length/width ratio of the theca was a morphological trait related to the colonized habitats, but not the shape and size of the aperture that is often linked to moisture adaption in testate and thecate amoebae.

Advantages and Limits of Metagenomic Assembly and Binning of a Giant Virus.

Giant viruses have large genomes, often within the size range of cellular organisms. This distinguishes them from most other viruses and demands additional effort for the successful recovery of their genomes from environmental sequence data. Here, we tested the performance of genome-resolved metagenomics on a recently isolated giant virus, Fadolivirus, by spiking it into an environmental sample from which two other giant viruses were isolated. At high spike-in levels, metagenome assembly and binning led to the successful genomic recovery of Fadolivirus from the sample. A complementary survey of the major capsid protein indicated the presence of other giant viruses in the sample matrix but did not detect the two isolated from this sample. Our results indicate that genome-resolved metagenomics is a valid approach for the recovery of near-complete giant virus genomes given that sufficient clonal particles are present. However, our data also underline that a vast majority of giant viruses remain currently undetected, even in an era of terabase-scale metagenomics.IMPORTANCE The discovery of large and giant nucleocytoplasmic large DNA viruses (NCLDV) with genomes in the megabase range and equipped with a wide variety of features typically associated with cellular organisms was one of the most unexpected, intriguing, and spectacular breakthroughs in virology. Recent studies suggest that these viruses are highly abundant in the oceans, freshwater, and soil, impact the biology and ecology of their eukaryotic hosts, and ultimately affect global nutrient cycles. Genome-resolved metagenomics is becoming an increasingly popular tool to assess the diversity and coding potential of giant viruses, but this approach is currently lacking validation.

Supervised machine learning is superior to indicator value inference in monitoring the environmental impacts of salmon aquaculture using eDNA metabarcodes.

Increasing anthropogenic impact and global change effects on natural ecosystems has prompted the development of less expensive and more efficient bioassessments methodologies. One promising approach is the integration of DNA metabarcoding in environmental monitoring. A critical step in this process is the inference of ecological quality (EQ) status from identified molecular bioindicator signatures that mirror environmental classification based on standard macroinvertebrate surveys. The most promising approaches to infer EQ from biotic indices (BI) are supervised machine learning (SML) and the calculation of indicator values (IndVal). In this study we compared the performance of both approaches using DNA metabarcodes of bacteria and ciliates as bioindicators obtained from 152 samples collected from seven Norwegian salmon farms. Results from standard macroinvertebrate-monitoring of the same samples were used as reference to compare the accuracy of both approaches. First, SML outperformed the IndVal approach to infer EQ from eDNA metabarcodes. The Random Forest (RF) algorithm appeared to be less sensitive to noisy data (a typical feature of massive environmental sequence data sets) and uneven data coverage across EQ classes (a typical feature of environmental compliance monitoring scheme) compared to a widely used method to infer IndVals for the calculation of a BI. Second, bacteria allowed for a more accurate EQ assessment than ciliate eDNA metabarcodes. For the implementation of DNA metabarcoding into routine monitoring programmes to assess EQ around salmon aquaculture cages, we therefore recommend bacterial DNA metabarcodes in combination with SML to classify EQ categories based on molecular signatures.

Making sense of environmental sequencing data: Ecologically important functional traits of the protistan groups Cercozoa and Endomyxa (Rhizaria).

We have compiled a database of functional traits for two widespread and ecologically important groups of protists, Cercozoa and Endomyxa (Rhizaria). The functional traits of microorganisms are crucially important for interpreting results from environmental sequencing surveys. Linking morphological and ecological traits to environmental factors is common practice in studies involving micro- and macroorganisms, but is rarely applied to protists. Our database provides functional and ecologically significant traits linked to morphology, nutrition, locomotion and habitats. We discuss how the use of functional traits may help to unveil underlying ecosystem processes. This database is intended as a common reference for the molecular ecology community and will boost the understanding of ecosystem functions, especially those driven by biological interactions.