Polyamines (PAs), such as putrescine, spermidine, and spermine, are essential for plant growth and development. However, the post-translational regulation of PA metabolism remains unknown. Here, we report the COP9 SIGNALOSOME SUBUNIT 5A (FvCSN5A) mediates the degradation of the POLYAMINE OXIDASE 5 (FvPAO5), which catalyzes the conversion of spermidine/spermine to produce H2O2 in strawberry (Fragaria vesca). FvCSN5A is localized in the cytoplasm and nucleus, is ubiquitously expressed in strawberry plants, and is rapidly induced during fruit ripening. FvCSN5A RNA interference (RNAi) transgenic strawberry lines exhibit pleiotropic effects on plant development, fertility, and fruit ripening due to altered PA and H2O2 homeostasis, similar to FvPAO5 transgenic overexpression lines. Moreover, FvCSN5A interacts with FvPAO5 in vitro and in vivo, and the ubiquitination and degradation of FvPAO5 are impaired in FvCSN5A RNAi lines. Additionally, FvCSN5A interacts with cullin 1 (FvCUL1), a core component of the E3 ubiquitin-protein ligase complex. Transient genetic analysis in cultivated strawberry (Fragaria × ananassa) fruits showed that inhibiting FaPAO5 expression could partially rescue the ripening phenotype of FaCSN5A RNAi fruits. Taken together, our results suggest that the CSN5A-CUL1-PAO5 signaling pathway responsible for PA and H2O2 homeostasis is crucial for strawberry vegetative and reproductive growth in particular fruit ripening. Our findings present a promising strategy for improving crop yield and quality.

WormBase has been the major repository and knowledgebase of information about the genome and genetics of Caenorhabditis elegans and other nematodes of experimental interest for over 2 decades. We have 3 goals: to keep current with the fast-paced C. elegans research, to provide better integration with other resources, and to be sustainable. Here, we discuss the current state of WormBase as well as progress and plans for moving core WormBase infrastructure to the Alliance of Genome Resources (the Alliance). As an Alliance member, WormBase will continue to interact with the C. elegans community, develop new features as needed, and curate key information from the literature and large-scale projects.

Polyamines (PAs), including putrescine, spermidine, and spermine, are essential for plant growth and development. However, the post-translational regulation of PA metabolism remains elusive. Here, we report the COP9 signalosome subunit 5A (FvCSN5A)-mediated degradation of the PA oxidase FvPAO5 which catalyzes polyamines to produce H2O2. FvCSN5A was identified through a yeast two-hybrid screen using FvPAO5 as the bait. FvCSN5A localized in both the cytoplasm and nucleus, and its interaction with FvPAO5 occurred in the cytoplasm. FvCSN5A expression was ubiquitous in strawberries and peaked during fruit ripening. We utilized two independent RNAi lines, RNAi -1 and RNAi -2, in which FvCSN5A expression was downregulated by 8-fold and 46-fold, respectively, to demonstrate the pleiotropic roles of FvCSN5A. FvCSN5A positively regulated plant development, fertility, and fruit ripening by maintaining PA homeostasis, and promotes ubiquitination degradation of FvPAO5 through the interaction with cullin 1 (FvCUL1). The accumulation of FvPAO5 in the partial loss-of-function of FvCSN5A transgenic plants resulted from the inhibition of polyubiquitination modification of FvPAO5. Finally, we propose a post-translational regulatory mechanism involving the FvCSN5A-FvCUL1-FvPAO5 axis underlying PA and H2O2 homeostasis, providing novel insights into the regulation of plant growth by integrating the COP9 signalosome-mediated ubiquitination system into PA metabolism.

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication we describe enhancements made to our data processing pipeline and to our website to adapt to an ever-increasing information content. The number of sequences in UniProtKB has risen to over 227 million and we are working towards including a reference proteome for each taxonomic group. We continue to extract detailed annotations from the literature to update or create reviewed entries, while unreviewed entries are supplemented with annotations provided by automated systems using a variety of machine-learning techniques. In addition, the scientific community continues their contributions of publications and annotations to UniProt entries of their interest. Finally, we describe our new website (https://www.uniprot.org/), designed to enhance our users' experience and make our data easily accessible to the research community. This interface includes access to AlphaFold structures for more than 85% of all entries as well as improved visualisations for subcellular localisation of proteins.

Chinese hamster ovary (CHO) cell lines are widely used to manufacture biopharmaceuticals. However, CHO cells are not an optimal expression host due to the intrinsic plasticity of the CHO genome. Genome plasticity can lead to chromosomal rearrangements, transgene exclusion, and phenotypic drift. A poorly understood genomic element of CHO cell line instability is extrachromosomal circular DNA (eccDNA) in gene expression and regulation. EccDNA can facilitate ultra-high gene expression and are found within many eukaryotes including humans, yeast, and plants. EccDNA confers genetic heterogeneity, providing selective advantages to individual cells in response to dynamic environments. In CHO cell cultures, maintaining genetic homogeneity is critical to ensuring consistent productivity and product quality. Understanding eccDNA structure, function, and microevolutionary dynamics under various culture conditions could reveal potential engineering targets for cell line optimization. In this study, eccDNA sequences were investigated at the beginning and end of two-week fed-batch cultures in an ambr®250 bioreactor under control and lactate-stressed conditions. This work characterized structure and function of eccDNA in a CHO-K1 clone. Gene annotation identified 1551 unique eccDNA genes including cancer driver genes and genes involved in protein production. Furthermore, RNA-seq data is integrated to identify transcriptionally active eccDNA genes.

Alzheimer’s disease and related dementias (AD/ADRDs) are among the most common forms of dementia, and yet no effective treatments have been developed. To gain insight into the disease mechanism, capturing the connection of genetic variations to their impacts, at the disease and molecular levels, is essential. The scientific literature continues to be a main source for reporting experimental information about the impact of variants. Thus, development of automatic methods to identify publications and extract the information from the unstructured text would facilitate collecting and organizing information for reuse. We developed eMIND, a deep learning-based text mining system that supports the automatic extraction of annotations of variants and their impacts in AD/ADRDs. In particular, we use this method to capture the impacts of protein-coding variants affecting a selected set of protein properties, such as protein activity/function, structure and post-translational modifications. We conducted an evaluation on the efficacy of eMIND to extract variant impact relations and obtained a recall of 0.84 and a precision of 0.94. The publications and extracted information are integrated into the UniProtKB computationally mapped bibliography to expand annotations on protein entries. eMIND’s text-mined output are presented using controlled vocabularies and ontologies for variant, disease and impact along with the evidence sentences. A sample of annotated abstracts can be accessed at URL: https://research.bioinformatics.udel.edu/itextmine/emind .

Chinese hamster ovary (CHO) cells are widely used for mass production of therapeutic proteins in the pharmaceutical industry. With the growing need in optimizing the performance of producer CHO cell lines, research on CHO cell line development and bioprocess continues to increase in recent decades. Bibliographic mapping and classification of relevant research studies will be essential for identifying research gaps and trends in literature. To qualitatively and quantitatively understand the CHO literature, we have conducted topic modeling using a CHO bioprocess bibliome manually compiled in 2016, and compared the topics uncovered by the Latent Dirichlet Allocation (LDA) models with the human labels of the CHO bibliome. The results show a significant overlap between the manually selected categories and computationally generated topics, and reveal the machine-generated topic-specific characteristics. To identify relevant CHO bioprocessing papers from new scientific literature, we have developed supervized models using Logistic Regression to identify specific article topics and evaluated the results using three CHO bibliome datasets, Bioprocessing set, Glycosylation set, and Phenotype set. The use of top terms as features supports the explainability of document classification results to yield insights on new CHO bioprocessing papers.

WormBase (www.wormbase.org) is the central repository for the genetics and genomics of the nematode Caenorhabditis elegans. We provide the research community with data and tools to facilitate the use of C. elegans and related nematodes as model organisms for studying human health, development, and many aspects of fundamental biology. Throughout our 22-year history, we have continued to evolve to reflect progress and innovation in the science and technologies involved in the study of C. elegans. We strive to incorporate new data types and richer data sets, and to provide integrated displays and services that avail the knowledge generated by the published nematode genetics literature. Here, we provide a broad overview of the current state of WormBase in terms of data type, curation workflows, analysis, and tools, including exciting new advances for analysis of single-cell data, text mining and visualization, and the new community collaboration forum. Concurrently, we continue the integration and harmonization of infrastructure, processes, and tools with the Alliance of Genome Resources, of which WormBase is a founding member.

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.

The UniProt knowledgebase is a public database for protein sequence and function, covering the tree of life and over 220 million protein entries. Now, the whole community can use a new crowdsourcing annotation system to help scale up UniProt curation and receive proper attribution for their biocuration work.

MOTIVATION:The number of protein records in the UniProt Knowledgebase (UniProtKB: https://www.uniprot.org) continues to grow rapidly as a result of genome sequencing and the prediction of protein-coding genes. Providing functional annotation for these proteins presents a significant and continuing challenge. RESULTS:In response to this challenge, UniProt has developed a method of annotation, known as UniRule, based on expertly curated rules, which integrates related systems (RuleBase, HAMAP, PIRSR, PIRNR) developed by the members of the UniProt consortium. UniRule uses protein family signatures from InterPro, combined with taxonomic and other constraints, to select sets of reviewed proteins which have common functional properties supported by experimental evidence. This annotation is propagated to unreviewed records in UniProtKB that meet the same selection criteria, most of which do not have (and are never likely to have) experimentally verified functional annotation. Release 2020_01 of UniProtKB contains 6496 UniRule rules which provide annotation for 53 million proteins, accounting for 30% of the 178 million records in UniProtKB. UniRule provides scalable enrichment of annotation in UniProtKB. AVAILABILITY AND IMPLEMENTATION:UniRule rules are integrated into UniProtKB and can be viewed at https://www.uniprot.org/unirule/. UniRule rules and the code required to run the rules, are publicly available for researchers who wish to annotate their own sequences. The implementation used to run the rules is known as UniFIRE and is available at https://gitlab.ebi.ac.uk/uniprot-public/unifire.

Background: As bioprocess intensification has increased over the last 30 years, yields from mammalian cell processes have increased from 10's of milligrams to over 10's of grams per liter. Most of these gains in productivity can be attributed to increasing cell densities within bioreactors. As such, strategies have been developed to minimize accumulation of metabolic wastes, such as lactate and ammonia. Unfortunately, neither cell growth nor biopharmaceutical production can occur without some waste metabolite accumulation. Inevitably, metabolic waste accumulation leads to decline and termination of the culture. While it is understood that the accumulation of these unwanted compounds imparts a suboptimal culture environment, little is known about the genotoxic properties of these compounds that may lead to global genome instability. In this study, we examined the effects of high and moderate extracellular ammonia on the physiology and genomic integrity of Chinese hamster ovary (CHO) cells. Results: Through whole genome sequencing, we discovered 2394 variant sites within functional genes comprised of both single nucleotide polymorphisms and insertion/deletion mutations as a result of ammonia stress with high or moderate impact on functional genes. Furthermore, several of these de novo mutations were found in genes whose functions are to maintain genome stability, such as Tp53, Tnfsf11, Brca1, as well as Nfkb1. Furthermore, we characterized microsatellite content of the cultures using the CriGri-PICR Chinese hamster genome assembly and discovered an abundance of microsatellite loci that are not replicated faithfully in the ammonia-stressed cultures. Unfaithful replication of these loci is a signature of microsatellite instability. With rigorous filtering, we found 124 candidate microsatellite loci that may be suitable for further investigation to determine whether these loci may be reliable biomarkers to predict genome instability in CHO cultures. Conclusion; This study advances our knowledge with regards to the effects of ammonia accumulation on CHO cell culture performance by identifying ammonia-sensitive genes linked to genome stability and lays the foundation for the development of a new diagnostic tool for assessing genome stability.

WormBase (https://wormbase.org/) is a mature Model Organism Information Resource supporting researchers using the nematode Caenorhabditis elegans as a model system for studies across a broad range of basic biological processes. Toward this mission, WormBase efforts are arranged in three primary facets: curation, user interface and architecture. In this update, we describe progress in each of these three areas. In particular, we discuss the status of literature curation and recently added data, detail new features of the web interface and options for users wishing to conduct data mining workflows, and discuss our efforts to build a robust and scalable architecture by leveraging commercial cloud offerings. We conclude with a description of WormBase's role as a founding member of the nascent Alliance of Genome Resources.

The universal protein knowledgebase (UniProtKB) collects and centralises functional information on proteins across a wide range of species. In addition to the functional information added to all protein entries, for enzymes, which represent 20–40% of most proteomes, UniProtKB provides additional information about Enzyme Commission classification, catalytic activity, cofactors, enzyme regulation, kinetics and pathways, all based on critical assessment of published experimental data. Computer‐based analysis and structural data are used to enrich the annotation of the sequence through the identification of active sites and binding sites. While the annotation of enzymes is well‐defined, the curation of pseudoenzymes in UniProtKB has highlighted some challenges: how to identify them, how to assess their lack of catalytic activity, how to annotate their lack of catalytic activity in a consistent way and how much can be inferred and propagated from experimental data obtained from other species. Through various examples, we illustrate some of these issues and discuss some of the changes we propose to enhance the annotation and discovery of pseudoenzymes. Ultimately, improving the curation of pseudoenzymes will provide the scientific community with a comprehensive resource for pseudoenzymes, which in turn will lead to a better understanding of the evolution of these molecules, the aetiology of related diseases and the development of drugs.

Methods focused on predicting 'global' annotations for proteins (such as molecular function, biological process and presence of domains or membership in a family) have reached a relatively mature stage. Methods to provide fine-grained 'local' annotation of functional sites (at the level of individual amino acid) are now coming to the forefront, especially in light of the rapid accumulation of genetic variant data. We have developed a computational method and workflow that predicts functional sites within proteins using position-specific conditional template annotation rules (namely PIR Site Rules or PIRSRs for short). Such rules are curated through review of known protein structural and other experimental data by structural biologists and are used to generate high-quality annotations for the UniProt Knowledgebase (UniProtKB) unreviewed section. To share the PIRSR functional site prediction method with the broader scientific community, we have streamlined our workflow and developed a stand-alone Java software package named PIRSitePredict. We demonstrate the use of PIRSitePredict for functional annotation of de novo assembled genome/transcriptome by annotating uncharacterized proteins from Trinity RNA-seq assembly of embryonic transcriptomes of the following three cartilaginous fishes: Leucoraja erinacea (Little Skate), Scyliorhinus canicula (Small-spotted Catshark) and Callorhinchus milii (Elephant Shark). On average about 1200 lines of annotations were predicted for each species.

As bioprocess intensification has increased over the last 30 years, yields from mammalian cell processes have increased from 10’s of milligrams to over 10’s of grams per liter. Most of these gains in productivity have been due to increasing cell numbers in the bioreactors, and with those increases in cell numbers, strategies have been developed to minimize metabolite waste accumulation, such as lactate and ammonia. Unfortunately, cell growth cannot occur without some waste metabolite accumulation, as central metabolism is required to produce the biopharmaceutical. Inevitably, metabolic waste accumulation leads to decline and termination of the culture. While it is understood that the accumulation of these unwanted compounds imparts a less than optimal culture environment, little is known about the genotoxic properties and the influence of these compounds on global genome instability. In this study, we examined the effects on Chinese hamster ovary (CHO) cells’ genome sequences and physiology due to exposure to elevated ammonia levels. We identified genome-wide de novo mutations, in addition to variants in functional regions of certain genes involved in the mismatch repair (MMR) pathway, such as DNA2, BRCA1 and RAD52 , which led to loss-of-function and eventual genome instability. Additionally, we characterized the presence of microsatellites against the most recent Chinese Hamster genome assembly and discovered certain loci are not replicated faithfully in the presence of elevated ammonia, which represents microsatellite instability (MSI). Furthermore, we found 124 candidate loci that may be suitable biomarkers to gauge genome stability in CHO cultures.

WormBase (http://www.wormbase.org) is an important knowledge resource for biomedical researchers worldwide. To accommodate the ever increasing amount and complexity of research data, WormBase continues to advance its practices on data acquisition, curation and retrieval to most effectively deliver comprehensive knowledge about Caenorhabditis elegans, and genomic information about other nematodes and parasitic flatworms. Recent notable enhancements include user-directed submission of data, such as micropublication; genomic data curation and presentation, including additional genomes and JBrowse, respectively; new query tools, such as SimpleMine, Gene Enrichment Analysis; new data displays, such as the Person Lineage browser and the Summary of Ontology-based Annotations. Anticipating more rapid data growth ahead, WormBase continues the process of migrating to a cutting-edge database technology to achieve better stability, scalability, reproducibility and a faster response time. To better serve the broader research community, WormBase, with five other Model Organism Databases and The Gene Ontology project, have begun to collaborate formally as the Alliance of Genome Resources.

Post-translational modifications (PTMs) are one of the main contributors to the diversity of proteoforms in the proteomic landscape. In particular, protein phosphorylation represents an essential regulatory mechanism that plays a role in many biological processes. Protein kinases, the enzymes catalyzing this reaction, are key participants in metabolic and signaling pathways. Their activation or inactivation dictate downstream events: what substrates are modified and their subsequent impact (e.g., activation state, localization, protein-protein interactions (PPIs)). The biomedical literature continues to be the main source of evidence for experimental information about protein phosphorylation. Automatic methods to bring together phosphorylation events and phosphorylation-dependent PPIs can help to summarize the current knowledge and to expose hidden connections. In this chapter, we demonstrate two text mining tools, RLIMS-P and eFIP, for the retrieval and extraction of kinase-substrate-site data and phosphorylation-dependent PPIs from the literature. These tools offer several advantages over a literature search in PubMed as their results are specific for phosphorylation. RLIMS-P and eFIP results can be sorted, organized, and viewed in multiple ways to answer relevant biological questions, and the protein mentions are linked to UniProt identifiers.

This short paper briefly presents an efficient implementation of a named entity recognition system for biomedical entities, which is also available as a web service. The approach is based on a dictionary-based entity recognizer combined with a machine-learning classifier which acts as a filter. We evaluated the efficiency of the approach through participation in the TIPS challenge (BioCreative V.5), where it obtained the best results among participating systems. We separately evaluated the quality of entity recognition and linking, using a manually annotated corpus as a reference (CRAFT), where we obtained state-of-the-art results.