Biology subjects

Iwasaki, W.

Publications and source records attributed to Iwasaki, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Genomic, spatial, and evolutionary insights into a dominant Mycoplasmatota symbiont colonizing the body wall of deep-sea holothurians

Subcuticular bacteria (SCB) are widespread symbionts of echinoderms and often dominate the body-wall microbiome, suggesting important roles in host physiology. However, their diversity, metabolic properties, and host associations remain poorly characterized. Here, we report a novel dominant SCB lineage associated with deep-sea holothurians, Scotoplanes spp. collected from the Northwest Pacific. We recovered two high-quality genomes, including a 649-kb complete circular genome, and propose a new genus and species, "Candidatus Abyssoplasma scotoplanesicola", within Mycoplasmatota. The two genomes showed a highly reduced metabolic repertoire, lacking central pathways including glycolysis. In contrast, acidic cell-surface-associated proteins, including large proteins exceeding 5,000 amino acids, accounted for 27.6% of the complete genome and clustered near defense islands. Localized genome plasticity in these regions, revealed by comparison between the two closely related genomes, suggests a possible mechanism for diversification of cell-surface proteins at the host-symbiont interface. "Candidatus Abyssoplasma scotoplanesicola" occupied 76.4-98.9% of the body-wall microbiome of the Scotoplanes specimens. Fluorescence in situ hybridization analysis confirmed that these bacteria formed aggregates on the epidermal side of the body wall. Overall, this study provides genome-and spatially resolved views of dominant SCB in holothurians and offers evolutionary insights into host-interface diversification in the deep-sea holothurian body wall.

microbiology↗

bioRxiv2025

MitoNGS: an online platform to analyze fish metabarcoding data in high-resolution

Environmental DNA (eDNA) metabarcoding has become a powerful tool for assessing fish biodiversity in aquatic ecosystems. However, accurate species-level identification remains challenging due to incomplete and contaminated reference databases, as well as ambiguous taxa sharing identical barcode sequences. Here, we present MitoNGS, a next-generation platform that succeeds the widely used MiFish pipeline, designed for high-resolution analysis of fish metabarcoding data. MitoNGS addresses these challenges by incorporating more comprehensive references including non-fish species and detailed annotations of heterospecific regions. Additionally, it introduces the "species group" strategy in conjunction with environmental habitat and geographic occurrence data to resolve ambiguous taxa. Furthermore, MitoNGS expands the functionalities of the legacy MiFish pipeline. It can analyze data from any mitochondrial markers and from Nanopore sequencing platforms. MitoNGS demonstrated excellent performance on our testing datasets from diverse locations, markers and sequencing platforms. MitoNGS offers a user-friendly, web-based solution for fish detection, biodiversity monitoring, conservation research, and bioresource management. MitoNGS is freely available via https://mitofish.aori.u-tokyo.ac.jp/mito-ngs.

bioinformatics↗

bioRxiv2025

Globally unified analysis of riverine eDNA reveals common associations of fish biodiversity with drainage characteristics

Freshwater biodiversity is declining at a pace that outstrips the capacity of existing monitoring approaches both in temporal and spatial dimensions, highlighting the urgent need for rapid and scalable assessment and attribution of biodiversity states and changes. Here, we present one of the first global assessments and unified analyses of riverine fish biodiversity using environmental DNA (eDNA) collected from 1818 sites across 113 river systems. We quantified species richness, functional redundancy, phylogenetic diversity, and genetic sequence diversity, and related them to drainage characteristics. Our results showed that eDNA effectively captured global patterns of multi-faceted riverine fish biodiversity and disentangled the roles of climate and human activities in shaping biodiversity-area relationships. Catchments in warmer climates consistently enhanced biodiversity accumulation with area, while higher human activity intensity weakened this scaling. Species richness, functional, and genetic sequence diversity exhibited stronger negative responses to human activities in larger catchments. In contrast, phylogenetic diversity showed the strongest negative effects in smaller catchments with these impacts diminishing as catchment area increased, highlighting the facet-dependent nature of biodiversity responses to environmental gradients. Our findings demonstrate the power of eDNA-based datasets for harmonized, multi-faceted biodiversity assessments, offering a scalable approach for detecting and attributing biodiversity change and informing conservation strategies under accelerating global change.

ecology↗

bioRxiv2025

Integrated reanalysis of global riverine fish eDNA datasets shows robustness and congruence of biodiversity conclusions

The analysis of environmental DNA (eDNA) has revolutionized biodiversity assessments in aquatic ecosystems, enabling non-invasive monitoring of fish communities across diverse regions. However, the global comparability of these eDNA datasets remains ambiguous due heterogeneous sampling protocols and bioinformatic workflows across studies, particularly regarding the robustness of their conclusions on biodiversity assessments. Here, we conducted a meta-analysis of 58 riverine fish eDNA metabarcoding datasets, covering 1,818 sampling sites worldwide, to evaluate the robustness of eDNA-derived biodiversity patterns. We found that species richness estimates and metrics of community structure derived under a common bioinformatic workflow were overall consistent with those of original analyses, despite the relatively high variability in bioinformatic analyses in the respective original studies. Contrastingly, congruence of species identity varied more extensively across datasets, mostly reflecting different completeness and regional relevance of reference databases. Restricting taxonomic assignment to basin-specific species pools improved species identification accuracy, while datasets lacking publicly accessible or well-curated reference data were more prone to mismatches. Year of sampling had a positive effect on taxonomic congruence, such that more recent studies showed increased robustness, also reflecting improved reference database coverage and enhanced species-level identification over time and overall method congruence in more recent years. Overall, the suitability and potential of eDNA for global biodiversity monitoring is corroborating overall robust biodiversity estimates, irrespective of the bioinformatic approaches. Our study underlines the effectiveness and need of further harmonization of bioinformatic workflows and strengthened region-specific reference databases for improved taxonomic resolution and comparability across studies.

ecology↗

bioRxiv2025

Genomic and evolutionary factors influencing the prediction accuracy of optimal growth temperature in prokaryotes

Bacteria and archaea have evolved diverse genomic adaptations to thrive across various temperatures. These adaptations include genome sequence optimizations, such as increased GC content in rRNA and tRNA, shifts in codon and amino acids usage, and the acquisition of functional genes conferring adaptation for specific temperatures. Since the experimental determination of optimal growth temperatures (OGT) is only possible for cultured species, predicting OGT from genomic information has become increasingly important given the exponential increase in genomic data. Although previous studies developed prediction models integrating multiple features based on genome composition using machine learning, the accuracy was variable depending on the target species, with models performing well for thermophiles but less accurately for psychrophiles. In this study, we curated the OGT and genomic data of 2,869 bacterial species to develop a novel prediction model incorporating features reflecting genomic adaptation toward lower temperatures. We found that species with rapid OGT shifts from their ancestors, including psychrophiles, showed less accuracy in genome composition-based models. Incorporating the gene presence/absence information associated with the rapid changes in OGT improved the prediction accuracy for psychrophiles. We also observed that OGT in archaea is phylogenetically more conserved than in bacteria, which may lead to the long-term optimization of the genome composition and explain high predictability of OGT in archaea. These findings highlight the importance of integrating long- and short-term evolutionary adaptations for phenotype prediction models.

genomics↗

bioRxiv2025

Bioinformatics classification of the MgtE Mg2+ channel and de novo protein design for the stabilization of its novel subclass

MgtE channels play crucial roles in Mg{superscript 2} homeostasis and are implicated in bacterial survival under antibiotic exposure. Previous structural and biophysical studies have predominantly focused on the Thermus thermophilus MgtE, leaving the structural and mechanistic diversity of MgtE family proteins largely unexplored. In this study, using a genome mining approach, we identified diverse MgtE homologs, including a novel subclass termed the "mini-N type," which lacks the canonical cytoplasmic N and CBS domains but possesses a unique small N-like domain. Despite extensive expression screening, mini-N type homologs could not be stably purified. To address this issue, we designed a series of de novo proteins and determined their crystal structures. A selected de novo protein was fused to a mini-N type MgtE, enabling successful purification and preliminary cryo-EM imaging. Our findings demonstrate that de novo designed protein fusions can serve as powerful tools for stabilizing and purifying otherwise unstable membrane proteins, opening new avenues for the structural and functional studies of otherwise inaccessible membrane proteins.

biophysics↗

bioRxiv2025

CORGIAS: identifying correlated gene pairs by considering evolutionary history in a large-scale prokaryotic genome dataset

The recent expansion of prokaryotic genomes reveals many ortholog groups (OGs) whose function cannot be inferred from conventional, sequence similarity-based annotation methods, especially in metagenome-assembled genomes. Phylogenetic profiling is one of the promising methods to annotate these OGs, by identifying functional relationships of OGs using co- or anti-occurrence of OGs distributions, not sequence similarity. Here, we proposed two new phylogenetic methods for large-scale data, Ancestral State Adjustment (ASA) and Simultaneous EVolution test (SEV), which consider the ancestral state of gene presence/absence. In evaluations using three distinct prokaryotic datasets, ASA and SEV showed better or comparable performance to both established and recently proposed methods for large-scale data. We compared the functionally related genes detected by each method and found that SEV and its predecessor can identify slowly evolving genes, such as housekeeping genes. In contrast, ASA and its predecessors can detect functionally related genes that tend to be gained or lost in a fixed-order, indicating a strong evolutionary constraint that provides clues for functional prediction. Using matrix multiplication, we showed that SEV is scalable in the latest genome databases.

bioinformatics↗

bioRxiv2025

Repeatability of protein structural evolution following convergent gene fusions

Convergent evolution of proteins provides insights into repeatability of genetic adaptation. While local convergence of proteins at residue or domain level has been characterized, global structural convergence by inter-domain/molecular interactions remains largely unknown. Here we present structural convergent evolution on fusion enzymes of aldehyde dehydrogenases (ALDHs) and alcohol dehydrogenases (ADHs). We discovered BdhE (bifunctional dehydrogenase E), an enzyme clade that emerged independently from the previously known AdhE family through distinct gene fusion events. AdhE and BdhE showed shared enzymatic activities and non-overlapping phylogenetic distribution, suggesting common functions in different species. Cryo-electron microscopy revealed BdhEs form donut-like homotetramers, contrasting AdhEs helical homopolymers. Intriguingly, despite distinct quaternary structures and >70% unshared amino acids, both enzymes form resembled dimeric structure units by ALDH-ADH interactions via convergently elongated loop structures. These findings suggest convergent gene fusions recurrently led to substrate channeling evolution to enhance two-step reaction efficiency. Our study unveils structural convergence at inter-domain/molecular level, expanding our knowledges on patterns behind molecular evolution exploring protein structural universe.

evolutionary biology↗

bioRxiv2024

CoLaML: Inferring latent evolutionary modes from heterogeneous gene content

MotivationEstimating the history of gene content evolution provides insights into genome evolution on a macroevolutionary timescale. Previous models did not consider heterogeneity in evolutionary patterns among gene families across different periods and/or clades. ResultsWe introduce CoLaML (joint inference of gene COntent evolution and its LA-tent modes using Maximum Likelihood), which considers heterogeneity using a Markov-modulated Markov chain. This model assumes that internal states determine evolutionary patterns (i.e., latent evolutionary modes) and attributes heterogeneity to their switchover during the evolutionary timeline. We developed a practical algorithm for model inference and validated its performance through simulations. CoLaML outperformed previous models in fitting empirical datasets and estimated plausible evolutionary histories, capturing heterogeneity among clades and gene families without prior knowledge. AvailabilityCoLaML is freely available at https://github.com/mtnouchi/colaml. Contactyamanouchi@bs.s.u-tokyo.ac.jp

bioinformatics↗

bioRxiv2024

Cooperation shapes bacterial niche breadth evolution and patterns of diversification

Bacteria exhibit varying niche breadths, with generalists thriving in diverse environments and specialists confined to specific habitats. This variability reflects the adaptability of bacteria to their environment and may influence their speciation and extinction rates. We used phylogenetic causal inference and diversification analysis techniques to investigate the influence of cooperation on bacterial niche breadth evolution and patterns of diversification across 25,785 species. We found: (1) a positive correlation between the proportion of genes for cooperation and niche breadth; (2) a decreased proportion of genes for cooperation promotes niche contraction; and (3) species with a higher proportion of genes for cooperation show increased speciation and extinction rates when their niche breadths are narrower. Our study highlights the role of genes for cooperation in shaping both niche breadth and diversification of bacteria, underscoring their critical function in maintaining the ecological versatility and diversity of bacteria.

evolutionary biology↗

bioRxiv2023

Cell surface architecture of the cultivated DPANN archaeon Nanobdella aerobiophila

The DPANN archaeal clade includes obligately ectosymbiotic species. Their cell surfaces potentially play an important role in the symbiotic interaction between the ectosymbionts and their hosts. However, little is known about the mechanism of the ectosymbiosis. Here, we show cell surface structures of the cultivated DPANN archaeon Nanobdella aerobiophila strain MJ1T and its host Metallosphaera sedula strain MJ1HA, using a variety of electron microscopy techniques, i.e., negative-staining transmission electron microscopy (TEM), quick-freeze deep-etch (QFDE) TEM, and 3D electron tomography. The thickness, unit size, and lattice symmetry of the S-layer of strain MJ1T were different from those of the host archaeon strain MJ1HA. Genomic and transcriptomic analyses highlighted the most highly expressed MJ1T gene for a putative S-layer protein with multiple glycosylation sites and immunoglobulin-like folds, which has no sequence homology to known S-layer proteins. In addition, genes for putative pectin lyase- or lectin-like extracellular proteins, which are potentially involved in symbiotic interaction, were found in the MJ1T genome based on in silico 3D protein structure prediction. Live cell imaging at the optimum growth temperature of 65{degrees}C indicated that cell complexes of strains MJ1T and MJ1HA were motile, but sole MJ1T cells were not. Taken together, we propose a model of the symbiotic interaction and cell cycle of Nanobdella aerobiophila. ImportanceDPANN archaea are widely distributed in a variety of natural and artificial environments, and may play a considerable role in the microbial ecosystem. All of the cultivated DPANN archaea so far need host organisms for their growth, i.e., obligately ectosymbiotic. However, the mechanism of the ectosymbiosis by DPANN archaea is largely unknown. To this end, we performed a comprehensive analysis of the cultivated DPANN archaeon, Nanobdella aerobiophila, using electron microscopy, live cell imaging, transcriptomics, and genomics including 3D protein structure prediction. Based on the results, we propose a reasonable model of the symbiotic interaction and cell cycle of Nanobdella aerobiophila, which will enhance our understanding of the enigmatic physiology and ecological significance of DPANN archaea.

microbiology↗

bioRxiv2023

SonicParanoid2: fast, accurate, and comprehensive orthology inference with machine learning and language models

Accurate inference of orthologous genes constitutes a prerequisite for comparative and evolutionary genomics. SonicParanoid is one of the fastest tools for orthology inference; however, its scalability and accuracy have been hampered by time-consuming all-versus-all alignments and the existence of proteins with complex domain architectures. Here, we present a substantial update of Sonicparanoid, where a gradient boosting predictor halves the execution time and a language model doubles the recall. Application to empirical large-scale and standardized benchmark datasets showed that SonicParanoid2 is up to 18X faster than comparable methods and also the most accurate. SonicParanoid2 is available at https://gitlab.com/salvo981/sonicparanoid2

evolutionary biology↗

bioRxiv2023

Probe capture enrichment sequencing of amoA genes discloses diverse ammonia-oxidizing archaeal and bacterial populations

The ammonia monooxygenase subunit A (amoA) gene has been used to investigate the phylogenetic diversity, spatial distribution, and activity of ammonia-oxidizing archaeal (AOA) and bacterial (AOB), which contribute significantly to the nitrogen cycle in various ecosystems. Amplicon sequencing of amoA is a widely used method; however, it produces inaccurate results owing to the lack of a universal primer set. Moreover, currently available primer sets suffer from amplification biases, which can lead to severe misinterpretation. Although shotgun metagenomic and metatranscriptomic analyses are alternative approaches without amplification bias, the low concentration of target genes in heterogeneous environmental DNA restricts a comprehensive analysis to a realizable sequencing depth. In this study, we developed a method for amoA enrichment sequencing using a hybridization capture technique. Using metagenomic mock community samples, our approach effectively enriched amoA genes with low compositional changes, outperforming amplification and meta-omics sequencing analyses. Following the analysis of metatranscriptomic marine samples, we predicted 80 operational taxonomic units (OTUs) assigned to either AOA or AOB, of which 30 OTUs were unidentified using simple metatranscriptomic or amoA gene amplicon sequencing. Mapped read ratios to all the detected OTUs were significantly higher for the capture samples (50.4 {+/-} 27.2%) than for non-capture samples (0.05 {+/-} 0.02%), demonstrating the high enrichment efficiency of the method. The analysis also revealed the spatial diversity of AOA ecotypes with high sensitivity and phylogenetic resolution, which are difficult to examine using conventional approaches.

microbiology↗

bioRxiv2023

Uncovering plant microbiomes using long-read metagenomic sequencing

The microbiome of plants plays a pivotal role in their growth and health. Despite its importance, many fundamental questions about the microbiome remain largely unanswered, such as the identification of colonizing bacterial species, the genes they carry, and the location of these genes on chromosomes or plasmids. To gain insights into the genetic makeup of the rice leaf microbiome, we performed a metagenomic analysis using long-read sequences, and developed a genomic DNA extraction method that provides relatively intact DNA for long-read sequencing. 1.8 Gb reads were assembled into 26,067 contigs, including 136 circular sequences of less than 1 Mbp, as well as 172 large ([≥] 1 Mbp) sequences, six of which were circularized. Within these contigs, 669 complete 16S rRNA genes were clustered into 166 bacterial species, 130 of which showed low identity to previously defined sequences, suggesting that they represent novel species. The large circular contigs contain novel chromosomes and a megaplasmid, and most of the smaller circular contigs (<1 Mbp) were defined as novel plasmids or bacteriophages. One circular contig represents the complete chromosome of an uncultivated bacterium in the candidate phylum Candidatus Saccharibacteria. Our findings demonstrate the efficacy of long-read-based metagenomics for profiling microbial communities and discovering novel sequences in plant-microbiome studies.

microbiology↗

bioRxiv2022

canaper: Categorical analysis of neo- and paleo-endemism in R

O_LIBiodiversity has typically been quantified using species richness, but this ignores evolutionary history. Due to the increasing availability of robust phylogenies, methods have been developed that incorporate phylogenetic relationships into quantification of biodiversity. CANAPE (categorical analysis of neo- and paleo-endemism) is one such method that can provide insight into the evolutionary processes generating biodiversity. The only currently available software implementing CANAPE is Biodiverse, which is written in Perl and can be used either through a graphical user interface (GUI) or user-developed scripts. However, many researchers, particularly in the fields of ecology and evolutionary biology, use the R programming language to conduct their analyses. C_LIO_LIHere, we present canaper, a new R package that provides functions to conduct CANAPE in R. canaper implements methods for efficient computation, including parallelization and encoding of community data as sparse matrices. The interface is designed for maximum simplicity and reproducibility; CANAPE can be conducted with two functions, and parallel computing can be enabled with one line of code. C_LIO_LIOur case study shows that canaper produces equivalent results to Biodiverse and can complete computations on moderately sized datasets quickly (< 10 min to reproduce a canonical study). C_LIO_LIcanaper allows researchers to conduct all analyses from data import and cleaning through CANAPE within R, thereby averting the need to manually import and export data and analysis results between programs. We anticipate canaper will become a part of the toolkit for analyzing biodiversity in R. C_LI

evolutionary biology↗

bioRxiv2022

A fungal secondary metabolism gene cluster enables mutualist-pathogen transition in root endophyte Colletotrichum tofieldiae

Plant-associated fungi show diverse lifestyles from pathogenic to mutualistic to the host; however, the principles and mechanisms through which they shift the lifestyles require elucidation. The root fungus Colletotrichum tofieldiae (Ct) promotes Arabidopsis thaliana growth under phosphate limiting conditions. We reveal a Ct strain, designated Ct3, that severely inhibits plant growth. Ct3 pathogenesis occurs through activation of host abscisic acid (ABA) pathways via a fungal secondary metabolism gene cluster related to sesquiterpene ABA and botrydial (BOT) biosynthesis. ABA-BOT cluster activation during root infection suppresses host nutrient uptake-related genes and changes the mineral contents, suggesting its role in manipulating host nutrition states. Conversely, disruption or environmental suppression of the cluster renders Ct3 beneficial for plant growth, in a manner dependent on host phosphate starvation response regulators. Our findings indicate that a fungal metabolism cluster provides a means by which infectious fungi modulate lifestyles along the parasitic-mutualistic continuum in fluctuating environments.

microbiology↗

bioRxiv2022

An Open and Continuously Updated Fern Tree of Life (FTOL)

1Ferns, with about 12,000 species, are the second most diverse lineage of vascular plants after angiosperms. They have been the subject of numerous molecular phylogenetic studies, resulting in the publication of trees for every major clade and DNA sequences from nearly half of all species. Global fern phylogenies have been published periodically, but as molecular systematics research continues at a rapid pace, these become quickly outdated. Here, we develop a mostly automated, reproducible, open pipeline to generate a continuously updated fern tree of life (FTOL) from DNA sequence data available in GenBank. Our tailored sampling strategy combines whole plastomes (few taxa, many loci) with commonly sequenced plastid regions (many taxa, few loci) to obtain a global, species-level fern phylogeny with high resolution along the backbone and maximal sampling across the tips. We use a curated reference taxonomy to resolve synonyms in general compliance with the community-driven Pteridophyte Phylogeny Group I classification. The current FTOL includes 5,582 species, an increase of ca. 40% relative to the most recently published global fern phylogeny. Using an updated and expanded list of 51 fern fossil constraints, we find estimated ages for most families and deeper clades to be considerably older than earlier studies. FTOL and its accompanying datasets, including the fossil list and taxonomic database, will be updated on a regular basis and are available via a web portal (https://fernphy.github.io) and R packages, enabling immediate access to the most up-to-date, comprehensively sampled fern phylogeny. FTOL will be useful for anyone studying this important group of plants over a wide range of taxonomic scales, from smaller clades to the entire tree. We anticipate FTOL will be particularly relevant for macroecological studies at regional to global scales and will inform future taxonomic systems with the most recent hypothesis of fern phylogeny.

evolutionary biology↗

bioRxiv2021

Inverse Potts model improves accuracy of phylogenetic profiling

Phylogenetic profiling is a powerful computational method for revealing the functions of function-unknown genes. Although conventional similarity evaluation measures in phylogenetic profiling showed high prediction accuracy, they have two estimation biases: an evolutionary bias and a spurious correlation bias. Existing studies have focused on the evolutionary bias, but the spurious correlation bias has not been analyzed. To eliminate the spurious correlation bias, we applied an evaluation measure based on the inverse Potts model (IPM) to phylogenetic profiling. We also proposed an evaluation measure to remove both the evolutionary and spurious correlation biases using the IPM. In an empirical dataset analysis, we demonstrated that these IPM-based evaluation measures improved the prediction performance of phylogenetic profiling. In addition, we found that the integration of several evaluation measures, including the IPM-based evaluation measures, had superior performance to a single evaluation measure. The source code is freely available at https://github.com/fukunagatsu/Ipm.

bioinformatics↗