Diverse Organisms Research Articles

Staring into a crystall ball: understanding evolution and development of in vivo aquatic organismal transparency

Organismal transparency is an ecologically important trait that can provide camouflage advantages to diverse organisms. Transparent organisms are quite common—especially in oceans. Organismal transparency requires low absorption and scattering of light in the body across multi-scale levels. However, it is still not fully understood how such organisms achieve these requirements. Understanding this process requires multiple approaches from various fields and methods. Here, we offer recent insights on this topic from the viewpoints of evolution, developmental biology, and evaluation methodologies of organismal transparency. We also propose “organismal transparency biology” as a new interdisciplinary field of study. Furthermore, we suggest that tunicates are an ideal model animal for studying in vivo organismal transparency.

RiboSeq.Org: an integrated suite of resources for ribosome profiling data analysis and visualization.

Ribosome profiling (Ribo-Seq) has revolutionisedour understanding of translation, but the increasing complexity and volume of Ribo-Seq data present challenges for its reuse. Here, we formally introduce RiboSeq.Org, an integrated suite of resources designed to facilitate Ribo-Seq data analysis and visualisation within a web browser. RiboSeq.Org comprises several interconnected tools: GWIPS-viz for genome-wide visualisation, Trips-Viz for transcriptome-centric analysis, RiboGalaxy for data processing and the newly developed RiboSeq data portal (RDP) for centralised dataset identification and access. The RDP currently hosts preprocessed datasets corresponding to 14840 sequence libraries (samples) from 969 studies across 96 species, in various file formats along with standardised metadata. RiboSeq.Org addresses key challenges in Ribo-Seq data reuse through standardised sample preprocessing, semi-automated metadata curation and programmatic informationaccess via a REST API and command-line utilities. RiboSeq.Org enhances the accessibility and utility of public Ribo-Seq data, enabling researchers to gain new insights into translational regulation and protein synthesis across diverse organisms and conditions. By providing these integrated, user-friendly resources, RiboSeq.Org aims to lower the barrier to reproducible research in the field of translatomics and promote more efficient utilisation of the wealth of available Ribo-Seq data.

Harnessing full-text publications for deep insights into C. elegans and Drosophila biomaps.

In the rapidly expanding domain of scientific research, tracking and synthesizing information from the rapidly increasing volume of publications pose significant challenges. To address this, we introduce a novel high-throughput pipeline that employs ChatGPT to systematically extract and analyze connectivity information from the full-texts and abstracts of 24,237 and 150,538 research publications concerning Caenorhabditis elegans and Drosophila melanogaster, respectively. This approach has effectively identified 200,219 and 1,194,587 interactions within the C. elegans and Drosophila biomaps, respectively. Utilizing Cytoscape Web, we have developed a searchable online biomaps that link relevant keywords to their corresponding PubMed IDs, thus providing seamless access to an extensive knowledge network encompassing C. elegans and Drosophila. Our work highlights the transformative potential of integrating artificial intelligence with bioinformatics to deepen our understanding of complex biological systems. By revealing the intricate web of relationships among key entities in C. elegans and Drosophila, we offer invaluable insights that promise to propel advancements in genetics, developmental biology, neuroscience, longevity, and beyond. We also provide details and discuss significant nodes within both biomaps, including the insulin/IGF-1 signaling (IIS) and the notch pathways. Our innovative methodology sets a robust foundation for future research aimed at unravelling complex biological networks across diverse organisms. The two databases are available at worm.bio-map.com and drosophila.bio-map.com.

OrthoDB and BUSCO update: annotation of orthologs with wider sampling of genomes.

OrthoDB (https://www.orthodb.org) offers evolutionary and functional annotations of orthologous genes in the widest sampling of eukaryotes, prokaryotes, and viruses, extending experimental gene function knowledge to newly sequenced genomes. We collect gene annotations, delineate hierarchical gene orthologyand annotate the orthologous groups (OGs) with functional and evolutionary traits. OrthoDB is the leading resource for species diversity, striving to sample the most diverse and well-researched organisms with the highest quality genomic data. This update expands to include 5827 eukaryotic genomes. We have also added coding DNA sequences (CDSs) and gene loci coordinates. OrthoDB can be browsed, downloaded, or accessed using REST API, SPARQL/RDFand now also via API packages for Python and R Bioconductor. OrthoLoger (https://orthologer.ezlab.org), the tool used for inferring orthologs in OrthoDB, is now available as a Conda package and through BioContainers. ODB-mapper, a component of OrthoLoger, streamlines annotation of genes from newly sequenced genomes with OrthoDB evolutionary and functional descriptors. The benchmarking sets of universal single-copy orthologs (BUSCO), derived from OrthoDB, had correspondingly a major update. The BUSCO tool (https://busco.ezlab.org) has become a standard in genomics, uniquely capable of assessing both eukaryotic and prokaryotic species. It is applicable to gene sets, transcriptomes, genome assembliesand metagenomic bins.

Resveratrol Potentiates BCG-induced Trained Immunity in Human Monocytes.

Resveratrol is a natural polyphenol derived from plants such as grapes and berries. In addition to its role in plants during injury and infection, various cardioprotective, neuroprotective, and longevity-promoting effects were reported in diverse model organisms. The primary target of resveratrol is the deacetylase Sirtuin 1 (SIRT1), which regulates many immunological processes, including BCG-induced trained immunity response in humans. We, therefore, investigated the effect of resveratrol on trained immunity induced by BCG, β-glucan, C. albicans, or oxidized low-density lipoprotein (oxLDL). Using an in-vitro model of trained immunity with monocytes obtained from healthy donors, we demonstrate that resveratrol amplifies BCG-induced trained immunity regarding IL-6 and TNFα production after a secondary challenge. Although resveratrol did not improve and even limited glycolysis, oxidative phosphorylation, and reactive oxygen species production, it enhanced the permissive epigenetic mark H3K27Ac on IL-6 and TNFα promoters. In contrast to BCG-induced trained immunity, resveratrol potently inhibited training induced by β-glucan, C. albicans, oxLDL, and muramyl dipeptide (MDP), a peptidoglycan component of BCG. Resveratrol's unique boosting effect on BCG training depended on BCG being alive and metabolically active. These results suggest that resveratrol might amplify the effects of BCG vaccination, which should be mechanistically characterized further. In addition, resveratrol could alleviate oxLDL-induced training of innate immune cells in atherosclerosis, and in-vivo studies of trained immunity combined with resveratrol are warranted to explore these therapeutic possibilities.

Conserved features and diversity attributes of chimeric RNAs across accessions in four plants.

As a non-collinear expression form of genetic information, chimeric RNAs increase the complexity of transcriptome in diverse organisms. Although chimeric RNAs have been identified in plants, few common features have been revealed. Here, we systemically explored the landscape of chimeric RNAs across multi-accession and multi-tissue using pan-genome and transcriptome data of four plants: rice, maize, soybean, and Arabidopsis. Among the four species, conserved characteristics of breakpoints and parental genes were discovered. In each species, chimeric RNAs displayed a high level of diversity among accessions, and the clustering of accessions using chimeric events was generally concordant with clustering based on genomic variants, implying a general relationship between genetic variations and chimeric RNAs. Through mass spectrometry, we confirmed a fusion protein OsNDC1-OsGID1L2 and observed its subcellular localization, which differed from the original proteins. Phenotypic cues in transgenic rice suggest the potential functions of OsNDC1-OsGID1L2. Moreover, an intriguing chimeric event Os01g0216500-Os01g0216900, generated by a large deletion in basmati rice, also exists in another accession without the deletion, demonstrating its convergence in evolution. Our results illuminate the characteristics and hint at the evolutionary implications of plant chimeric RNAs, which serve as a supplement to genetic variations, thus expanding our understanding of genetic diversity.

Local freshwater fluxes determine salinity variations of the Bohai Sea: Based on 60 years of observations

Salinity, a fundamental characteristic of seawater, significantly influences the ocean's physicochemical properties and directly affects marine biodiversity and its spatial distribution. The semi-enclosed Bohai Sea is home to diverse marine organisms and serves as a critical area for human mariculture. Salinity variations in this region are crucial for the stability of the ecosystem and the sustainability of the marine economy. However, significant discrepancies have been observed between the practical salinity measurements of the Bohai Sea in winter 2007 and that recorded in widely used national and international marine atlases prior to 2000. To identify these discrepancies, this study systematically investigates the salinity variations and the regulatory mechanisms in the Bohai Sea. First, we constructed a climatological salinity dataset with a broader temporal scope based on in-situ salinity data from 1960 to 2020, confirming that the climatological salinity field of the Bohai Sea did not undergo a significant shift, but exhibited phase changes. Subsequently, using the principles of conservation of mass and salinity, we developed a box model to analyze annual salinity changes in the Bohai Sea. This model was optimized using in-situ hydrological measurements and reanalysis data spanning over 60 years, successfully revealing the central regulatory role of local freshwater fluxes in annual salinity changes in the Bohai Sea. Furthermore, we elucidated that the anomalously high salinity in the Bohai Sea in the winter of 2007 resulted from the cumulative effect of several consecutive years of negative freshwater fluxes. The results of this study not only enhance our understanding and prediction of salinity changes in semi-enclosed seas, providing a scientific basis for ecosystem protection and management, but also offer valuable insights for studying long-term salinity changes in other semi-enclosed seas.

The UCSC Genome Browser database: 2025 update.

The UCSC Genome Browser (https://genome.ucsc.edu) is a widely utilized web-based tool for visualization and analysis of genomic data, encompassing over 4000 assemblies from diverse organisms. Since its release in 2001, it has become an essential resource for genomics and bioinformatics research. Annotation data available on Genome Browser includes both internally created and maintained tracks as well as custom tracks and track hubs provided by the research community. This last year's updates include over 25 new annotation tracks such as the gnomAD 4.1 track on the human GRCh38/hg38 assembly, the addition of three new public hubs, and significant expansions to the Genome Archive[GenArk) system for interacting with the enormous variety of assemblies. We have also made improvements to our interface, including updates to the browser graphic page, such as a new popup dialog feature that now displays item details without requiring navigation away from the main Genome Browser page. GenePred tracks have been upgraded with right-click options for zooming and precise navigation, along with enhanced mouseOver functions. Additional improvements include a new grouping feature for track hubs and hub description info links. A new tutorial focusing on Clinical Genetics has also been added to the UCSC Genome Browser.

IModulonMiner and PyModulon: Software for unsupervised mining of gene expression compendia.

Public gene expression databases are a rapidly expanding resource of organism responses to diverse perturbations, presenting both an opportunity and a challenge for bioinformatics workflows to extract actionable knowledge of transcription regulatory network function. Here, we introduce a five-step computational pipeline, called iModulonMiner, to compile, process, curate, analyze, and characterize the totality of RNA-seq data for a given organism or cell type. This workflow is centered around the data-driven computation of co-regulated gene sets using Independent Component Analysis, called iModulons, which have been shown to have broad applications. As a demonstration, we applied this workflow to generate the iModulon structure of Bacillus subtilis using all high-quality, publicly-available RNA-seq data. Using this structure, we predicted regulatory interactions for multiple transcription factors, identified groups of co-expressed genes that are putatively regulated by undiscovered transcription factors, and predicted properties of a recently discovered single-subunit phage RNA polymerase. We also present a Python package, PyModulon, with functions to characterize, visualize, and explore computed iModulons. The pipeline, available at https://github.com/SBRG/iModulonMiner, can be readily applied to diverse organisms to gain a rapid understanding of their transcriptional regulatory network structure and condition-specific activity.

Trehalulose: Exploring its benefits, biosynthesis, and enhanced production techniques

The increasing concern over sugar-related health issues has sparked research interest in seeking alternatives to sucrose. Trehalulose, a beneficial structural isomer of sucrose, is a non-cariogenic sugar with a low glycemic and insulinemic index. Besides its potential as a sugar substitute, trehalulose exhibits high antioxidant properties, making it attractive for various industrial applications. Despite its numerous advantages and potential application in various sectors, the industrial adoption of trehalulose has yet to be established due to lack of studies on its characteristics and practical uses. This review aims to provide a comprehensive overview of the properties of trehalulose, emphasizing its health benefits. The industrial prospects of trehalulose as sweetener and reducing agent, particularly in food and beverages pharmaceutical, and cosmeceutical sectors, are explored. Additionally, the review delves into the sources of trehalulose and the diverse organisms capable of producing trehalulose. The biosynthesis of this sugar primarily involves an enzyme-mediated process. Thus, these enzymes' properties, mechanisms, and the heterologous expression of genes associated with trehalulose production are explored. The strategies discussed in this review can be improved and applied to establish trehalulose bio-factories for efficient synthesis of trehalulose in the future. With further research and development, trehalulose holds promise as a valuable component across various industries.

Peptide-Based Inhibitors of Protein-Protein Interactions (PPIs): A Case Study on the Interaction Between SARS-CoV-2 Spike Protein and Human Angiotensin-Converting Enzyme 2 (hACE2).

Protein-protein interactions (PPIs) are fundamental to many critical biological processes and are crucial in mediating essential cellular functions across diverse organisms, including bacteria, parasites, and viruses. A notable example is the interaction between the SARS-CoV-2 spike (S) protein and the human angiotensin-converting enzyme 2 (hACE2), which initiates a series of events leading to viral replication. Interrupting this interaction offers a promising strategy for blocking or significantly reducing infection, highlighting its potential as a target for anti-SARS-CoV-2 therapies. This review focuses on the hACE2 and SARS-CoV-2 spike protein interaction, exemplifying the latest advancements in peptide-based strategies for developing PPI inhibitors. We discuss various approaches for creating peptide-based inhibitors that target this critical interaction, aiming to provide potential treatments for COVID-19.

Changing epidemiology and antimicrobial susceptibility of bloodstream infections at a Vietnamese infectious diseases hospital (2010–2020)

Bloodstream infection (BSI) poses a global health problem, with diverse organisms and rising antimicrobial resistance (AMR). Here, we characterized trends in BSI prevalence, AMR, and antibiotic use at a Vietnamese infectious diseases hospital from 2010 to 2020. Among 108,303 cultured blood samples, 8.8% were positive, yielding 7995 pathogens. Of 7553 BSI cases, 86.4% were community-acquired. BSI prevalence varied from 17 to 35 cases/1000 admissions/year, highest in HIV/hepatitis wards and patients >60. The in-hospital mortality or hospice discharge outcome was 21.3%. The top three pathogens, E. coli (24%), K. pneumoniae (8.7%) and S. aureus (8.5%) exhibited increasing prevalence and multidrug resistance. Pathogens like Cryptococcus neoformans (8.4%), Talaromyces marneffei (6.7%), and Salmonella enterica (6.5%) declined. E. coli and K. pneumoniae were prevalent in older adults with community-acquired BSIs. Antibiotic use reached 842.6 DOT/1000 PD and significantly reduced after an antibiotic control policy. Enhanced surveillance and antimicrobial stewardship are crucial for managing BSIs in Vietnam.

Marine biofilms: cyanobacteria factories for the global oceans.

Cyanobacteria, highly diverse microbial organisms, play a crucial role in Earth's oxygenation and biogeochemical cycling. However, their connection to these processes remains unclear, partly due to incomplete surveys of oceanic niches. Our study uncovered significant cyanobacterial diversity in marine biofilms, showing distinct niche differentiation compared to seawater counterparts. These patterns reflect three key stages of marine cyanobacterial diversification, coinciding with major geological events in the Earth's history.

ProEnd: a comprehensive database for identifying HbYX motif-containing proteins across the tree of life

The proteasome plays a crucial role in cellular homeostasis by degrading misfolded, damaged, or unnecessary proteins. Understanding the regulatory mechanisms of proteasome activity is vital, particularly the interaction with activators containing the hydrophobic-tyrosine-any amino acid (HbYX) motif. Here, we present ProEnd, a comprehensive database designed to identify and catalog HbYX motif-containing proteins across the tree of life. Using a simple bioinformatics pipeline, we analyzed approximately 73 million proteins from 22,000 reference proteomes in the UniProt/SwissProt database. Our findings reveal the widespread presence of HbYX motifs in diverse organisms, highlighting their evolutionary conservation and functional significance. Notably, we observed an interesting prevalence of these motifs in viral proteomes, suggesting strategic interactions with the host proteasome. As validation two novel HbYX proteins found in this database were experimentally tested by pulldowns, confirming that they directly interact with the proteasome, with one of them directly activating it. ProEnd’s extensive dataset and user-friendly interface enable researchers to explore the potential proteasomal regulator landscape, generating new hypotheses to advance proteasome biology. This resource is set to facilitate the discovery of novel therapeutic targets, enhancing our approach to treating diseases such as neurodegenerative disorders and cancer.

Factors shaping pelagic-benthic coupling in the process of settlement in an Arctic fjord

Benthic organisms typically possess a planktonic propagule stage in the form of larvae or spores, which enables them to spread over large distances before settlement, and promotes tight pelago-benthic coupling. However, factors driving dispersal and epibenthos recruitment in shallow hard-bottom Arctic communities are poorly known. We therefore conducted a year-round in situ colonization experiment in Isfjorden (Svalbard), and found out that variation in early-stage epibenthic assemblages was explained by the combination of: abiotic (45.9%) and biotic variables (23.9%), and their interactions (30.2%). The upward-facing experimental plates were dominated by coralline algae, and this is the first study showing that at high latitudes coralline algae Lithothamnion sp. settle in high numbers on available substrates during the polar night in winter. The downward-facing plates, which had much less exposure to light, contained more diverse organisms, with a predominance of polychaetas and bryozoans. However, in summer, the barnacle Semibalanus balanoides outcompeted all the other recruits, as a result of massive occurrence of meroplanktonic Cirripedia larvae, triggered by the phytoplankton bloom. In conclusion, the rate and success of epibenthic settlements were dependent mostly on light availability and temperature, suggesting that larval settlement will be impacted by global warming with some taxa benefitting, while others losing.

Genome-Scale Metabolic Models in Fungal Pathogens: Past, Present, and Future.

Fungi are diverse organisms with various characteristics and functions. Some play a role in recycling essential elements, such as nitrogen and carbon, while others are utilized in the food and drink production industry. Some others are known to cause diseases in various organisms, including humans. Fungal pathogens cause superficial, subcutaneous, and systemic infections. Consequently, many scientists have focused on studying the factors contributing to the development of human diseases. Therefore, multiple approaches have been assessed to examine the biology of these intriguing organisms. The genome-scale metabolic models (GEMs) have demonstrated many advantages to microbial metabolism studies and the ability to propose novel therapeutic alternatives. Despite significant advancements, much remains to be elucidated regarding the use of this tool for investigating fungal metabolism. This review aims to compile the data provided by the published GEMs of human fungal pathogens. It gives specific examples of the most significant contributions made by these models, examines the advantages and difficulties associated with using such models, and explores the novel approaches suggested to enhance and refine their development.

GeneCompass: deciphering universal gene regulatory mechanisms with a knowledge-informed cross-species foundation model.

Deciphering universal gene regulatory mechanisms in diverse organisms holds great potential for advancing our knowledge of fundamental life processes and facilitating clinical applications. However, the traditional research paradigm primarily focuses on individual model organisms and does not integrate various cell types across species. Recent breakthroughs in single-cell sequencing and deep learning techniques present an unprecedented opportunity to address this challenge. In this study, we built an extensive dataset of over 120 million human and mouse single-cell transcriptomes. After data preprocessing, we obtained 101,768,420 single-cell transcriptomes and developed a knowledge-informed cross-species foundation model, named GeneCompass. During pre-training, GeneCompass effectively integrated four types of prior biological knowledge to enhance our understanding of gene regulatory mechanisms in a self-supervised manner. By fine-tuning for multiple downstream tasks, GeneCompass outperformed state-of-the-art models in diverse applications for a single species and unlocked new realms of cross-species biological investigations. We also employed GeneCompass to search for key factors associated with cell fate transition and showed that the predicted candidate genes could successfully induce the differentiation of human embryonic stem cells into the gonadal fate. Overall, GeneCompass demonstrates the advantages of using artificial intelligence technology to decipher universal gene regulatory mechanisms and shows tremendous potential for accelerating the discovery of critical cell fate regulators and candidate drug targets.

Statistical analysis of the unique characteristics of secondary structures in proteins

Protein folding is a complex process influenced by the primary sequence of amino acids. Early studies focused on understanding whether the specificity or the conservation of properties of amino acids was crucial for folding into secondary structures such as α-helices, β-sheets, turns, and coils. However, with the advent of artificial intelligence (AI) and machine learning (ML), the emphasis has shifted towards the precise nature and occurrence of specific amino acids. In our study, we analyzed a large set of proteins from diverse organisms to identify unique features of secondary structures, particularly in terms of the distribution of polar, non-polar, and charged amino acid residues. We found that α-helices tend to have a higher proportion of charged and non-polar groups compared to other secondary structures and that the presence of oppositely charged amino acid residues in helices stabilizes them, facilitating the formation of longer helices. These characteristics are distinct to α-helices. This study offers valuable insights for researchers in the field of protein design, enabling the de-novo creation of short helical peptides for a range of applications. We have also developed a web server for extensive analysis of proteins from different databases. The web server is housed at https://proseqanalyser.iitgn.ac.in/

Investigating Non-Native Ribbon Worm Cephalothrix simula as a Potential Source of Tetrodotoxin in British Bivalve Shellfish.

Tetrodotoxin (TTX) is a potent marine neurotoxin found in several phylogenetically diverse organisms, some of which are sought as seafood. Since 2015, TTX has been reported in bivalve shellfish from several estuarine locations along the Mediterranean and European Atlantic coasts, posing an emerging food safety concern. Although reports on spatial and temporal distribution have increased in recent years, processes leading to TTX accumulation in European bivalves are yet to be described. Here, we explored the hypothesis that the ribbon worm species Cephalothrix simula, known to contain high levels of TTX, could play a role in the trophic transfer of the toxin into shellfish. During a field study at a single location in southern England, we confirmed C. simula DNA in seawater adjacent to trestle-farmed Pacific oysters Magallana gigas (formerly Crassostrea gigas) with a history of TTX occurrence. C. simula DNA in seawater was significantly higher in June and July during the active phase of toxin accumulation compared to periods of either no or continually decreasing TTX concentrations in M. gigas. In addition, C. simula DNA was detected in oyster digestive glands collected on 15 June 2021, the day with the highest recorded C. simula DNA abundance in seawater. These findings show evidence of a relationship between C. simula and TTX occurrence, providing support for the hypothesis that bivalves may acquire TTX through filter-feeding on microscopic life forms of C. simula present in the water column at particular periods each year. Although further evidence is needed to confirm such feeding activity, this study significantly contributes to discussions about the biological source of TTX in European bivalve shellfish.

Minimal motifs for habituating systems

Habituation-a phenomenon in which a dynamical system exhibits a diminishing response to repeated stimulations that eventually recovers when the stimulus is withheld-is universally observed in living systems from animals to unicellular organisms. Despite its prevalence, generic mechanisms for this fundamental form of learning remain poorly defined. Drawing inspiration from prior work on systems that respond adaptively to step inputs, we study habituation from a nonlinear dynamics perspective. This approach enables us to formalize classical hallmarks of habituation that have been experimentally identified in diverse organisms and stimulus scenarios. We use this framework to investigate distinct dynamical circuits capable of habituation. In particular, we show that driven linear dynamics of a memory variable with static nonlinearities acting at the input and output can implement numerous hallmarks in a mathematically interpretable manner. This work establishes a foundation for understanding the dynamical substrates of this primitive learning behavior and offers a blueprint for the identification of habituating circuits in biological systems.