3\',5\'-cyclic uridine monophosphate (cUMP) and 3\',5\'-cyclic cytidine monophosphate (cCMP) have been established as bacterial second messengers in the phage defense system, named pyrimidine cyclase system for anti-phage resistance (Pycsar). This system consists of a pyrimidine cyclase and a cyclic pyrimidine receptor protein. However, the molecular mechanism underlying cyclic pyrimidine synthesis and recognition remains unclear. Herein, we determine the crystal structures of a uridylate cyclase and a cytidylate cyclase, revealing the conserved residues for cUMP and cCMP production, respectively. In addition, a distinct zinc-finger motif of the uridylate cyclase is identified to confer substantial resistance against phage infections. Furthermore, structural characterization of cUMP receptor protein PycTIR provides clear picture of specific cUMP recognition and identifies a conserved N-terminal extension that mediates PycTIR oligomerization and activation. Overall, our results contribute to the understanding of cyclic pyrimidine-mediated bacterial defense.

Protein SUMOylation is a prevalent stress-response posttranslational modification crucial for maintaining cellular homeostasis. Herein, we report that protein SUMOylation modulates cellular signaling mediated by cAMP, an ancient and universal stress-response second messenger. We identify K561 as a primary SUMOylation site in exchange protein directly activated by cAMP (EPAC1) via site-specific mapping of SUMOylation using mass spectrometry. Sequence and site-directed mutagenesis analyses reveal that a functional SUMO-interacting motif in EPAC1 is required for the binding of SUMO-conjugating enzyme UBC9, formation of EPAC1 nuclear condensate, and EPAC1 cellular SUMOylation. Heat shock-induced SUMO modification of EPAC1 promotes Rap1/2 activation in a cAMP-independent manner. Structural modeling and molecular dynamics simulation studies demonstrate that SUMO substituent on K561 of EPAC1 promotes Rap1 interaction by increasing the buried surface area between the SUMOylated receptor and its effector. Our studies identify a functional SUMOylation site in EPAC1 and unveil a novel mechanism in which SUMOylation of EPAC1 leads to its autonomous activation. The findings of SUMOylation-mediated activation of EPAC1 not only provide new insights into our understanding of cellular regulation of EPAC1 but also will open up a new field of experimentation concerning the cross-talk between cAMP/EPAC1 signaling and protein SUMOylation, two major cellular stress response pathways, during cellular homeostasis.

The optimization of therapeutic antibodies through traditional techniques, such as candidate screening via hybridoma or phage display, is resource-intensive and time-consuming. In recent years, computational and artificial intelligence-based methods have been actively developed to accelerate and improve the development of therapeutic antibodies. In this study, we developed an end-to-end sequence-based deep learning model, termed AttABseq, for the predictions of the antigen-antibody binding affinity changes connected with antibody mutations. AttABseq is a highly efficient and generic attention-based model by utilizing diverse antigen-antibody complex sequences as the input to predict the binding affinity changes of residue mutations. The assessment on the three benchmark datasets illustrates that AttABseq is 120% more accurate than other sequence-based models in terms of the Pearson correlation coefficient between the predicted and experimental binding affinity changes. Moreover, AttABseq also either outperforms or competes favorably with the structure-based approaches. Furthermore, AttABseq consistently demonstrates robust predictive capabilities across a diverse array of conditions, underscoring its remarkable capacity for generalization across a wide spectrum of antigen-antibody complexes. It imposes no constraints on the quantity of altered residues, rendering it particularly applicable in scenarios where crystallographic structures remain unavailable. The attention-based interpretability analysis indicates that the causal effects of point mutations on antibody-antigen binding affinity changes can be visualized at the residue level, which might assist automated antibody sequence optimization. We believe that AttABseq provides a fiercely competitive answer to therapeutic antibody optimization.

The potential role of the juvenile hormone receptor gene (methoprene-tolerant, Met) in reproduction of Coccinella septempunctata L. (Coleoptera: Coccinellidae)(Coleoptera: Coccinellidae), was investigated by cloning, analyzing expression profiles by quantitative real-time PCR, and via RNA interference (RNAi). CsMet encoded a 1518-bp open reading frames with a predicted protein product of 505 amino acids; the latter contained 2 Per-Arnt-Sim repeat profile at amino acid residues 30-83 and 102-175. CsMet was expressed in different C. septempunctata larvae developmental stages and was most highly expressed in third instar. CsMet expression in female adults gradually increased from 20 to 30 d, and expression levels at 25 and 30 d were significantly higher than levels at 1-15 d. CsMet expression in 20-d-old male adults was significantly higher than in males aged 1-15 d. CsMet expression levels in fat body tissues of male and female adults were significantly higher than expression in the head, thorax, and reproductive system. At 5 and 10 d after CsMet-dsRNA injection, CsMet expression was significantly lower than the controls by 75.05% and 58.38%, respectively. Ovary development and vitellogenesis in C. septempunctata injected with CsMet-dsRNA were significantly delayed and fewer mature eggs were produced. This study provides valuable information for the large-scale rearing of C. septempunctata.

The third complementary-determining regions of the heavy-chain (CDR3H) variable regions (VH) of some cattle antibodies are highly extended, consisting of 48 or more residues. These `ultralong\' CDR3Hs form β-ribbon stalks that protrude from the surface of the antibody with a disulfide cross-linked knob region at their apex that dominates antigen interactions over the other CDR loops. The structure of the Fab fragment of a naturally paired bovine ultralong antibody (D08), identified by single B-cell sequencing, has been determined to 1.6 Å resolution. By swapping the D08 native light chain with that of an unrelated antigen-unknown ultralong antibody, it is shown that interactions between the CDR3s of the variable domains potentially affect the fine positioning of the ultralong CDR3H; however, comparison with other crystallographic structures shows that crystalline packing is also a major contributor. It is concluded that, on balance, the exact positioning of ultralong CDR3H loops is most likely to be due to the constraints of crystal packing.

Major vault protein (MVP) is the main component of the vault complex, which is a highly conserved ribonucleoprotein complex found in most eukaryotic organisms. MVP or vaults have previously been found to be overexpressed in multidrug-resistant cancer cells and implicated in various cellular processes such as cell signaling and innate immunity. The precise function of MVP is, however, poorly understood and its expression and probable function in lower eukaryotes are not well characterized. In this study, we report that the Atlantic salmon louse expresses three full-length MVP paralogues (LsMVP1-3). Furthermore, we extended our search and identified MVP orthologues in several other ecdysozoan species. LsMVPs were shown to be expressed in various tissues at both transcript and protein levels. In addition, evidence for LsMVP to assemble into vaults was demonstrated by performing differential centrifugation. LsMVP was found to be highly expressed in cement, an extracellular material produced by a pair of cement glands in the adult female salmon louse. Cement is important for the formation of egg strings that serve as protective coats for developing embryos. Our results imply a possible novel function of LsMVP as a secretory cement protein. LsMVP may play a role in structural or reproductive functions, although this has to be further investigated.

The primary objective of analyzing the data obtained in a mass spectrometry-based proteomic experiment is peptide and protein identification, or correct assignment of the tandem mass spectrum to one amino acid sequence. Comparison of empirical fragment spectra with the theoretical predicted one or matching with the collected spectra library are commonly accepted strategies of proteins identification and defining of their amino acid sequences. Although these approaches are widely used and are appreciably efficient for the well-characterized model organisms or measured proteins, they cannot detect novel peptide sequences that have not been previously annotated or are rare. This study presents PowerNovo tool for de novo sequencing of proteins using tandem mass spectra acquired in a variety of types of mass analyzers and different fragmentation techniques. PowerNovo involves an ensemble of models for peptide sequencing: model for detecting regularities in tandem mass spectra, precursors, and fragment ions and a natural language processing model, which has a function of peptide sequence quality assessment and helps with reconstruction of noisy sequences. The results of testing showed that the performance of PowerNovo is comparable and even better than widely utilized PointNovo, DeepNovo, Casanovo, and Novor packages. Also, PowerNovo provides complete cycle of processing (pipeline) of mass spectrometry data and, along with predicting the peptide sequence, involves the peptide assembly and protein inference blocks.

UNASSIGNED: The integration of diagnostic methods holds promise for advancing the surveillance of malaria transmission in both endemic and non-endemic regions. Serological assays emerge as valuable tools to identify and delimit malaria transmission, serving as a complementary method to rapid diagnostic tests (RDT) and thick smear microscopy. Here, we evaluate the potential of antibodies directed against peptides encompassing the entire amino acid sequence of the PvMSP-1 Sal-I strain as viable serological biomarkers for P. vivax exposure.
UNASSIGNED: We screened peptides encompassing the complete amino acid sequence of the Plasmodium vivax Merozoite Surface Protein 1 (PvMSP-1) Sal-I strain as potential biomarkers for P. vivax exposure. Here, immunodominant peptides specifically recognized by antibodies from individuals infected with P. vivax were identified using the SPOT-synthesis technique followed by immunoblotting. Two 15-mer peptides were selected based on their higher and specific reactivity in immunoblotting assays. Subsequently, peptides p70 and p314 were synthesized in soluble form using SPPS (Solid Phase Peptide Synthesis) and tested by ELISA (IgG, and subclasses).
UNASSIGNED: This study unveils the presence of IgG antibodies against the peptide p314 in most P. vivax-infected individuals from the Brazilian Amazon region. In silico B-cell epitope prediction further supports the utilization of p314 as a potential biomarker for evaluating malaria transmission, strengthened by its amino acid sequence being part of a conserved block of PvMSP-1. Indeed, compared to patients infected with P. falciparum and uninfected individuals never exposed to malaria, P. vivax-infected patients have a notably higher recognition of p314 by IgG1 and IgG3.

Understanding a protein\'s function based solely on its amino acid sequence is a crucial but intricate task in bioinformatics. Traditionally, this challenge has proven difficult. However, recent years have witnessed the rise of deep learning as a powerful tool, achieving significant success in protein function prediction. Their strength lies in their ability to automatically learn informative features from protein sequences, which can then be used to predict the protein\'s function. This study builds upon these advancements by proposing a novel model: CNN-CBAM+BiGRU. It incorporates a Convolutional Block Attention Module (CBAM) alongside BiGRUs. CBAM acts as a spotlight, guiding the CNN to focus on the most informative parts of the protein data, leading to more accurate feature extraction. BiGRUs, a type of Recurrent Neural Network (RNN), excel at capturing long-range dependencies within the protein sequence, which are essential for accurate function prediction. The proposed model integrates the strengths of both CNN-CBAM and BiGRU. This study\'s findings, validated through experimentation, showcase the effectiveness of this combined approach. For the human dataset, the suggested method outperforms the CNN-BIGRU+ATT model by +1.0 % for cellular components, +1.1 % for molecular functions, and +0.5 % for biological processes. For the yeast dataset, the suggested method outperforms the CNN-BIGRU+ATT model by +2.4 % for the cellular component, +1.2 % for molecular functions, and +0.6 % for biological processes.

Protein tyrosine phosphatase non-receptor type 21 (PTPN21) is a cytosolic protein tyrosine phosphatase that regulates cell growth and invasion. Due to its oncogenic properties, PTPN21 has recently emerged as a potential therapeutic target for cancer. In this study, the three-dimensional structure of the PTPN21 FERM domain was determined at 2.1 Å resolution by X-ray crystallography. The crystal structure showed that this domain harbors canonical FERM folding and consists of three subdomains that are tightly packed via highly conserved intramolecular hydrophobic interactions. Consistent with this, the PTPN21 FERM domain shares high structural homology with several other FERM domains. Moreover, structural superimposition demonstrated two putative protein-binding sites of the PTPN21 FERM domain, which are presumed to be associated with interaction with its binding partner, kinesin family member 1C. Thus, these data suggest that the FERM domain of PTPN21 serves as a module that mediates protein-protein interaction, like other FERM domains.