To initiate or not to initiate: A critical assessment of eIF2A, eIF2D, and MCT-1·DENR to deliver initiator tRNA to ribosomes.

Selection of the correct start codon is critical for high-fidelity protein synthesis. In eukaryotes, this is typically governed by a multitude of initiation factors (eIFs), including eIF2·GTP that directly delivers the initiator tRNA (Met-tRNAi Met ) to the P site of the ribosome. However, numerous reports, some dating back to the early 1970s, have described other initiation factors having high affinity for the initiator tRNA and the ability of delivering it to the ribosome, which has provided a foundation for further work demonstrating non-canonical initiation mechanisms using alternative initiation factors. Here we provide a critical analysis of current understanding of eIF2A, eIF2D, and the MCT-1·DENR dimer, the evidence surrounding their ability to initiate translation, their implications in human disease, and lay out important key questions for the field. This article is categorized under: RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes Translation > Mechanisms Translation > Regulation.

Costs of being a diet generalist for the protist predator Dictyostelium discoideum.

Consumers range from specialists that feed on few resources to generalists that feed on many. Generalism has the clear advantage of having more resources to exploit, but the costs that limit generalism are less clear. We explore two understudied costs of generalism in a generalist amoeba predator, Dictyostelium discoideum, feeding on naturally co-occurring bacterial prey. Both involve costs of combining prey that are suitable on their own. First, amoebas exhibit a reduction in growth rate when they switched to one species of prey bacteria from another compared to controls that experience only the second prey. The effect was consistent across all six tested species of bacteria. These switching costs typically disappear within a day, indicating adjustment to new prey bacteria. This suggests that these costs are physiological. Second, amoebas usually grow more slowly on mixtures of prey bacteria compared to the expectation based on their growth on single prey. There were clear mixing costs in three of the six tested prey mixtures, and none showed significant mixing benefits. These results support the idea that, although amoebas can consume a variety of prey, they must use partially different methods and thus must pay costs to handle multiple prey, either sequentially or simultaneously.

Bioenergetic costs and the evolution of noise regulation by microRNAs.

Noise control, together with other regulatory functions facilitated by microRNAs (miRNAs), is believed to have played important roles in the evolution of multicellular eukaryotic organisms. miRNAs can dampen protein fluctuations via enhanced degradation of messenger RNA (mRNA), but this requires compensation by increased mRNA transcription to maintain the same expression levels. The overall mechanism is metabolically expensive, leading to questions about how it might have evolved in the first place. We develop a stochastic model of miRNA noise regulation, coupled with a detailed analysis of the associated metabolic costs. Additionally, we calculate binding free energies for a range of miRNA seeds, the short sequences which govern target recognition. We argue that natural selection may have fine-tuned the Michaelis-Menten constant [Formula: see text] describing miRNA-mRNA affinity and show supporting evidence from analysis of experimental data. [Formula: see text] is constrained by seed length, and optimal noise control (minimum protein variance at a given energy cost) is achievable for seeds of 6 to 7 nucleotides in length, the most commonly observed types. Moreover, at optimality, the degree of noise reduction approaches the theoretical bound set by the Wiener-Kolmogorov linear filter. The results illustrate how selective pressure toward energy efficiency has potentially shaped a crucial regulatory pathway in eukaryotes.

VIRify: An integrated detection, annotation and taxonomic classification pipeline using virus-specific protein profile hidden Markov models.

The study of viral communities has revealed the enormous diversity and impact these biological entities have on various ecosystems. These observations have sparked widespread interest in developing computational strategies that support the comprehensive characterisation of viral communities based on sequencing data. Here we introduce VIRify, a new computational pipeline designed to provide a user-friendly and accurate functional and taxonomic characterisation of viral communities. VIRify identifies viral contigs and prophages from metagenomic assemblies and annotates them using a collection of viral profile hidden Markov models (HMMs). These include our manually-curated profile HMMs, which serve as specific taxonomic markers for a wide range of prokaryotic and eukaryotic viral taxa and are thus used to reliably classify viral contigs. We tested VIRify on assemblies from two microbial mock communities, a large metagenomics study, and a collection of publicly available viral genomic sequences from the human gut. The results showed that VIRify could identify sequences from both prokaryotic and eukaryotic viruses, and provided taxonomic classifications from the genus to the family rank with an average accuracy of 86.6%. In addition, VIRify allowed the detection and taxonomic classification of a range of prokaryotic and eukaryotic viruses present in 243 marine metagenomic assemblies. Finally, the use of VIRify led to a large expansion in the number of taxonomically classified human gut viral sequences and the improvement of outdated and shallow taxonomic classifications. Overall, we demonstrate that VIRify is a novel and powerful resource that offers an enhanced capability to detect a broad range of viral contigs and taxonomically classify them.

Assessment of Toxoplasma gondii lytic cycle and the impact of a gene deletion using 3D label-free optical diffraction holotomography.

Toxoplasma gondii is a widespread single-celled intracellular eukaryotic apicomplexan protozoan parasite primarily associated with mammalian foetal impairment and miscarriage, including in humans. Is estimated that approximately one third of the human population worldwide is infected by this parasite. Here we used cutting-edge, label-free 3D quantitative optical diffraction holotomography to capture and evaluate the Toxoplasma lytic cycle (invasion, proliferation and egress) in real-time based on the refractive index distribution. In addition, we used this technology to analyse an engineered CRISPR-Cas9 Toxoplasma mutant to reveal differences in cellular physical properties when compared to the parental line. Collectively, these data support the use of holotomography as a powerful tool for the study of protozoan parasites and their interactions with their host cells.

Real-Time PCR Method for Assessment of ParA-Mediated Recombination Efficiency in Minicircle Production.

The in vivo intramolecular recombination of a parental plasmid allows excising prokaryotic backbone from the eukaryotic cassette of interest, leading to the formation of, respectively, a miniplasmid and a minicircle. Here we describe a real-time PCR protocol suitable for the determination of recombination efficiency of parental plasmids with multimer resolution sites (MRS). The protocol was successfully applied to purified DNA samples obtained from E. coli cultures, allowing a more reproducible determination of recombination efficiency than densitometry analysis of agarose gels.

Sex Without Sexes: Can the Cost of Finding a Mate Explain Diversity in Fungal Mating Systems?

Eukaryotes have evolved myriad ways of uniting gametes during sexual reproduction. A repeated pattern is the convergent evolution of a mating system with the fusion of larger gametes with smaller gametes (anisogamy) from that of fusion between morphologically identical gametes (isogamy). In anisogamous species, sexes are defined as individuals that produce only one gamete type. Although sexes abound throughout Eukarya, in fungi there are no biological sexes, because even in anisogamous species, individuals are hermaphroditic and produce both gamete types. For this reason, the term mating types is preferred over sexes, and, thus defined, only individuals of differing mating types can mate (homoallelic incompatibility). In anisogamous fungal species, there is scant evidence that there are more than two mating types, and this may be linked to genetic constraints, such as the use of mating types to determine the inheritance of cytoplasmic genomes. However, the mushroom fungi (Agaricomycetes) stand out as having both large numbers of mating types within a species, which will allow nearly all individuals to be compatible with each other, and reciprocal exchange of nuclei during mating, which will avoid cytoplasmic mixing and cyto-nuclear conflicts. Although the limitation of mating types to two in most fungi is consistent with the cyto-nuclear conflicts model, there are many facets of the Agaricomycete life cycle that also suggest they will demand a high outbreeding efficiency. Specifically, they are mostly obligately sexual and outcrossing, inhabit complex competitive niches, and display broadcast spore dispersal. Subsequently, the Agaricomycete individual pays a high cost to being choosy when encountering a mate. Here, I discuss the costs of mate finding and choice and demonstrate how most fungi have multiple ways of reducing these costs, which can explain why mating types are mostly limited to two per species. Nevertheless, it is perplexing that fungi have not evolved multiple mating types on more occasions nor evolved sexes. The few exceptions to these rules suggest that it is dictated by both molecular and evolutionary constraints.

Critical assessment of DNA adenine methylation in eukaryotes using quantitative deconvolution.

The discovery of N6-methyldeoxyadenine (6mA) across eukaryotes led to a search for additional epigenetic mechanisms. However, some studies have highlighted confounding factors that challenge the prevalence of 6mA in eukaryotes. We developed a metagenomic method to quantitatively deconvolve 6mA events from a genomic DNA sample into species of interest, genomic regions, and sources of contamination. Applying this method, we observed high-resolution 6mA deposition in two protozoa. We found that commensal or soil bacteria explained the vast majority of 6mA in insect and plant samples. We found no evidence of high abundance of 6mA in Drosophila, Arabidopsis, or humans. Plasmids used for genetic manipulation, even those from Dam methyltransferase mutant Escherichia coli, could carry abundant 6mA, confounding the evaluation of candidate 6mA methyltransferases and demethylases. On the basis of this work, we advocate for a reassessment of 6mA in eukaryotes.

Critical assessment of computational tools for prokaryotic and eukaryotic promoter prediction.

Promoters are crucial regulatory DNA regions for gene transcriptional activation. Rapid advances in next-generation sequencing technologies have accelerated the accumulation of genome sequences, providing increased training data to inform computational approaches for both prokaryotic and eukaryotic promoter prediction. However, it remains a significant challenge to accurately identify species-specific promoter sequences using computational approaches. To advance computational support for promoter prediction, in this study, we curated 58 comprehensive, up-to-date, benchmark datasets for 7 different species (i.e. Escherichia coli, Bacillus subtilis, Homo sapiens, Mus musculus, Arabidopsis thaliana, Zea mays and Drosophila melanogaster) to assist the research community to assess the relative functionality of alternative approaches and support future research on both prokaryotic and eukaryotic promoters. We revisited 106 predictors published since 2000 for promoter identification (40 for prokaryotic promoter, 61 for eukaryotic promoter, and 5 for both). We systematically evaluated their training datasets, computational methodologies, calculated features, performance and software usability. On the basis of these benchmark datasets, we benchmarked 19 predictors with functioning webservers/local tools and assessed their prediction performance. We found that deep learning and traditional machine learning-based approaches generally outperformed scoring function-based approaches. Taken together, the curated benchmark dataset repository and the benchmarking analysis in this study serve to inform the design and implementation of computational approaches for promoter prediction and facilitate more rigorous comparison of new techniques in the future.

Effectiveness assessment of using riverine water eDNA to simultaneously monitor the riverine and riparian biodiversity information.

Both aquatic and terrestrial biodiversity information can be detected in riverine water environmental DNA (eDNA). However, the effectiveness of using riverine water eDNA to simultaneously monitor the riverine and terrestrial biodiversity information remains unidentified. Here, we proposed that the monitoring effectiveness could be approximated by the transportation effectiveness of land-to-river and upstream-to-downstream biodiversity information flows and described by three new indicators. Subsequently, we conducted a case study in a watershed on the Qinghai-Tibet Plateau. The results demonstrated that there was higher monitoring effectiveness on summer or autumn rainy days than in other seasons and weather conditions. The monitoring of the bacterial biodiversity information was more efficient than the monitoring of the eukaryotic biodiversity information. On summer rainy days, 43-76% of species information in riparian sites could be detected in adjacent riverine water eDNA samples, 92-99% of species information in riverine sites could be detected in a 1-km downstream eDNA sample, and half of dead bioinformation (the bioinformation labeling the biological material that lacked life activity and fertility) could be monitored 4-6 km downstream for eukaryotes and 13-19 km downstream for bacteria. The current study provided reference method and data for future monitoring projects design and for future monitoring results evaluation.

Assessment of current taxonomic assignment strategies for metabarcoding eukaryotes.

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to genus or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging as researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities by using COI barcode fragments. The mock communities varied in species number and specimen abundance, while upstream molecular and bioinformatic variables were held constant, and using a set of COI fragments. We evaluated the impact of parameter optimization on the quality of the predictions. Our results indicate that BLAST top hit competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts (query compositional heterogeneity) which ultimately influence the selection of appropriate software. We urge researchers to: (i) use realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method employed; (ii) carefully choose and curate the reference databases including completeness; and (iii) use QIIME, BLAST or LCA methods, in conjunction with parameter tuning to better assign taxonomy to diverse communities, especially when information on species diversity is lacking for the area under study.

Genotype by sequencing: An alternative new method to amplicon metabarcoding and shotgun metagenomics for the assessment of eukaryote biodiversity.

The use of high-throughput DNA sequencing (HTS) has revolutionized the assessment of biodiversity in plant and animal communities. There are two main approaches to estimate the identity and the relative species abundance (RSA) in complex mixtures using HTS: amplicon metabarcoding and shotgun metagenomics. While amplicon metabarcoding targets one or a few genomic regions, shotgun metagenomics randomly explores the genome of the species. In this issue of Molecular Ecology Resources, Wagemaker et al. (2021) present a new method, multi-species Genotyping by Sequencing (msGBS), as an alternative middle ground between metabarcoding and metagenomics. They apply the technique to mixtures of plant roots and report the remarkable capacity of msGBS to estimate the RSA. If validated in other laboratories and biological communities, msGBS might become a third method to explore the biodiversity of biological communities, especially of plants, where current techniques are struggling to get sufficient taxonomic resolution.

Assessment of microbial plankton diversity as an ecological indicator in the NW Mediterranean coast.

High-throughput sequencing of microbial assemblages has been proposed as an alternative methodology to the traditional ones used in marine monitoring and environmental assessment. Here, we evaluated pico- and nanoplankton diversity as ecological indicators in NW Mediterranean coastal waters by comparing their diversity in samples subjected to varying degrees of continental pressures. Using metabarcoding of the 16S and 18S rRNA genes, we explored whether alphadiversity indices, abundance of Operational Taxonomic Units and taxonomic groups (and their ratios) provide information on the ecological quality of coastal waters. Our results revealed that only eukaryotic diversity metrics and a limited number of prokaryotic and eukaryotic taxa displayed potential in assessing continental influences in our surveyed area, resulting thus in a restrained potential of microbial plankton diversity as an ecological indicator. Therefore, incorporating microbial plankton diversity in environmental assessment could not always result in a significant improvement of current marine monitoring strategies.

Chromatin as a key consumer in the metabolite economy.

In eukaryotes, chromatin remodeling and post-translational modifications (PTMs) shape the local chromatin landscape to establish permissive and repressive regions within the genome, orchestrating transcription, replication, and DNA repair in concert with other epigenetic mechanisms. Though cellular nutrient signaling encompasses a huge number of pathways, recent attention has turned to the hypothesis that the metabolic state of the cell is communicated to the genome through the type and concentration of metabolites in the nucleus that are cofactors for chromatin-modifying enzymes. Importantly, both epigenetic and metabolic dysregulation are hallmarks of a range of diseases, and this metabolism-chromatin axis may yield a well of new therapeutic targets. In this Perspective, we highlight emerging themes in the inter-regulation of the genome and metabolism via chromatin, including nonenzymatic histone modifications arising from chemically reactive metabolites, the expansion of PTM diversity from cofactor-promiscuous chromatin-modifying enzymes, and evidence for the existence and importance of subnucleocytoplasmic metabolite pools.

The C- and G-value paradox with polyploidy, repeatomes, introns, phenomes and cell economy.

BACKGROUND: The apparent disconnection between biological complexity and both genome size (C-value) and gene number (G-value) is one of the long-standing biological puzzles. Gene-dense genomic sequences in prokaryotes or simple eukaryotes are highly constrained during selection, whereas gene-sparse genomic sequences in higher eukaryotes have low selection constraints. This review discusses the correlations of the C-value and G-value with genome architecture, polyploidy, repeatomes, introns, cell economy and phenomes. DISCUSSION: Eukaryotic chromosomes carry an assortment of various repeated DNA sequences (repeatomes). Expansion of copies of repeatomes together with polyploidization or whole-genome duplication (WGD) are major players in genome size (C-value) bloating, but genomes are equipped with counterbalancing systems such as diploidization, illegitimate recombination, and nonhomologous end joining (NHEJ) after double-strand breaks (DSBs). The lack of these efficient purging systems allowed the accumulation of repeat DNA, which resulted in extremely large genomes in several species. However, the correlation between chromosome number and genome size is not clear due to inconsistent results with different sets of species. Positive correlations between genome size and intron size and density were reported in early studies, but these proposals were refuted by the results with increased numbers of species, in which genome-wide features of introns (size, density, gene contents, repeats) were weakly associated with genome size. The assumption of the correlations between C-value and gene number (G-value) and organismal complexity is acceptable in general, but this assumption is often violated in specific lineages or species, suggesting C- and G-value paradoxes. The C-value paradox is partly explained by noncoding repeatomes. The G-value paradox can also be explained by several genomic features: (1) one gene can produce many mature mRNAs by alternative splicing, and eukaryotic gene expression is highly regulated at both the transcriptional and translational levels; (2) many proteins exert multiple functions during development; (3) gene expansion/contraction are frequent events in the gene family among evolutionarily close species; and (4) sets of homeotic genes regulate development such that organismal complexity is sometimes not clear among organisms. A large genome must be burdensome in terms of cell economy, such that a large genome constraint results in the distribution of genome sizes skewed to small genomes. Moreover, the C-value can affect the phenome. A strong positive correlation has been recognized between genome size and cell size, but the relationship is weak or null with higher-level traits. Additional analyses of the relationship between the C-value and phenome should be carried out, because natural selection acts on the phenotype rather than the genotype. CONCLUSIONS: Dramatic advancement in genomics has given some answers to the C-value and G-value paradoxes. We know the mechanisms by which the current genomes have been constructed. However, basic questions have not yet been fully resolved. Why have some species retained small genomes yet some closely related species have large genomes? Random genetic drift and mutational pressure might have affected for genome size in the limited population size during evolution; thus, genome size may be quasiadaptable rather than the best adaptive trait.

A metagenomic assessment of microbial eukaryotic diversity in the global ocean.

Surveying microbial diversity and function is accomplished by combining complementary molecular tools. Among them, metagenomics is a PCR free approach that contains all genetic information from microbial assemblages and is today performed at a relatively large scale and reasonable cost, mostly based on very short reads. Here, we investigated the potential of metagenomics to provide taxonomic reports of marine microbial eukaryotes. We prepared a curated database with reference sequences of the V4 region of 18S rDNA clustered at 97% similarity and used this database to extract and classify metagenomic reads. More than half of them were unambiguously affiliated to a unique reference whilst the rest could be assigned to a given taxonomic group. The overall diversity reported by metagenomics was similar to that obtained by amplicon sequencing of the V4 and V9 regions of the 18S rRNA gene, although either one or both of these amplicon surveys performed poorly for groups like Excavata, Amoebozoa, Fungi and Haptophyta. We then studied the diversity of picoeukaryotes and nanoeukaryotes using 91 metagenomes from surface down to bathypelagic layers in different oceans, unveiling a clear taxonomic separation between size fractions and depth layers. Finally, we retrieved long rDNA sequences from assembled metagenomes that improved phylogenetic reconstructions of particular groups. Overall, this study shows metagenomics as an excellent resource for taxonomic exploration of marine microbial eukaryotes.

Assessment of prokaryote to eukaryote ratios in environmental samples by SSU rDNA length polymorphism.

Microbial communities are important regulators of many processes in all ecosystems. Understanding of ecosystem processes requires at least an overview of the involved microorganisms. While in-depth identification of microbial species in environmental samples can be achieved by next generation sequencing, profiling of whole microbial communities can be accomplished via less labour-intensive approaches. Especially automated ribosomal intergenic spacer analysis (ARISA) are of interest as they are highly specific even at fine scales and widely applicable for environmental samples. Yet, established protocols lack the possibility to compare prokaryotic and eukaryotic communities as different primer sets are necessary. However, shifts in the eukaryote to prokaryote ratio can be a useful indicator for ecosystem processes like decomposition or nutrient cycling. We propose a protocol to analyse prokaryotic and eukaryotic communities using a single primer pair based reaction based on a region with variable length (V4, which is about 180 bp shorter in prokaryotes compared to eukaryotes) in the small ribosomal subunit flanked by two highly conservative regions. Shifts in the prokaryotic and eukaryotic ratio between samples can be reliably detected by fragment length polymorphism analysis as well as sequencing of this region. Together with established approaches such as ARISA or 16S and ITS rDNA sequencing, this can provide a more complex insight into microbial community shifts and ecosystem processes.

Look4TRs: a de novo tool for detecting simple tandem repeats using self-supervised hidden Markov models.

MOTIVATION: Simple tandem repeats, microsatellites in particular, have regulatory functions, links to several diseases and applications in biotechnology. There is an immediate need for an accurate tool for detecting microsatellites in newly sequenced genomes. The current available tools are either sensitive or specific but not both; some tools require adjusting parameters manually. RESULTS: We propose Look4TRs, the first application of self-supervised hidden Markov models to discovering microsatellites. Look4TRs adapts itself to the input genomes, balancing high sensitivity and low false positive rate. It auto-calibrates itself. We evaluated Look4TRs on 26 eukaryotic genomes. Based on F measure, which combines sensitivity and false positive rate, Look4TRs outperformed TRF and MISA-the most widely used tools-by 78 and 84%. Look4TRs outperformed the second and the third best tools, MsDetector and Tantan, by 17 and 34%. On eight bacterial genomes, Look4TRs outperformed the second and the third best tools by 27 and 137%. AVAILABILITY AND IMPLEMENTATION: https://github.com/TulsaBioinformaticsToolsmith/Look4TRs. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Metabarcoding assessment of prokaryotic and eukaryotic taxa in sediments from Stellwagen Bank National Marine Sanctuary.

Stellwagen Bank National Marine Sanctuary (SBNMS) in the Gulf of Maine is a historic fishing ground renowned for remarkable productivity. Biodiversity conservation is a key management priority for SBNMS and yet data on the diversity of microorganisms, both prokaryotic and eukaryotic, is lacking. This study utilized next generation sequencing to characterize sedimentary communities within SBNMS at three sites over two seasons. Targeting 16S and 18S small subunit (SSU) rRNA genes and fungal Internal Transcribed Spacer (ITS) rDNA sequences, samples contained high diversity at all taxonomic levels and identified 127 phyla, including 115 not previously represented in the SBNMS Management Plan and Environmental Assessment. A majority of the diversity was bacterial, with 59 phyla, but also represented were nine Archaea, 18 Animalia, 14 Chromista, eight Protozoa, two Plantae, and 17 Fungi phyla. Samples from different sites and seasons were dominated by the same high abundance organisms but displayed considerable variation in rare taxa. The levels of biodiversity seen on this small spatial scale suggest that benthic communities of this area support a diverse array of micro- and macro-organisms, and provide a baseline for future studies to assess changes in community structure in response to rapid warming in the Gulf of Maine.

IT'S 2 for the price of 1: Multifaceted ITS2 processing machines in RNA and DNA maintenance.

Cells utilize sophisticated RNA processing machines to ensure the quality of RNA. Many RNA processing machines have been further implicated in regulating the DNA damage response signifying a strong link between RNA processing and genome maintenance. One of the most intricate and highly regulated RNA processing pathways is the processing of the precursor ribosomal RNA (pre-rRNA), which is paramount for the production of ribosomes. Removal of the Internal Transcribed Spacer 2 (ITS2), located between the 5.8S and 25S rRNA, is one of the most complex steps of ribosome assembly. Processing of the ITS2 is initiated by the newly discovered endoribonuclease Las1, which cleaves at the C2 site within the ITS2, generating products that are further processed by the polynucleotide kinase Grc3, the 5'→3' exonuclease Rat1, and the 3'→5' RNA exosome complex. In addition to their defined roles in ITS2 processing, these critical cellular machines participate in other stages of ribosome assembly, turnover of numerous cellular RNAs, and genome maintenance. Here we summarize recent work defining the molecular mechanisms of ITS2 processing by these essential RNA processing machines and highlight their emerging roles in transcription termination, heterochromatin function, telomere maintenance, and DNA repair.