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BACKGROUND: Staphylococci cause a wide range of infections, including implant-associated infections which are difficult to treat due to the presence of biofilms. Whilst some proteins involved in biofilm formation are known, the differences in biofilm production between staphylococcal species remains understudied. Currently biofilm formation by Staphylococcus aureus is better understood than other members of the genus as more research has focused on this species. RESULTS: We assembled a panel of 385 non-aureus Staphylococcus isolates of 19 species from a combination of clinical sources and reference strains. We used a high-throughput crystal violet assay to assess the biofilm forming ability of all strains and assign distinct biofilm formation categories. We compared the prevalence of Pfam domains between the categories and used machine learning to identify amino acid 20-mers linked to biofilm formation. This identified some domains within proteins already linked to biofilm formation and important domains not previously linked to biofilm formation in staphylococci. RT-qPCR confirmed the expression of selected genes predicted to encode important domains within biofilms in Staphylococcus epidermidis. The prevalence and distribution of biofilm associated domains showed a link to phylogeny, suggesting different Staphylococcus species have independently evolved different mechanisms of biofilm production. CONCLUSIONS: This work has identified different routes to biofilm formation in diverse species of Staphylococcus and suggests independent evolution of biofilm has occurred multiple times across the genus. Understanding the mechanisms of biofilm formation in any given species is likely to require detailed study of relevant strains and the ability to generalise across the genus may be limited.

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GABAA receptors (γ-aminobutyric acid-gated receptors type A; GABAARs), the major structural and functional postsynaptic components of inhibitory synapses in the mammalian brain, belong to a family of GABA-gated Cl-/HCO3 - ion channels. They are assembled as heteropentamers from a family of subunits including: α (1-6), ß(1-3), γ(1-3), δ, ε, π, θ and ρ(1-3). GABAARs together with the postsynaptic adhesion protein Neuroligin 2 (NL2) and many other pre- and post-synaptic proteins guide the initiation and functional maturation of inhibitory GABAergic synapses. This study examined how GABAARs and NL2 interact with each other to initiate the formation of synapses. Two functionally distinct GABAAR subtypes, the synaptic type α2ß2γ2-GABAARs versus extrasynaptic type α4ß3δ-GABAARs were expressed in HEK293 cells alone or together with NL2 and co-cultured with striatal GABAergic medium spiny neurons to enable innervation of HEK293 cells by GABAergic axons. When expressed alone, only the synaptic α2ß2γ2-GABAARs induced innervation of HEK293 cells. However, when GABAARs were co-expressed with NL2, the effect on synapse formation exceeded the individual effects of these proteins indicating a synergistic interaction, with α2ß2γ2-GABAAR/NL2 showing a significantly greater synaptogenic activity than α4ß3δ-GABAAR/NL2 or NL2 alone. To investigate the molecular basis of this interaction, different combinations of GABAAR subunits and NL2 were co-expressed, and the degree of innervation and synaptic activity assessed, revealing a key role of the γ2 subunit. In biochemical assays, the interaction between NL2 and α2ß2γ2-GABAAR was established and mapped to the large intracellular domain of the γ2 subunit.

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Src homology 3 (SH3) domains play a critical role in mediating protein-protein interactions (PPIs) involved in cell proliferation, migration, and the cytoskeleton. Despite their abundance in the human proteome, the functions and molecular interactions of many SH3 domains remain unknown, and this is in part due to the lack of SH3-domain-specific reagents available for their study. Affimer proteins have been developed as affinity reagents targeting a diverse range of targets, including those involved in PPIs. In this study, Affimer proteins were isolated against both the N- and C-terminal SH3 domains (NSH3 and CSH3) of growth-factor-receptor-bound protein 2 (Grb2), an adapter protein that provides a critical link between cell surface receptors and Ras signalling pathways. Targeting the CSH3 alone for the inhibition of PPIs appeared sufficient for curtailing Ras signalling in mammalian cell lines stimulated with human epidermal growth factor (EGF), which conflicts with the notion that the predominant interactions with Ras activating Son of sevenless (SOS) occur via the NSH3 domain. This result supports a model in which allosteric mechanisms involved in Grb2-SOS1 interaction modulate Ras activation.

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Land plants (embryophytes) came about in a momentous evolutionary singularity: plant terrestrialization. This event marks not only the conquest of land by plants but also the massive radiation of embryophytes into a diverse array of novel forms and functions. The unique suite of traits present in the earliest land plants is thought to have been ushered in by a burst in genomic novelty. Here, we asked the question of how these bursts were possible. For this, we explored: (i) the initial emergence and (ii) the reshuffling of domains to give rise to hallmark environmental response genes of land plants. We pinpoint that a quarter of the embryophytic genes for stress physiology are specific to the lineage, yet a significant portion of this novelty arises not de novo but from reshuffling and recombining of pre-existing domains. Our data suggest that novel combinations of old genomic substrate shaped the plant terrestrialization toolkit, including hallmark processes in signalling, biotic interactions and specialized metabolism.

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BACKGROUND: One of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as "genetic constraint". Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes. METHODS: We aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues. RESULTS: We identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism. CONCLUSIONS: Grouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.

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Protein O-linked mannose (O-Man) glycosylation is an evolutionary conserved posttranslational modification that fulfills important biological roles during embryonic development. Three nonredundant enzyme families, POMT1/POMT2, TMTC1-4, and TMEM260, selectively coordinate the initiation of protein O-Man glycosylation on distinct classes of transmembrane proteins, including α-dystroglycan, cadherins, and plexin receptors. However, a systematic investigation of their substrate specificities is lacking, in part due to the ubiquitous expression of O-Man glycosyltransferases in cells, which precludes analysis of pathway-specific O-Man glycosylation on a proteome-wide scale. Here, we apply a targeted workflow for membrane glycoproteomics across five human cell lines to extensively map O-Man substrates and genetically deconstruct O-Man initiation by individual and combinatorial knockout of O-Man glycosyltransferase genes. We established a human cell library for the analysis of substrate specificities of individual O-Man initiation pathways by quantitative glycoproteomics. Our results identify 180 O-Man glycoproteins, demonstrate new protein targets for the POMT1/POMT2 pathway, and show that TMTC1-4 and TMEM260 pathways widely target distinct Ig-like protein domains of plasma membrane proteins involved in cell-cell and cell-extracellular matrix interactions. The identification of O-Man on Ig-like folds adds further knowledge on the emerging concept of domain-specific O-Man glycosylation which opens for functional studies of O-Man-glycosylated adhesion molecules and receptors.

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Heaps' or Herdan-Heaps' law is a linguistic law describing the relationship between the vocabulary/dictionary size (type) and word counts (token) to be a power-law function. Its existence in genomes with certain definition of DNA words is unclear partly because the dictionary size in genome could be much smaller than that in a human language. We define a DNA word as a coding region in a genome that codes for a protein domain. Using human chromosomes and chromosome arms as individual samples, we establish the existence of Heaps' law in the human genome within limited range. Our definition of words in a genomic or proteomic context is different from other definitions such as over-represented k-mers which are much shorter in length. Although an approximate power-law distribution of protein domain sizes due to gene duplication and the related Zipf's law is well known, their translation to the Heaps' law in DNA words is not automatic. Several other animal genomes are shown herein also to exhibit range-limited Heaps' law with our definition of DNA words, though with various exponents. When tokens were randomly sampled and sample sizes reach to the maximum level, a deviation from the Heaps' law was observed, but a quadratic regression in log-log type-token plot fits the data perfectly. Investigation of type-token plot and its regression coefficients could provide an alternative narrative of reusage and redundancy of protein domains as well as creation of new protein domains from a linguistic perspective.

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Identifying unknown functional properties of proteins is essential for understanding their roles in both health and disease states. The domain composition of a protein can reveal critical information in this context, as domains are structural and functional units that dictate how the protein should act at the molecular level. The expensive and time-consuming nature of wet-lab experimental approaches prompted researchers to develop computational strategies for predicting the functions of proteins. In this study, we proposed a new method called Domain2GO that infers associations between protein domains and function-defining gene ontology (GO) terms, thus redefining the problem as domain function prediction. Domain2GO uses documented protein-level GO annotations together with proteins' domain annotations. Co-annotation patterns of domains and GO terms in the same proteins are examined using statistical resampling to obtain reliable associations. As a use-case study, we evaluated the biological relevance of examples selected from the Domain2GO-generated domain-GO term mappings via literature review. Then, we applied Domain2GO to predict unknown protein functions by propagating domain-associated GO terms to proteins annotated with these domains. For function prediction performance evaluation and comparison against other methods, we employed Critical Assessment of Function Annotation 3 (CAFA3) challenge datasets. The results demonstrated the high potential of Domain2GO, particularly for predicting molecular function and biological process terms, along with advantages such as producing interpretable results and having an exceptionally low computational cost. The approach presented here can be extended to other ontologies and biological entities to investigate unknown relationships in complex and large-scale biological data. The source code, datasets, results, and user instructions for Domain2GO are available at https://github.com/HUBioDataLab/Domain2GO. Additionally, we offer a user-friendly online tool at https://huggingface.co/spaces/HUBioDataLab/Domain2GO, which simplifies the prediction of functions of previously unannotated proteins solely using amino acid sequences.

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A rapid increase in antimicrobial resistant bacterial infections around the world is causing a global health crisis. The Gram-negative bacterium Acinetobacter baumannii is categorized as a Priority 1 pathogen for research and development of new antimicrobials by the World Health Organization due to its numerous intrinsic antibiotic resistance mechanisms and ability to quickly acquire new resistance determinants. Specialized phage enzymes, called depolymerases, degrade the bacterial capsule polysaccharide layer and show therapeutic potential by sensitizing the bacterium to phages, select antibiotics, and serum killing. The functional domains responsible for the capsule degradation activity are often found in the tail fibers of select A. baumannii phages. To further explore the functional domains associated with depolymerase activity, tail-associated proteins of 71 sequenced and fully characterized phages were identified from published literature and analyzed for functional domains using InterProScan. Multisequence alignments and phylogenetic analyses were conducted on the domain groups and assessed in the context of noted halo formation or depolymerase characterization. Proteins derived from phages noted to have halo formation or a functional depolymerase, but no functional domain hits, were modeled with AlphaFold2 Multimer, and compared to other protein models using the DALI server. The domains associated with depolymerase function were pectin lyase-like (SSF51126), tailspike binding (cd20481), (Trans)glycosidases (SSF51445), and potentially SGNH hydrolases. These findings expand our knowledge on phage depolymerases, enabling researchers to better exploit these enzymes for therapeutic use in combating the antimicrobial resistance crisis.

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CATH (https://www.cathdb.info) classifies domain structures from experimental protein structures in the PDB and predicted structures in the AlphaFold Database (AFDB). To cope with the scale of the predicted data a new NextFlow workflow (CATH-AlphaFlow), has been developed to classify high-quality domains into CATH superfamilies and identify novel fold groups and superfamilies. CATH-AlphaFlow uses a novel state-of-the-art structure-based domain boundary prediction method (ChainSaw) for identifying domains in multi-domain proteins. We applied CATH-AlphaFlow to process PDB structures not classified in CATH and AFDB structures from 21 model organisms, expanding CATH by over 100%. Domains not classified in existing CATH superfamilies or fold groups were used to seed novel folds, giving 253 new folds from PDB structures (September 2023 release) and 96 from AFDB structures of proteomes of 21 model organisms. Where possible, functional annotations were obtained using (i) predictions from publicly available methods (ii) annotations from structural relatives in AFDB/UniProt50. We also predicted functional sites and highly conserved residues. Some folds are associated with important functions such as photosynthetic acclimation (in flowering plants), iron permease activity (in fungi) and post-natal spermatogenesis (in mice). CATH-AlphaFlow will allow us to identify many more CATH relatives in the AFDB, further characterising the protein structure landscape.

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Mowat-Wilson syndrome (MWS) is a rare genetic neurodevelopmental congenital disorder associated with various defects of the zinc finger E-box binding homeobox 2 (ZEB2) gene. The ZEB2 gene is autosomal dominant and encodes six protein domains including the SMAD-binding protein, which functions as a transcriptional corepressor involved in the conversion of neuroepithelial cells in early brain development and as a mediator of trophoblast differentiation. This review summarizes reported ZEB2 gene variants, their types, and frequencies among the 10 exons of ZEB2. Additionally, we summarized their corresponding encoded protein defects including the most common variant, c.2083 C>T in exon 8, which directly impacts the homeodomain (HD) protein domain. This single defect was found in 11% of the 298 reported patients with MWS. This review demonstrates that exon 8 encodes at least three of the six protein domains and accounts for 66% (198/298) of the variants identified. More than 90% of the defects were due to nonsense or frameshift changes. We show examples of protein modeling changes that occurred as a result of ZEB2 gene defects. We also report a novel pathogenic variant in exon 8 in a 5-year-old female proband with MWS. This review further explores other genes predicted to be interacting with the ZEB2 gene and their predicted gene-gene molecular interactions with protein binding effects on embryonic multi-system development such as craniofacial, spine, brain, kidney, cardiovascular, and hematopoiesis.

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Calcium (Ca2 +) homeostasis is essential in conducting various cellular processes including nerve transmission, muscular movement, and immune response. Changes in Ca2 + concentration in the cytoplasm are significant in bringing about various immune responses such as pathogen clearance and apoptosis. Various key players are involved in calcium homeostasis such as calcium binders, pumps, and channels. Sequence-based evolutionary information has recently been exploited to predict the biophysical behaviors of proteins, giving critical clues about their functionality. Ion channels are reportedly the first channels developed during evolution. Calcium homeostasis modulator protein 6 (CALHM6) is one such channel. Comprised of a single domain called Ca_hom_mod, CALHM6 is a stable protein interacting with various other proteins in calcium regulation. No previous attempt has been made to trace the exact evolutionary events in the domain of CALHM6, leaving plenty of room for exploring its evolution across a wide range of organisms. The current study aims to answer the questions by employing a computational-based strategy that used profile Hidden Markov Models (HMMs) to scan for the CALHM6 domain, integrated the data with a time-calibrated phylogenetic tree using BEAST and Mesquite, and visualized through iTOL. Around 4,000 domains were identified, and 14,000 domain gain, loss, and duplication events were observed at the end which also included various protein domains other than CALHM6. The data were analyzed concerning CALHM6 evolution as well as the domain gain, loss, and duplication of its interacting partners: Calpain, Vinculin, protein S100-A7, Thioredoxin, Peroxiredoxin, and Calmodulin-like protein 5. Duplication events of CALHM6 near higher eukaryotes showed its increasing complexity in structure and function. This in-silico phylogenetic approach applied to trace the evolution of CALHM6 was an effective approach to get a better understanding of the protein CALHM6.

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IMPORTANCE: We found that in contrast to the best-studied model organisms, such as Escherichia coli and Bacillus subtilis, most bacterial and archaeal species have a CheA protein with a different domain composition. We report variations in CheA architecture, such as domain duplication and acquisition as well as class-specific domain composition. Our results will be of interest to those working on signal transduction in bacteria and archaea and lay the foundation for experimental studies.

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La ivermectina demostró importantes acciones antivirales ante varios virus con genoma de ARN, inclusive contra el SARS-CoV-2. Este fármaco inhibe la actividad del heterodímero importina α/ß1, sin embargo, se desconoce los blancos específicos de interacción de la molécula. Objetivos: analizar in silico los blancos de interacción de la ivermectina en interacción con la estructura de la importina α humana, utilizando la estrategia del acoplamiento molecular. Métodos: se realizaron simulaciones del acoplamiento utilizando un modelo semiflexible y el algoritmo Broyden-Fletcher-Goldfarb-Shanno entre las estructuras de ivermectina y la importina α. Resultados: los datos obtenidos revelan una mayor afinidad de interacción de la ivermectina a la región mayor de unión (armadillo ARM2-ARM4) de las importinas α humanas, con energías de unión favorables de -9,5 a -8,0 kcal.mol-1. Los aminoácidos activos de importancia en las uniones fueron el Triptófano, Asparagina y Arginina, los cuales también son fundamentales para el reconocimiento de secuencias NLS (secuencias de localización nuclear) de las proteínas virales. También se registró afinidades por los dominios H1-ARM5, H2-ARM6 y H2-ARM7, con energía de unión de -7,5 kcal.mol-1. Conclusiones: los hallazgos demuestran que la ivermectina presenta afinidades de unión favorables a la región mayor de unión (ARM2-ARM4) de las importinas a el cual es un sitio importante de unión a proteínas virales.

Ivermectin has demonstrated significant antiviral actions against several RNA-genome viruses, including SARS-CoV-2. This drug inhibits the activity of the α/ß1 importin heterodimer; however, the specific interaction targets of the molecule are unknown yet. Objectives: to analyze in silico the interaction targets of ivermectin interacting with the human α-importin structure using the molecular docking strategy. Methods: simulations of the molecular docking were carried out using a semi-flexible model and the Broyden-Fletcher-Goldfarb- Shanno algorithm between the structures of ivermectin and importin α. Results: data obtained reveal a higher interaction affinity of ivermectin to the major binding region (armadillo ARM2-ARM4) of human importins α, with favorable binding energies of -9,5 to -8,0 kcal.mol-1. The active amino acids of importance in the bindings were Tryptophan, Asparagine and Arginine, which are also critical for the recognition of NLS sequences (nuclear location sequences) of viral proteins. Affinities for H1-ARM5, H2-ARM6 and H2-ARM7 domains were also recorded, with binding energy of -7,5 kcal.mol-1. Conclusions: the findings demonstrate that ivermectin exhibits favorable binding affinities to the major binding region (ARM2-ARM4) of importins a which is an important viral protein binding site.

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IMPORTANCE: Short linear motifs (SLiMs) are 3-10 amino acid long binding motifs in intrinsically disordered protein regions (IDRs) that serve as ubiquitous protein-protein interaction modules in eukaryotic cells. Through molecular mimicry, viruses hijack these sequence motifs to control host cellular processes. It is thought that the small size of SLiMs and the high mutation frequencies of viral IDRs allow rapid host adaptation. However, a salient characteristic of RNA viruses, due to high replication errors, is their obligate existence as mutant swarms. Taking advantage of the uniquely large genomic database of SARS-CoV-2, here, we analyze the role of sequence diversity in the presentation of SLiMs, focusing on the highly abundant, multi-functional nucleocapsid protein. We find that motif mimicry is a highly dynamic process that produces an abundance of motifs transiently present in subsets of mutant species. This diversity allows the virus to efficiently explore eukaryotic motifs and evolve the host-virus interface.

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Background: Genomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Computational approaches have been aiding the work in this field by modeling and analyzing the mutational landscape. However, new approaches are required, especially for accurate representation and data-centric analysis of sequence variations. Method: In this study, we propose ASCARIS (Annotation and StruCture-bAsed RepresentatIon of Single amino acid variations), a method for the featurization (i.e., quantitative representation) of single amino acid variations (SAVs), which could be used for a variety of purposes, such as predicting their functional effects or building multi-omics-based integrative models. ASCARIS utilizes the direct and spatial correspondence between the location of the SAV on the sequence/structure and 30 different types of positional feature annotations (e.g., active/lipidation/glycosylation sites; calcium/metal/DNA binding, inter/transmembrane regions, etc.), along with structural features and physicochemical properties. The main novelty of this method lies in constructing reusable numerical representations of SAVs via functional annotations. Results: We statistically analyzed the relationship between these features and the consequences of variations and found that each carries information in this regard. To investigate potential applications of ASCARIS, we trained variant effect prediction models that utilize our SAV representations as input. We carried out an ablation study and a comparison against the state-of-the-art methods and observed that ASCARIS has a competing and complementary performance against widely-used predictors. ASCARIS can be used alone or in combination with other approaches to represent SAVs from a functional perspective. ASCARIS is available as a programmatic tool at https://github.com/HUBioDataLab/ASCARIS and as a web-service at https://huggingface.co/spaces/HUBioDataLab/ASCARIS.

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The Candidate Phyla Radiation (CPR) was found to harbor a vast repertoire of genes encoding for enzymes with potential antibiotic resistance activity. Among these, as many as 3349 genes were predicted in silico to contain a metallo-beta-lactamase-like (MBL-like) fold. These proteins were subject to an in silico functional characterization by comparing their protein profiles (presence/absence of conserved protein domains) to other MBLs, including 24 already expressed in vitro, along with those of the beta-lactamase database (BLDB) (n = 761). The sequence similarity network (SSN) was then used to predict the functional clusters of CPR MBL-like sequences. Our findings showed that CPR MBL-like sequences were longer and more diverse than bacterial MBL sequences, with a high content of functional domains. Most CPR MBL-like sequences did not show any SSN connectivity with expressed MBLs, indicating the presence of many potential, yet unidentified, functions in CPR. In conclusion, CPR was shown to have many protein functions and a large sequence variability of MBL-like folds, exceeding all known MBLs. Further experimental and evolutionary studies of this superfamily of hydrolyzing enzymes are necessary to illustrate their functional annotation, origin, and expansion for adaptation or specialization within a given niche or compared to a specific substrate.

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Background: Functionally related genes are well known to be often grouped in close vicinity in the genomes, particularly in prokaryotes. Notwithstanding the diverse evolutionary mechanisms leading to this phenomenon, it can be used to predict functions of uncharacterized genes. Methods: Here, we provide a simple but robust statistical approach that leverages the vast amounts of genomic data available today. Considering a protein domain as a functional unit, one can explore other functional units (domains) that significantly often occur within the genomic neighborhoods of the queried domain. This analysis can be performed across different taxonomic levels. Provisions can also be made to correct for the uneven sampling of the taxonomic space by genomic sequencing projects that often focus on large numbers of very closely related strains, e.g., pathogenic ones. To this end, an optional procedure for averaging occurrences within subtaxa is available. Results: Several examples show this approach can provide useful functional predictions for uncharacterized gene families, and how to combine this information with other approaches. The method is made available as a web server at http://bioinfo.sggw.edu.pl/neighborhood_analysis.

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Duck Tembusu virus (DTMUV) causes severe reduction in egg production and neurological symptoms in ducklings. Vaccination is the primary measure used to prevent DTMUV infections. In this study, self-assembled nanoparticles with the E protein domain III of DTMUV, using ferritin as a carrier (EDⅢ-RFNp), were prepared using a prokaryotic expression system. Ducks were intramuscularly vaccinated with EDⅢ-RFNp, EDⅢ protein, an inactivated vaccine HB strain (InV-HB), and PBS. At 0, 4, and 6 weeks post-primary vaccination, the EDIII protein-specific antibody titre, IL-4, and IFN-γ concentrations in serum were determined by ELISA, and neutralising antibodies titres in sera were determined by virus neutralising assay. Peripheral blood lymphocytes proliferation was determined by CCK-8 kit. Following challenge with the virulent DTMUV strain, the clinical signals and survival rate of the vaccinated ducks were recorded, and DTMUV RNA levels in the blood and tissues of the surviving ducks were determined by real-time quantitative RT-PCR. The near-spherical EDⅢ-RFNp nanoparticles with 13.29 ± 1.43 nm diameter were observed by transmission electron microscope. At 4 and 6 weeks post-primary vaccination, special and Virus neutralisation (VN) antibodies, lymphocyte proliferation (stimulator index, SI), and concentrations of IL-4 and IFN-γ in the EDⅢ-RFNp group were significantly higher than in the EDⅢ and PBS groups. In the DTMUV virulent strain challenge test, the EDⅢ-RFNp-vaccinated ducks showed milder clinical signs and higher survival rates than EDⅢ- and PBS-vaccinated ducks. The DTMUV RNA levels in the blood and tissues of EDⅢ-RFNp-vaccinated ducks were significantly lower than those in EDⅢ- and PBS-vaccinated ducks. Additionally, the EDⅢ protein-special and VN antibodies, SI value, and concentration of IL-4 and IFN-γ in the InV-HB group was significantly higher than that of the PBS group at 4 and 6 weeks post-primary vaccination. InV-HB provided more efficient protection than PBS based on a higher survival rate, milder signals, and lower levels of the DTMUV virus in the blood and tissues. These results indicated that EDⅢ-RFNp effectively protected ducks against DTMUV challenge and could be a vaccine candidate to prevent DTMUV infection.

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SASH1 is a scaffold protein with context-dependent biological functions in cell adhesion, tumor metastasis, lung development, and pigmentation. As a member of the SLy protein family, it contains the conserved SLY, SH3, and SAM domains. The 19 kDa SLY domain harbors over 70% of the SASH1 variants associated with pigmentation disorders. However, its solution structure or dynamics have not been investigated yet, and its exact position in the sequence is not clearly defined. Based on the bioinformatic and experimental evidence, we propose renaming this region to the SLy Proteins Associated Disordered Region (SPIDER) and defining the exact position to be amino acids 400-554 of SASH1. We have previously identified a variant in this region linked to a pigmentation disorder, S519N. Here, we used a novel deuteration technique, a suite of TROSY-based 3D NMR experiments, and a high-quality HNN to obtain near complete solution backbone assignment of SASH1's SPIDER. A comparison with the chemical shifts of non-variant (S519) SPIDER shows that the S519N substitution does not alter the free form solution structural propensities of SPIDER. This assignment is the first step to characterize the role of SPIDER in SASH1-mediated cellular functions and provides a model for the future study of sister SPIDER domains in the SLy protein family.

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