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Protein translation initiation is a conserved process involving many proteins acting in concert. The 13 subunit eukaryotic initiation factor 3 (eIF3) complex is essential for assembly of the pre-initiation complex that scans mRNA and positions ribosome at the initiation codon. We previously reported that a gain-of-function (gf) mutation affecting the G subunit of the Caenorhabditis elegans eIF3 complex, eif-3.g(gf), selectively modulates protein translation in the ventral cord cholinergic motor neurons. Here, through unbiased genetic suppressor screening, we identified that the gene lin-66 mediates eif-3.g(gf)-dependent protein translation in motor neurons. LIN-66 is composed largely of low-complexity amino acid sequences with unknown functional domains. We combined bioinformatics analysis with in vivo functional dissection and identified a cold-shock domain in LIN-66 critical for its function. In cholinergic motor neurons, LIN-66 shows a close association with EIF-3.G in the cytoplasm. The low-complexity amino acid sequences of LIN-66 modulate its subcellular pattern. As cold-shock domains function broadly in RNA regulation, we propose that LIN-66 mediates stimulus-dependent protein translation by facilitating the interaction of mRNAs with EIF-3.G.

Computational protein design is advancing rapidly. Here we describe efficient routes starting from validated parallel and antiparallel peptide assemblies to design two families of α-helical barrel proteins with central channels that bind small molecules. Computational designs are seeded by the sequences and structures of defined de novo oligomeric barrel-forming peptides, and adjacent helices are connected by loop building. For targets with antiparallel helices, short loops are sufficient. However, targets with parallel helices require longer connectors; namely, an outer layer of helix-turn-helix-turn-helix motifs that are packed onto the barrels. Throughout these computational pipelines, residues that define open states of the barrels are maintained. This minimizes sequence sampling, accelerating the design process. For each of six targets, just two to six synthetic genes are made for expression in Escherichia coli. On average, 70% of these genes express to give soluble monomeric proteins that are fully characterized, including high-resolution structures for most targets that match the design models with high accuracy.

Antigenically sequence variable M proteins of the major bacterial pathogen Streptococcus pyogenes (Strep A) are responsible for recruiting human C4b-binding protein (C4BP) to the bacterial surface, which enables Strep A to evade destruction by the immune system. The most sequence divergent portion of M proteins, the hypervariable region (HVR), is responsible for binding C4BP. Structural evidence points to the conservation of two C4BP-binding sequence patterns (M2 and M22) in the HVR of numerous M proteins, with this conservation applicable to vaccine immunogen design. These two patterns, however, only partially explain C4BP binding by Strep A. Here, we identified several M proteins that lack these patterns but still bind C4BP and determined the structures of two, M68 and M87 HVRs, in complex with a C4BP fragment. Mutagenesis of these M proteins led to the identification of amino acids that are crucial for C4BP binding, enabling formulation of new C4BP-binding patterns. Mutagenesis was also carried out on M2 and M22 proteins to refine or generate experimentally grounded C4BP-binding patterns. The M22 pattern was the most prevalent among M proteins, followed by the M87 and M2 patterns, while the M68 pattern was rare. These patterns, except for M68, were also evident in numerous M-like Enn proteins. Binding of C4BP via these patterns to Enn proteins was verified. We conclude that C4BP-binding patterns occur frequently in Strep A strains of differing M types, being present in their M or Enn proteins, or frequently both, providing further impetus for their use as vaccine immunogens.

Transmembrane (TM) domains as simple as a single span can perform complex biological functions using entirely lipid-embedded chemical features. Computational design has the potential to generate custom tool molecules directly targeting membrane proteins at their functional TM regions. Thus far, designed TM domain-targeting agents have been limited to mimicking the binding modes and motifs of natural TM interaction partners. Here, we demonstrate the design of de novo TM proteins targeting the erythropoietin receptor (EpoR) TM domain in a custom binding topology competitive with receptor homodimerization. The TM proteins expressed in mammalian cells complex with EpoR and inhibit erythropoietin-induced cell proliferation. In vitro, the synthetic TM domain complex outcompetes EpoR homodimerization. Structural characterization reveals that the complex involves the intended amino acids and agrees with our designed molecular model of antiparallel TM helices at 1:1 stoichiometry. Thus, membrane protein TM regions can now be targeted in custom-designed topologies.

SLC22A10 is an orphan transporter with unknown substrates and function. The goal of this study is to elucidate its substrate specificity and functional characteristics. In contrast to orthologs from great apes, human SLC22A10, tagged with green fluorescent protein, is not expressed on the plasma membrane. Cells expressing great ape SLC22A10 orthologs exhibit significant accumulation of estradiol-17β-glucuronide, unlike those expressing human SLC22A10. Sequence alignments reveal a proline at position 220 in humans, which is a leucine in great apes. Replacing proline with leucine in SLC22A10-P220L restores plasma membrane localization and uptake function. Neanderthal and Denisovan genomes show proline at position 220, akin to modern humans, indicating functional loss during hominin evolution. Human SLC22A10 is a unitary pseudogene due to a fixed missense mutation, P220, while in great apes, its orthologs transport sex steroid conjugates. Characterizing SLC22A10 across species sheds light on its biological role, influencing organism development and steroid homeostasis.

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, SARS-CoV-2 variants capable of breakthrough infections have attracted global attention. These variants have significant mutations in the receptor-binding domain (RBD) of the spike protein and the membrane (M) protein, which may imply an enhanced ability to evade immune responses. In this study, an examination of co-mutations within the spike RBD and their potential correlation with mutations in the M protein was conducted. The EVmutation method was utilized to analyze the distribution of the mutations to elucidate the relationship between the mutations in the spike RBD and the alterations in the M protein. Additionally, the Sequence-to-Sequence Transformer Model (S2STM) was employed to establish mapping between the amino acid sequences of the spike RBD and M proteins, offering a novel and efficient approach for streamlined sequence analysis and the exploration of their interrelationship. Certain mutations in the spike RBD, G339D-S373P-S375F and Q493R-Q498R-Y505, are associated with a heightened propensity for inducing mutations at specific sites within the M protein, especially sites 3 and 19/63. These results shed light on the concept of mutational synergy between the spike RBD and M proteins, illuminating a potential mechanism that could be driving the evolution of SARS-CoV-2.

Vocal production learning (vocal learning) is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

Protein structure prediction (PSP) is the prediction of the three‐dimensional (3D) folding of a protein (its tertiary structure) starting from its amino acid sequence (its primary structure). The state of the art in PSP is achieved by deep learning pipelines that require several input features extracted from amino acid sequences. It has been demonstrated that features that grasp the relative orientation of amino acids positively impact the prediction accuracy of the 3D coordinates of atoms in the protein backbone. In this paper, we demonstrate the relevance of geometric algebra (GA) in instantiating orientational features for PSP problems. We do so by proposing two novel GA‐based metrics which contain information on relative orientations of amino acid residues. We then employ these metrics as additional input features to a graph transformer (GT) architecture to aid the prediction of the 3D coordinates of a protein, and compare them to classical angle‐based metrics. We show how our GA features yield comparable results to angle maps in terms of accuracy of the predicted coordinates. This is despite being constructed from less initial information about the protein backbone. The features are also fewer and more informative and can be (i) closely associated to protein secondary structures and (ii) more easily predicted compared to angle maps. We hence deduce that GA can be employed as a tool to simplify the modeling of protein structures and pack orientational information in a more natural and meaningful way. [ABSTRACT FROM AUTHOR]

Biocatalysts that are eco-friendly, sustainable, and highly specific have great potential for applications in the production of fine chemicals, food, detergents, biofuels, pharmaceuticals, and more. However, due to factors such as low activity, narrow substrate scope, poor thermostability, or incorrect selectivity, most natural enzymes cannot be directly used for large-scale production of the desired products. To overcome these obstacles, protein engineering methods have been developed over decades and have become powerful and versatile tools for adapting enzymes with improved catalytic properties or new functions. The vastness of the protein sequence space makes screening a bottleneck in obtaining advantageous mutated enzymes in traditional directed evolution. In the realm of mathematics, there are two major constraints in the protein sequence space: (1) the number of residue substitutions (M); and (2) the number of codons encoding amino acids as building blocks (N). This feature review highlights protein engineering strategies to reduce screening efforts from two dimensions by reducing the numbers M and N, and also discusses representative seminal studies of rationally engineered natural enzymes to deliver new catalytic functions. [ABSTRACT FROM AUTHOR]

The N-truncation of amyloid beta (Aβ) peptides could lead to peptide sequences with the histidine residue at the second and third positions, creating His-2 and His-3 motifs, known as high-affinity Cu(II) binding sites. In such complexes, the Cu(II) ion is arrested in a rigid structure of a square-planar arrangement of nitrogen donors, which highly limits its susceptibility to Cu(II) reduction. Cu(II) reduction fuels the Cu(II)/Cu(I) redox cycle, which is engaged in the production of reactive oxygen species (ROS). Employing electrochemical techniques, cyclic voltammetry (CV) and differential pulse voltammetry (DPV), together with UV–vis spectroscopy, we showed that low-molecular-weight (LMW) substances, such as imidazole, histamine, and histidine, could enhance the redox activity of Cu(II) complexes of three models of N-truncated Aβ peptides, Aβ4–9, Aβ5–9, and Aβ12–16, identifying three main mechanisms. LMW compounds could effectively compete with Aβ peptides for Cu(II) ions, forming Cu(II)/LMW species, which are more prone to Cu(II) reduction. LMW substances could also shift the equilibrium between the Cu(II)/Aβ species towards the species with higher susceptibility to Cu(II) reduction. Finally, the presence of LMW molecules could promote Cu(I) reoxidation in ternary Cu(II)/Aβ/LMW systems. The obtained results raise further questions regarding the Cu(II) redox activity in Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Statistical analysis of multiple sequence alignments of homologous proteins has revealed groups of coevolving amino acids called sectors. These groups of amino-acid sites feature collective correlations in their amino-acid usage, and they are associated to functional properties. Modeling showed that nonlinear selection on an additive functional trait of a protein is generically expected to give rise to a functional sector. These modeling results motivated a principled method, called ICOD, which is designed to identify functional sectors, as well as mutational effects, from sequence data. However, a challenge for all methods aiming to identify sectors from multiple sequence alignments is that correlations in amino-acid usage can also arise from the mere fact that homologous sequences share common ancestry, i.e. from phylogeny. Here, we generate controlled synthetic data from a minimal model comprising both phylogeny and functional sectors. We use this data to dissect the impact of phylogeny on sector identification and on mutational effect inference by different methods. We find that ICOD is most robust to phylogeny, but that conservation is also quite robust. Next, we consider natural multiple sequence alignments of protein families for which deep mutational scan experimental data is available. We show that in this natural data, conservation and ICOD best identify sites with strong functional roles, in agreement with our results on synthetic data. Importantly, these two methods have different premises, since they respectively focus on conservation and on correlations. Thus, their joint use can reveal complementary information. Author summary: Proteins perform crucial functions in the cell. The biological function of a protein is encoded in its amino-acid sequence. Natural selection acts at the level of function, while mutations arise randomly on sequences. In alignments of sequences of homologous proteins, which share common ancestry and common function, the amino acid usages at different sites can be correlated due to functional constraints. In particular, groups of collectively correlated amino acids, termed sectors, tend to emerge due to selection on functional traits. However, correlations can also arise from the shared evolutionary history of homologous proteins, even without functional constraints. This may obscure the inference of functional sectors. By analyzing controlled synthetic data as well as natural protein sequence data, we show that two very different methods allow to identify sectors and mutational effects in a way that is most robust to phylogeny. We suggest that considering both of these methods allows a better identification of functionally important sites from protein sequences. These results have potential impact on the design of new functional sequences. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusion In contrast to sublingual immunotherapy (SLIT) with recombinant Mal d 1 (rMal d 1‐SLIT), SLIT with rBet v 1 (rBet v 1‐SLIT) induced Mal d 1‐cross‐reactive antibodies without IgE‐blocking activity. To elucidate whether the development of cross‐protective IgG responses depends on the degree of molecular identity of allergens we compared the cross‐reactivity, cross‐blocking activity, and affinity of SLIT‐induced antibodies with allergens of varying amino acid sequence identities to Bet v 1 and Mal d 1, namely Cor a 1.04 (hazelnut), Pru av 1 (cherry), and Dau c 1 (carrot).Allergen‐specific antibodies were quantified by ELISA. IgE blocking was analyzed by inhibition of allergen‐induced basophil activation and IgE‐facilitated allergen‐presentation to T cells. The affinity of SLIT‐induced antibodies was studied by acidic dissociation ELISA and competition ELISA. Identical surface areas on allergens were predicted using an in‐house designed script based on structural alignments.rBet v 1‐SLIT‐induced IgG antibodies cross‐reacted with all allergens except Dau c 1. rMal d 1‐SLIT‐induced antibodies predominantly cross‐reacted with Pru av 1 and displayed significantly higher IgE blocking to Pru av 1 than rBet v 1‐SLIT‐induced antibodies. rMal d 1‐SLIT‐induced IgG1 showed higher affinity to Mal d 1 and Pru av 1. Surface analysis revealed 84% identical area on Mal d 1 and Pru av 1. Furthermore, we identified two surface areas potentially containing epitopes present on these allergens and absent on Bet v 1.In summary, our findings suggest that a relatively high threshold of similarity is required to establish effective cross‐blocking antibodies to related allergens. Apparently, the structural identity between Bet v 1 and Mal d 1 is below this threshold. Therefore, this study may explain why immunotherapy with birch pollen allergen often fails to reduce birch pollen‐related apple allergy. [ABSTRACT FROM AUTHOR]

In the current study, the ability of an indigenous marine Actinomycete Nocardiopsis dassonvillei (NCIM 5124) to degrade poly(3-hydroxybutyrate)-PHB was examined. From the whole genome sequencing data of the organism, information regarding the PHB depolymerase gene and amino acid sequence (Accession number: MCK9871921.1) was retrieved. In silico studies indicated the presence of a signal peptide characteristic of extracellular enzymes. ProtParam tool predicted that the protein had a molecular mass of 42.46 kDa with an isoelectric point of 4.51. Aliphatic and instability index values suggested that the protein was stable and the observed GARVY value indicated its hydrophilic nature. 3D structure prediction and multiple sequence alignments revealed the presence of Type I catalytic domain [including the oxyanion histidine towards the N terminal, the catalytic triad with serine (as a part of GLSAG pentapeptide), aspartate and histidine], substrate binding and linker domain. The organism was able to grow on PHB in solid and liquid media and effectively degrade it. Maximum enzyme activity (1.8 U/mL/min) was observed after 5 d of incubation in Bushnell Hass Medium containing 0.1% PHB, 1.5% sodium chloride, at 30 °C, pH 7.5 with agitation at 130 rpm. Application of the organism in disintegrating films of PHB and its copolymers was successfully demonstrated on the basis of weight loss and scanning electron microscope analysis. To the best of our knowledge, this is the first report on production of PHB depolymerase with high efficiency by N. dassonvillei, an organism that holds promise in degrading PHB-derived waste material. [ABSTRACT FROM AUTHOR]

The helix preferences of cyclopentane-containing β/γ-hybrid oligomers, consisting of alternating βAc5a (2-aminocyclopentanecarboxylic acid) and γ(Et)Ac5a [2-(2-aminocyclopentyl)butanoic acid] residues with homochiral S-configurations, were investigated through conformational searches and density functional theory calculations in chloroform. The β/γ-hybrid dimer exhibited a distinct inclination toward a ribbon-like structure characterized by alternating C8 and C9 H-bonds. However, for β/γ-hybrid oligomers longer than tetramer, a preference for a right-handed (P)-2.413-helical structure emerged. The robust stabilities observed for the H13 helical structures in chloroform were attributed to the favored solvation free energies, which increased with the length of the peptide sequence. Calculations revealed that the mean backbone torsion angles of the H13 helix foldamer in the β/γ-hybrid pentamer closely resembled those observed in X-ray structures of the pentamer consisting of βAc5a and a γ-residue with a cyclohexane substituent. The introduction of cyclopentane substitutions led to distinct conformational preferences and/or handedness of helix foldamers compared to those of the unsubstituted β/γ-hybrid oligomers. Notably, a pyrrolidine-substituted analog of the H13 helical structure for the β/γ-hybrid pentamer, with adjacent amine diads substituted in close proximity, appears to be a promising organic catalyst for organic reactions such as the crossed aldol condensation and the cyclodimerization of dialdehyde in nonpolar solvents, as previously elucidated. [ABSTRACT FROM AUTHOR]

Introduction: Emerging tick-borne viruses of medical and veterinary importance are increasingly being reported globally. This resurgence emphasizes the need for sustained surveillance to provide insights into tick-borne viral diversity and associated potential public health risks. We report on a virus tentatively designated Kinna virus (KIV) in the family Phenuiviridae and genus Bandavirus. The virus was isolated from a pool of Amblyomma gemma ticks from Kinna in Isiolo County, Kenya. High throughput sequencing of the virus isolate revealed close relatedness to the Guertu virus. The virus genome is consistent with the described genomes of other members of the genus Bandavirus, with nucleotides lengths of 6403, 3332 and 1752 in the Large (L), Medium (M) and Small (S) segments respectively. Phylogenetic analysis showed that the virus clustered with Guertu virus although it formed a distinct and well supported branch. The RdRp amino acid sequence had a 93.3% identity to that of Guertu virus, an indication that the virus is possibly novel. Neutralizing antibodies were detected in 125 (38.6%, 95% CI 33.3–44.1%) of the human sera from the communities in this region. In vivo experiments showed that the virus was lethal to mice with death occurring 6–9 days post-infection. The virus infected mammalian cells (Vero cells) but had reduced infectivity in the mosquito cell line (C636) tested. Conclusion: Isolation of this novel virus with the potential to cause disease in human and animal populations necessitates the need to evaluate its public health significance and contribution to disease burden in the affected regions. This also points to the need for continuous monitoring of vector and human populations in high-risk ecosystems to update pathogen diversity. [ABSTRACT FROM AUTHOR]

Background: Viral diseases of sweet potatoes are causing severe crop losses worldwide. More than 30 viruses have been identified to infect sweet potatoes among which the sweet potato latent virus (SPLV), sweet potato mild speckling virus (SPMSV), sweet potato virus G (SPVG) and sweet potato virus 2 (SPV2) have been recognized as distinct species of the genus Potyvirus in the family Potyviridae. The sweet potato virus 2 (SPV2) is a primary pathogen affecting sweet potato crops. Methods: In this study, we detected an SPV2 isolate (named SPV2-LN) in Ipomoea nil in China. The complete genomic sequence of SPV2-LN was obtained using sequencing of small RNAs, RT-PCR, and RACE amplification. The codon usage, phylogeny, recombination analysis and selective pressure analysis were assessed on the SPV2-LN genome. Results: The complete genome of SPV2-LN consisted of 10,606 nt (GenBank No. OR842902), encoding 3425 amino acids. There were 28 codons in the SPV2-LN genome with a relative synonymous codon usage (RSCU) value greater than 1, of which 21 end in A/U. Among the 12 proteins of SPV2, P3 and P3N-PIPO exhibited the highest variability in their amino acid sequences, while P1 was the most conserved, with an amino acid sequence identity of 87-95.3%. The phylogenetic analysis showed that 21 SPV2 isolates were clustered into four groups, and SPV2-LN was clustered together with isolate yu-17-47 (MK778808) in group IV. Recombination analysis indicated no major recombination sites in SPV2-LN. Selective pressure analysis showed dN/dS of the 12 proteins of SPV2 were less than 1, indicating that all were undergoing negative selection, except for P1N-PISPO. Conclusion: This study identified a sweet potato virus, SPV2-LN, in Ipomoea nil. Sequence identities and genome analysis showed high similarity between our isolate and a Chinese isolate, yu-17-47, isolated from sweet potato. These results will provide a theoretical basis for understanding the genetic evolution and viral spread of SPV2. [ABSTRACT FROM AUTHOR]

In this study, peptide‐calcium chelate was screened from antler bone hydrolysate, and its bioactivity on MC3T3‐E1 cells and its chelating mechanism were investigated. In vitro experiments showed that peptide‐calcium chelate promoted the differentiation and mineralization of MC3T3‐E1 cells. Subsequently, three novel calcium‐chelating peptides were obtained from antler bone hydrolysate using hydroxyapatite chromatography (HAC), Sephadex G‐25 gel filtration chromatography, and reversed‐phase high‐performance liquid chromatography (RP‐HPLC). Meanwhile, this work determined peptides' amino acid sequences as TKLGTQLQL, LETVILGLLKT, and KMVFLMDLLK based on LC–MS/MS. Then the present work prepared the three peptides, with the corresponding calcium‐chelating rates being verified as 87.68 ± 2.86%, 80.72 ± 0.93%, and 67.96 ± 0.98%, respectively. Fourier transform infrared (FTIR) spectroscopy, ultraviolet–visible absorption (UV–vis) spectroscopy, X‐ray diffraction (XRD), circular dichroism (CD), zeta potential, and molecular dynamics (MD) simulations were adopted to investigate the chelating mode of peptides with calcium ions. As a result, oxygen in the carboxyl group and the nitrogen in the amino group were related to calcium binding. In addition, the chelation site preferred the negatively charged carboxylate groups of Leu or Thr. The present work revealed that antler bone might be the new calcium‐chelating peptide source and elucidated their positive role in osteogenesis. [ABSTRACT FROM AUTHOR]

Chemokines are cytokines that mediate leukocyte traffic between the lymphoid organs, the bloodstream, and the site of tissue damage, which is essential for an efficient immune response. In particular, the gamma interferon (IFN-g) inducible chemokines CXCL9, CXCL10, and CXCL11, and their receptor CXCR3, are involved in T cell and macrophage recruitment to the site of infection. The nature and function of these chemokines and their receptor are well-known in mammals, but further research is needed to achieve a similar level of understanding in fish immunity. Thus, in this study, we seek to identify the genes encoding the components of the Atlantic salmon (Salmo salar) CXCL9, CXCL10, CXCL11/CXCR3 axis (CXCL9-11/CXCR3), predict the protein structure from the amino acid sequence, and explore the regulation of gene expression as well as the response of these chemokines and their receptor to viral infections. The cxcl9, cxcl10, cxcl11, and cxcr3 gene sequences were retrieved from the databases, and the phylogenetic analysis was conducted to determine the evolutionary relationships. The study revealed an interesting pattern of clustering and conservation among fish and mammalian species. The salmon chemokine sequences clustered with orthologs from other fish species, while the mammalian sequences formed separate clades. This indicates a divergent evolution of chemokines between mammals and fish, possibly due to different evolutionary pressures. While the structural analysis of the chemokines and the CXCR3 receptor showed the conservation of critical motifs and domains, suggesting preserved functions and stability throughout evolution. Regarding the regulation of gene expression, some components of the CXCL9-11/CXCR3 axis are induced by recombinant gamma interferon (rIFN-γ) and by Infectious pancreatic necrosis virus (IPNV) infection in Atlantic salmon cells. Further studies are needed to explore the role of Atlantic salmon CXCL9-11 chemokines in regulating immune cell migration and endothelial activation, as seen in mammals. To the best of our knowledge, there have been no functional studies of chemokines to understand these effects in Atlantic salmon. [ABSTRACT FROM AUTHOR]

Maruca vitrata, a significant pest of legumes, impacts food security in Asia and Africa. This study presents a high-quality genome assembly of M. vitrata, utilizing advanced sequencing technologies including Nanopore long-read, MGI short-read, and Hi-C. The genome, totaling 482.3 Mb with a contig N50 of 2.91 Mb, features 41.58% repetitive sequences and encompasses 13,320 protein-coding genes. We performed comparative genomic analyses to affirm the accuracy and completeness of the protein sequences assembled, ensuring the assembly's integrity. Additionally, the annotation of 83 Cytochrome P450 (CYP) genes further confirms the comprehensive nature of the genome assembly and its annotations. This genome assembly not only deepens our understanding of M. vitrata biology but also supports the development of sustainable pest management strategies. This research highlights the importance of genomics in advancing sustainable agricultural solutions through innovative pest management approaches. [ABSTRACT FROM AUTHOR]

Symmetry in nature often emerges from self-assembly processes and serves a wide range of functions. Cell surface layers (S-layers) form symmetrical lattices on many bacterial and archaeal cells, playing essential roles such as facilitating cell adhesion, evading the immune system, and protecting against environmental stress. However, the experimental structural characterization of these S-layers is challenging due to their self-assembly properties and high sequence variability. In this study, we introduce the SymProFold pipeline, which utilizes the high accuracy of AlphaFold-Multimer predictions to derive symmetrical assemblies from protein sequences, specifically focusing on two-dimensional S-layer arrays and spherical viral capsids. The pipeline tests all known symmetry operations observed in these systems (p1, p2, p3, p4, and p6) and identifies the most likely symmetry for the assembly. The predicted models were validated using available experimental data at the cellular level, and additional crystal structures were obtained to confirm the symmetry and interfaces of several SymProFold assemblies. Overall, the SymProFold pipeline enables the determination of symmetric protein assemblies linked to critical functions, thereby opening possibilities for exploring functionalities and designing targeted applications in diverse fields such as nanotechnology, biotechnology, medicine, and materials and environmental sciences. Here, the authors present SymProFold, a method that predicts the structure of symmetrical protein assemblies such as bacterial surface layers and viral capsids by utilising AlphaFold Multimer predictions. [ABSTRACT FROM AUTHOR]

CD8+ T cells destroy insulin-producing pancreatic β cells in type 1 diabetes through HLA class I–restricted presentation of self-antigens. Combinatorial peptide library screening was used to produce a preferred peptide recognition landscape for a patient-derived T cell receptor (TCR) that recognized the preproinsulin-derived (PPI-derived) peptide sequence LWMRLLPLL in the context of disease risk allele HLA A*24:02. Data were used to generate a strong superagonist peptide, enabling production of an autoimmune HLA A*24:02–peptide–TCR structure by crystal seeding. TCR binding to the PPI epitope was strongly focused on peptide residues Arg4 and Leu5, with more flexibility at other positions, allowing the TCR to strongly engage many peptides derived from pathogenic bacteria. We confirmed an epitope from Klebsiella that was recognized by PPI-reactive T cells from 3 of 3 HLA A*24:02+ patients. Remarkably, the same epitope selected T cells from 7 of 8 HLA A*24+ healthy donors that cross-reacted with PPI, leading to recognition and killing of HLA A*24:02+ cells expressing PPI. These data provide a mechanism by which molecular mimicry between pathogen and self-antigens could have resulted in the breaking of self-tolerance to initiate disease. [ABSTRACT FROM AUTHOR]

The origin of translation is one of the most difficult problems of molecular evolution. Identifying molecular systems that translate an RNA sequence into a peptide sequence in the absence of ribosomes and enzymes is a challenge. Recently, single‐nucleotide translation via coupling of 5′ phosphoramidate‐linked amino acids to 2′/3′‐aminoacyl transfer‐NMPs, as directed by the sequence of an RNA template, was demonstrated for three of the four canonical nucleotides. How single‐nucleotide translation could be expanded to include all four bases and to produce longer peptides without translocation along the template strand remained unclear. Using transfer strands of increasing length containing any of the four bases that interrogate adjacent positions along the template, we now show that pentapeptides can be produced in coupling reactions and subsequent hydrolytic release in situ. With 2′/3′‐aminoacylated mono‐, di‐, tri‐ and tetranucleotides we thus show how efficient translation can be without biomacromolecules. [ABSTRACT FROM AUTHOR]

The American manatee (Trichechus manatus), experiencing population declines due to various threats, is the focus of conservation efforts that include the capture, rehabilitation, and release of orphaned calves when their mothers are unable to care for them. These efforts are compromised by the use of commercially available milk substitutes that lack essential components found in natural manatee breast milk, particularly immunoglobulin A (IgA). IgA plays a crucial role in nurturing the immune mucosal system and fostering a healthy microbiota. However, research on IgA in non-maternally fed manatees is limited due to the lack of species-specific reagents. To address this gap, our study employs immuno-informatics analysis to compare IgA sequences from manatees with those from other species, aiming to explore epitope similarity and sharing. We compared the protein sequence of manatee IgA with available IgA sequences, assessing similarity at the sequence, 3D structures, and epitope levels. Our findings reveal that human IgA exhibits the highest similarity in terms of sequence and 3D structure. Additionally, epitope analysis shows high conservation, identity, and similarity of predicted epitopes compared to human IgA. Future studies should focus on functional analysis using human IgA polyclonal reagents to detect manatee IgA in breast milk. Our findings highlight the potential of comparative analysis in advancing the understanding of immunology in non-human animals and overcoming challenges associated with the scarcity of species-specific reagents. [ABSTRACT FROM AUTHOR]

Background: The Bucephalidae is a large family of digenean trematodes but most previous analyses of its phylogenetic position have relied on a single mitochondrial gene or morphological features. Mitochondrial genomes (mitogenomes) remain unavailable for the entire family. To address this, we sequenced the complete mitogenome of Dollfustrema vaneyi and analyzed the phylogenetic relationships with other trematodes. Results: The circular genome of Dollfustrema vaneyi spanned 14,959 bp and contained 12 protein-coding genes, 22 transfer RNA genes, 2 ribosomal RNA genes, and a major non-coding region. We used concatenated amino acid and nucleotide sequences of all 36 genes for phylogenetic analyses, conducted using MrBayes, IQ-TREE and PhyloBayes. We identified pronounced topological instability across different analyses. The addition of recently sequenced two mitogenomes for the Aspidogastrea subclass along with the use of a site-heterogeneous model stabilized the topology, particularly the positions of Azygiidae and Bucephalidae. The stabilized results indicated that Azygiidae was the closest lineage to Bucephalidae in the available dataset, and together, they clustered at the base of the Plagiorchiida. Conclusions: Our study provides the first comprehensive description and annotation of the mitochondrial genome for the Bucephalidae family. The results indicate a close phylogenetic relationship between Azygiidae and Bucephalidae, and reveal their basal placement within the order Plagiorchiida. Furthermore, the inclusion of Aspidogastrea mitogenomes and the site-heterogeneous model significantly improved the topological stability. These data will provide key molecular resources for future taxonomic and phylogenetic studies of the family Bucephalidae. [ABSTRACT FROM AUTHOR]

Bioresorbable shape memory polymers (SMP) are an emerging class of polymers that can help address several challenges associated with minimally invasive surgery by providing a solution for structural tissue repair. Like most synthetic polymer networks, SMPs require additional biorelevance and modification for biomedical applications. Methodologies used to incorporate bioactive ligands must preserve SMP thermomechanics and ensure biofunctionality following in vivo delivery. We have previously described the development of a novel thermoresponsive bioresorbable SMP, poly (glycerol dodecanedioate) (PGD). In this study, cell-adhesive peptide sequences RGD and YIGSR were conjugated with PGD. We investigated 1) the impact of conjugated peptides on the fixity (R f), recovery (R r), and recovery rate (dR r /dT), 2) the impact of conjugated peptides on cell binding, and 3) the impact of the shape memory cycle (T prog) on conjugated peptide functionality towards binding human bone marrow stromal cells (BMSC). Peptide conjugation conditions impact fixity but not the recovery or recovery rate (p < 0.01). Peptide-conjugated substrates increased cell attachment and proliferation compared with controls (p < 0.001). Using complementary integrin binding cell-adhesive peptides increased proliferation compared with using single peptides (p < 0.05). Peptides bound to PGD substrates exhibited specificity to their respective integrin targets. Following the shape memory cycle, peptides maintained functionality and specificity depending on the shape memory cycle conditions (p < 0.001). The dissipation of strain energy during recovery can drive differential arrangement of conjugated sequences impacting functionality, an important design consideration for functionalized SMPs. Shape memory elastomers are an emerging class of polymers that are well-suited for minimally invasive repair of soft tissues. Tissue engineering approaches commonly utilize biodegradable scaffolds to deliver instructive cues, including cells and bioactive signals. Delivering these instructive cues on biodegradable shape memory elastomers requires modification with bioactive ligands. Furthermore, it is necessary to ensure the specificity of the ligands to their biological targets when conjugated to the polymer. Moreover, the bioactive ligand functionality must be conserved after completing the shape memory cycle, for applications in tissue engineering. [Display omitted] [ABSTRACT FROM AUTHOR]

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Glutathione transferase P1 (GSTP1) is a multi-functional protein that protects cells from electrophiles by catalyzing their conjugation with glutathione, and contributes to the regulation of cell proliferation, apoptosis, and signalling. GSTP1, usually described as a cytosolic enzyme, can localize to other cell compartments and we have reported its strong association with the plasma membrane. In the current study, the hypothesis that GSTP1 is palmitoylated and this modification facilitates its dynamic localization and function was investigated. Palmitoylation is the reversible post-translational addition of a 16-C saturated fatty acid to proteins, most commonly on Cys residues through a thioester bond. GSTP1 in MCF7 cells was modified by palmitate, however, GSTP1 Cys to Ser mutants (individual and Cys-less) retained palmitoylation. Treatment of palmitoylated GSTP1 with 0.1 N NaOH, which cleaves ester bonds, did not remove palmitate. Purified GSTP1 was spontaneously palmitoylated in vitro and peptide sequencing revealed that Cys48 and Cys102 undergo S-palmitoylation, while Lys103 undergoes the rare N-palmitoylation. N-palmitoylation occurs via a stable NaOH-resistant amide bond. Analysis of subcellular fractions of MCF7-GSTP1 cells and a modified proximity ligation assay revealed that palmitoylated GSTP1 was present not only in the membrane fraction but also in the cytosol. GSTP1 isolated from E. coli, and MCF7 cells (grown under fatty acid free or regular conditions), associated with plasma membrane-enriched fractions and this association was not altered by palmitoyl CoA. Overall, GSTP1 is modified by palmitate, at multiple sites, including at least one non-Cys residue. These modifications could contribute to regulating the diverse functions of GSTP1. [ABSTRACT FROM AUTHOR]

Oral delivery of proteins faces challenges due to the harsh conditions of the gastrointestinal (GI) tract, including gastric acid and intestinal enzyme degradation. Permeation enhancers are limited in their ability to deliver proteins with high molecular weight and can potentially cause toxicity by opening tight junctions. To overcome these challenges, we propose the use of montmorillonite (MMT) as an adjuvant that possesses both inflammation-oriented abilities and the ability to regulate gut microbiota. This adjuvant can be used as a universal protein oral delivery technology by fusing with advantageous binding amino acid sequences. We demonstrated that anti-TNF-α nanobody (VII) can be intercalated into the MMT interlayer space. The carboxylate groups (-COOH) of aspartic acid (D) and glutamic acid (E) interact with the MMT surface through electrostatic interactions with sodium ions (Na+). The amino groups (NH2) of asparagine (N) and glutamine (Q) are primarily attracted to the MMT layers through hydrogen bonding with oxygen atoms on the surface. This binding mechanism protects VII from degradation and ensures its release in the intestinal tract, as well as retaining biological activity, leading to significantly enhanced therapeutic effects on colitis. Furthermore, VII@MMT increases the abundance of short-chain fatty acids (SCFAs)-producing strains, including Clostridia, Prevotellaceae, Alloprevotella, Oscillospiraceae, Clostridia_vadinBB60_group, and Ruminococcaceae, therefore enhance the production of SCFAs and butyrate, inducing regulatory T cells (Tregs) production to modulate local and systemic immune homeostasis. Overall, the MMT adjuvant provides a promising universal strategy for protein oral delivery by rational designed protein. [ABSTRACT FROM AUTHOR]

Protein–protein interactions orchestrate plant development and serve as crucial elements for cellular and environmental communication. Understanding these interactions offers a gateway to unravel complex protein networks that will allow a better understanding of nature. Methods for the characterization of protein–protein interactions have been around over 30 years, yet the complexity of some of these interactions has fueled the development of new techniques that provide a better understanding of the underlying dynamics. In many cases, the application of these techniques is limited by the nature of the available sample. While some methods require an in vivo set-up, others solely depend on protein sequences to study protein–protein interactions via an in silico set-up. The vast number of techniques available to date calls for a way to select the appropriate tools for the study of specific interactions. Here, we classify widely spread tools and new emerging techniques for the characterization of protein–protein interactions based on sample requirements while providing insights into the information that they can potentially deliver. We provide a comprehensive overview of commonly used techniques and elaborate on the most recent developments, showcasing their implementation in plant research. [ABSTRACT FROM AUTHOR]

Oxidation of a thioether linkage in thioether-closed macrocyclic peptides led to collision-induced site-selective linearization of the peptides. This method has allowed for de novo sequencing of thioether macrocyclic peptides. The utility of the sequencing method was demonstrated by identifying the correct peptide sequences from a virtually randomized thioether macrocyclic peptide library. [ABSTRACT FROM AUTHOR]

Phytochelatin synthase (PCS) is a critical enzyme involved in heavy metal detoxification in organisms. In this study, we aim to comprehensively investigate the molecular and functional characteristics of the PCS1 gene from Nicotiana tabacum by examining its enzymatic activity, tissue-specific expression pattern, Cd-induced expression, as well as the impact on Cd tolerance and accumulation. The results demonstrated that the amino acid sequence of NtPCS1 shared a high similarity in its N-terminal region with PCS from other species. The enzymatic activity of NtPCS1 was found to be enhanced in the order Ag2+ > Cd2+ >Cu2+ > Pb2+>Hg2+ > Fe2+ > Zn2+. In addition, RT-PCR data indicated that NtPCS1 gene is constitutively expressed, with the highest expression observed in flowers, and that its transcript levels are up-regulated by CdCl2. When tobacco overexpressing NtPCS1 (PCS1 lines) were grown under CdCl2 stress, they produced more phytochelatins (PCs) than WT plants, but this did not result in increased Cd accumulation. However, in a root growth assay, the PCS1 lines exhibited hypersensitivity to Cd. The overexpression of NtPCS1 itself does not appear to be the primary cause of this heightened sensitivity to Cd, as the Arabidopsis thaliana Atpcs1 mutant overexpressing NtPCS1 actually exhibited enhanced tolerance to Cd. Furthermore, the addition of exogenous glutathione (GSH) progressively reduced the Cd hypersensitivity of the PCS1 lines, with the hypersensitivity even being completely eliminated. Surprisingly, the application of exogenous GSH led to a remarkably enhanced Cd accumulation in the PCS1 lines. This study enriches our understanding of the molecular function of the NtPCS1 gene and suggests a promising avenue for Cd tolerance through the heterologous expression of PCS genes in different species. [ABSTRACT FROM AUTHOR]

Brain derived neurotrophic factor (BDNF) is the most studied trophic factor in the central nervous system (CNS), and its role in the maturation of neurons, including synapse development and maintenance has been investigated intensely for over three decades. The primary receptor for BDNF is the tropomyosin receptor kinase B (TrkB), which is broadly expressed as two primary isoforms in the brain; the full length TrkB (TrkB.FL) receptor, expressed mainly in neurons and the truncated TrkB (TrkB.T1) receptor. We recently demonstrated that TrkB.T1 is predominately expressed in astrocytes, and appears critical for astrocyte morphological maturation. Given the critical role of BDNF/TrkB pathway in healthy brain development and mature CNS function, we aimed to identify molecular underpinnings of cell-type specific expression of each TrkB isoform. Using Nanopore sequencing which enables direct, long read sequencing of native DNA, we profiled DNA methylation patterns of the entire TrkB gene, Ntrk2, in both neurons and astrocytes. Here, we identified robust differences in cell-type specific isoform expression associated with significantly different methylation patterns of the Ntrk2 gene in each cell type. Notably, astrocytes demonstrated lower 5mC methylation, and higher 5hmC across the entire gene when compared to neurons, including differentially methylated sites (DMSs) found in regions flanking the unique TrkB.T1 protein coding sequence (CDS). These data suggest DNA methylation patterns may provide instruction for isoform specific TrkB expression across unique CNS cell types. [ABSTRACT FROM AUTHOR]

How complex are the rules by which a protein's sequence determines its function? High-order epistatic interactions among residues are thought to be pervasive, suggesting an idiosyncratic and unpredictable sequence-function relationship. But many prior studies may have overestimated epistasis, because they analyzed sequence-function relationships relative to a single reference sequence—which causes measurement noise and local idiosyncrasies to snowball into high-order epistasis—or they did not fully account for global nonlinearities. Here we present a reference-free method that jointly infers specific epistatic interactions and global nonlinearity using a bird's-eye view of sequence space. This technique yields the simplest explanation of sequence-function relationships and is more robust than existing methods to measurement noise, missing data, and model misspecification. We reanalyze 20 experimental datasets and find that context-independent amino acid effects and pairwise interactions, along with a simple nonlinearity to account for limited dynamic range, explain a median of 96% of phenotypic variance and over 92% in every case. Only a tiny fraction of genotypes are strongly affected by higher-order epistasis. Sequence-function relationships are also sparse: a miniscule fraction of amino acids and interactions account for 90% of phenotypic variance. Sequence-function causality across these datasets is therefore simple, opening the way for tractable approaches to characterize proteins' genetic architecture. Understanding protein sequence-function relationships is complicated by high order epistatic interactions among residues, although the extent of these interactions remains uncertain. Here, the authors present a reference-free method which suggests that sequence-function relationships are relatively simple, with little influence from high order epistatic interactions. [ABSTRACT FROM AUTHOR]

DNA-protein interactions exert the fundamental structure of many pivotal biological processes, such as DNA replication, transcription, and gene regulation. However, accurate and efficient computational methods for identifying these interactions are still lacking. In this study, we propose a method ESM-DBP through refining the DNA-binding protein sequence repertory and domain-adaptive pretraining based the general protein language model. Our method considers the lacking exploration of general language model for DNA-binding protein domain-specific knowledge, so we screen out 170,264 DNA-binding protein sequences to construct the domain-adaptive language model. Experimental results on four downstream tasks show that ESM-DBP provides a better feature representation of DNA-binding protein compared to the original language model, resulting in improved prediction performance and outperforming the state-of-the-art methods. Moreover, ESM-DBP can still perform well even for those sequences with only a few homologous sequences. ChIP-seq on two predicted cases further support the validity of the proposed method. DNA-protein interactions form the fundamental structure of many pivotal biological processes. Here, authors propose ESM-DBP, which refines the DNA-binding protein sequence repertoire and domain-adaptive pretraining on general protein language models to predict DNA-binding protein-related tasks. [ABSTRACT FROM AUTHOR]

Deep learning-based methods for generating functional proteins address the growing need for novel biocatalysts, allowing for precise tailoring of functionalities to meet specific requirements. This advancement leads to the development of highly efficient and specialized proteins with diverse applications across scientific, technological, and biomedical fields. This study establishes a pipeline for protein sequence generation with a conditional protein diffusion model, namely CPDiffusion, to create diverse sequences of proteins with enhanced functions. CPDiffusion accommodates protein-specific conditions, such as secondary structures and highly conserved amino acids. Without relying on extensive training data, CPDiffusion effectively captures highly conserved residues and sequence features for specific protein families. We applied CPDiffusion to generate artificial sequences of Argonaute (Ago) proteins based on the backbone structures of wild-type (WT) Kurthia massiliensis Ago (KmAgo) and Pyrococcus furiosus Ago (PfAgo), which are complex multi-domain programmable endonucleases. The generated sequences deviate by up to nearly 400 amino acids from their WT templates. Experimental tests demonstrated that the majority of the generated proteins for both KmAgo and PfAgo show unambiguous activity in DNA cleavage, with many of them exhibiting superior activity as compared to the WT. These findings underscore CPDiffusion's remarkable success rate in generating novel sequences for proteins with complex structures and functions in a single step, leading to enhanced activity. This approach facilitates the design of enzymes with multi-domain molecular structures and intricate functions through in silico generation and screening, all accomplished without the need for supervision from labeled data. [ABSTRACT FROM AUTHOR]

Background: HIV-1 has well-established mechanisms to disrupt essential pathways in people with HIV, such as inflammation and metabolism. Moreover, diversity of the amino acid sequences in fundamental HIV-1 proteins including Tat and Vif, have been linked to dysregulating these pathways, and subsequently influencing clinical outcomes in people with HIV. However, the relationship between Tat and Vif amino acid sequence variation and specific immune markers and metabolites of the tryptophan-kynurenine (Trp-Kyn) pathway remains unclear. Therefore, this study aimed to investigate the relationship between Tat/Vif amino acid sequence diversity and Trp-Kyn metabolites (quinolinic acid (QUIN), Trp, kynurenic acid (KA), Kyn and Trp/Kyn ratio), as well as specific immune markers (sCD163, suPAR, IL-6, NGAL and hsCRP) in n = 67 South African cART-naïve people with HIV. Methods: Sanger sequencing was used to determine blood-derived Tat/Vif amino acid sequence diversity. To measure Trp-Kyn metabolites, a LC–MS/MS metabolomics platform was employed using a targeted approach. To measure immune markers, Enzyme-linked immunosorbent assays and the Particle-enhanced turbidimetric assay was used. Results: After adjusting for covariates, sCD163 (p = 0.042) and KA (p = 0.031) were higher in participants with Tat signatures N24 and R57, respectively, and amino acid variation at position 24 (adj R2 = 0.048, β = -0.416, p = 0.042) and 57 (adj R2 = 0.166, β = 0.535, p = 0.031) of Tat were associated with sCD163 and KA, respectively. Conclusions: These preliminary findings suggest that amino acid variation in Tat may have an influence on underlying pathogenic HIV-1 mechanisms and therefore, this line of work merits further investigation. [ABSTRACT FROM AUTHOR]

The aminoacyl‐tRNA synthetases (aaRS) are a large group of enzymes that implement the genetic code in all known biological systems. They attach amino acids to their cognate tRNAs, moonlight in various translational and non‐translational activities beyond aminoacylation, and are linked to many genetic disorders. The aaRS have a subtle ontology characterized by structural and functional idiosyncrasies that vary from organism to organism, and protein to protein. Across the tree of life, the 22 coded amino acids are handled by 16 evolutionary families of Class I aaRS and 21 families of Class II aaRS. We introduce AARS Online, an interactive Wikipedia‐like tool curated by an international consortium of field experts. This platform systematizes existing knowledge about the aaRS by showcasing a taxonomically diverse selection of aaRS sequences and structures. Through its graphical user interface, AARS Online facilitates a seamless exploration between protein sequence and structure, providing a friendly introduction to the material for non‐experts and a useful resource for experts. Curated multiple sequence alignments can be extracted for downstream analyses. Accessible at www.aars.online, AARS Online is a free resource to delve into the world of the aaRS. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is a rare neurodegenerative disease caused due to aggregation of Huntingtin (HTT) protein. This study involves the cloning of 40 DnaJ chaperones from Drosophila, and overexpressing them in yeasts and fly models of HD. Accordingly, DnaJ chaperones were catalogued as enhancers or suppressors based on their growth phenotypes and aggregation properties. 2 of the chaperones that came up as targets were CG5001 and P58IPK. Protein aggregation and slow growth phenotype was rescued in yeasts, S2 cells, and Drosophila transgenic lines of HTT103Q with these overexpressed chaperones. Since DnaJ chaperones have protein sequence similarity across species, they can be used as possible tools to combat the effects of neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Summary The vast majority of proteins still lack experimentally validated functional annotations, which highlights the importance of developing high-performance automated protein function prediction/annotation (AFP) methods. While existing approaches focus on protein sequences, networks, and structural data, textual information related to proteins has been overlooked. However, roughly 82% of SwissProt proteins already possess literature information that experts have annotated. To efficiently and effectively use literature information, we present GORetriever, a two-stage deep information retrieval-based method for AFP. Given a target protein, in the first stage, candidate Gene Ontology (GO) terms are retrieved by using annotated proteins with similar descriptions. In the second stage, the GO terms are reranked based on semantic matching between the GO definitions and textual information (literature and protein description) of the target protein. Extensive experiments over benchmark datasets demonstrate the remarkable effectiveness of GORetriever in enhancing the AFP performance. Note that GORetriever is the key component of GOCurator, which has achieved first place in the latest critical assessment of protein function annotation (CAFA5: over 1600 teams participated), held in 2023–2024. Availability and implementation GORetriever is publicly available at https://github.com/ZhuLab-Fudan/GORetriever. [ABSTRACT FROM AUTHOR]

Motivation For the alignment of large numbers of protein sequences, tools are predominant that decide to align two residues using only simple prior knowledge, e.g. amino acid substitution matrices, and using only part of the available data. The accuracy of state-of-the-art programs declines with decreasing sequence identity and when increasingly large numbers of sequences are aligned. Recently, transformer-based deep-learning models started to harness the vast amount of protein sequence data, resulting in powerful pretrained language models with the main purpose of generating high-dimensional numerical representations, embeddings, for individual sites that agglomerate evolutionary, structural, and biophysical information. Results We extend the traditional profile hidden Markov model so that it takes as inputs unaligned protein sequences and the corresponding embeddings. We fit the model with gradient descent using our existing differentiable hidden Markov layer. All sequences and their embeddings are jointly aligned to a model of the protein family. We report that our upgraded HMM-based aligner, learnMSA2, combined with the ProtT5-XL protein language model aligns on average almost 6% points more columns correctly than the best amino acid-based competitor and scales well with sequence number. The relative advantage of learnMSA2 over other programs tends to be greater when the sequence identity is lower and when the number of sequences is larger. Our results strengthen the evidence on the rich information contained in protein language models' embeddings and their potential downstream impact on the field of bioinformatics. Availability and implementation: https://github.com/Gaius-Augustus/learnMSA , PyPI and Bioconda, evaluation: https://github.com/felbecker/snakeMSA [ABSTRACT FROM AUTHOR]

AMPylation is a biologically significant yet understudied post-translational modification where an adenosine monophosphate (AMP) group is added to Tyrosine and Threonine residues primarily. While recent work has illuminated the prevalence and functional impacts of AMPylation, experimental identification of AMPylation sites remains challenging. Computational prediction techniques provide a faster alternative approach. The predictive performance of machine learning models is highly dependent on the features used to represent the raw amino acid sequences. In this work, we introduce a novel feature extraction pipeline to encode the key properties relevant to AMPylation site prediction. We utilize a recently published dataset of curated AMPylation sites to develop our feature generation framework. We demonstrate the utility of our extracted features by training various machine learning classifiers, on various numerical representations of the raw sequences extracted with the help of our framework. Tenfold cross-validation is used to evaluate the model's capability to distinguish between AMPylated and non-AMPylated sites. The top-performing set of features extracted achieved MCC score of 0.58, Accuracy of 0.8, AUC-ROC of 0.85 and F1 score of 0.73. Further, we elucidate the behaviour of the model on the set of features consisting of monogram and bigram counts for various representations using SHapley Additive exPlanations. [ABSTRACT FROM AUTHOR]

Although several filoviruses are dangerous human pathogens, there is conflicting evidence regarding their origins and interactions with animal hosts. Here we attempt to improve this understanding using the paleoviral record over a geological time scale, protein structure predictions, tests for evolutionary maintenance, and phylogenetic methods that alleviate sources of bias and error. We found evidence for long branch attraction bias in the L gene tree for filoviruses, and that using codon-specific models and protein structural comparisons of paleoviruses ameliorated conflict and bias. We found evidence for four ancient filoviral groups, each with extant viruses and paleoviruses with open reading frames. Furthermore, we found evidence of repeated transfers of filovirus-like elements to mouse-like rodents. A filovirus-like nucleoprotein ortholog with an open reading frame was detected in three subfamilies of spalacid rodents (present since the Miocene). We provide evidence that purifying selection is acting to maintain amino acids, protein structure and open reading frames in these elements. Our finding of extant viruses nested within phylogenetic clades of paleoviruses informs virus discovery methods and reveals the existence of Lazarus taxa among RNA viruses. Our results resolve a deep conflict in the evolutionary framework for filoviruses and reveal that genomic transfers to vertebrate hosts with potentially functional co-options have been more widespread than previously appreciated. Author summary: Filoviruses are a family of RNA viruses discovered in 1967 and notorious for spillover of the dangerous pathogens, Ebola virus and Marburg virus. However, their origins, deeper relations, diversity, and interactions with animal hosts remain controversial. Part of the confusion may be that differing rates of evolution among divergent viral lineages can create a bias termed long branch attraction (LBA). We tested for this scenario in the L protein gene sequence of filoviruses and found evidence that LBA is occurring leading to a false pairing of filovirus lineages associated with a fish and a snake. We found that using nucleotides instead of amino acids when inferring trees, paleoviral sequences with open reading frames, additional conserved genes, and comparisons of predicted protein structures can resolve the LBA. We found four major groups of filoviruses, with the paleoviral record and trees being consistent with an ancient fish origin for the family. Moreover, we found evidence of a filovirus-like element in spalacid rodents that has been evolutionarily maintained at the open-reading frame, amino acid sequence and structural level for over 20 million years. We conclude that genomic interactions of filoviruses with vertebrates likely predates the separation of lobe-finned and ray-finned fish and that filoviral elements (including potential co-opted genes) are more widespread than previously appreciated. [ABSTRACT FROM AUTHOR]

Molecules of the Major Histocompatibility Complex (MHC) present short protein fragments on the cell surface, an important step in T cell immune recognition. MHC-I molecules process peptides from intracellular proteins; MHC-II molecules act in antigen-presenting cells and present peptides derived from extracellular proteins. Here we show that the sequence-dependent energy landscapes of MHC-peptide binding encode class-specific nonlinearities (epistasis). MHC-I has a smooth landscape with global epistasis; the binding energy is a simple deformation of an underlying linear trait. This form of epistasis enhances the discrimination between strong-binding peptides. In contrast, MHC-II has a rugged landscape with idiosyncratic epistasis: binding depends on detailed amino acid combinations at multiple positions of the peptide sequence. The form of epistasis affects the learning of energy landscapes from training data. For MHC-I, a low-complexity problem, we derive a simple matrix model of binding energies that outperforms current models trained by machine learning. For MHC-II, higher complexity prevents learning by simple regression methods. Epistasis also affects the energy and fitness effects of mutations in antigen-derived peptides (epitopes). In MHC-I, large-effect mutations occur predominantly in anchor positions of strong-binding epitopes. In MHC-II, large effects depend on the background epitope sequence but are broadly distributed over the epitope, generating a bigger target for escape mutations due to loss of presentation. Together, our analysis shows how an energy landscape of protein-protein binding constrains the target of escape mutations from T cell immunity, linking the complexity of the molecular interactions to the dynamics of adaptive immune response. Author summary: T cell immunity involves the binding of short peptides to the intracellular MHC recognition machinery. Understanding how the peptide-MHC binding energy depends on the peptide sequence is key to computationally predict immune recognition and immune escape evolution, for example, of pathogens and cancer cells. By analyzing experimental binding affinity data, we find that peptide-MHC interactions are described by nonlinear energy landscapes that depend on the recognition pathway: smooth and easy to learn for MHC class I, rugged and difficult to learn for MHC class II. The different forms of nonlinearity—or epistasis—suggest the most suitable strategy to infer these landscapes. In addition, the nonlinearity has direct implications on the energy and fitness of single mutations, generating distinct distributions of possible targets for immune escape. Together, this work establishes links between biophysical origin, nonlinear structure, learnability from data, and biological implications of peptide-MHC interactions, which can be applicable also to other protein interaction landscapes. [ABSTRACT FROM AUTHOR]

Introduction: Hemibiotrophic Phytophthora are a group of agriculturally and ecologically important pathogenic oomycetes causing severe decline in plant growth and fitness. The lifestyle of these pathogens consists of an initial biotrophic phase followed by a switch to a necrotrophic phase in the latter stages of infection. Between these two phases is the biotrophic to necrotrophic switch (BNS) phase, the timing and controls of which are not well understood particularly in Phytophthora spp. where host resistance has a purely quantitative genetic basis. Methods: To investigate this we sequenced and annotated the genome of Phytophthora medicaginis, causal agent of root rot and substantial yield losses to Fabaceae hosts. We analyzed the transcriptome of P. medicaginis across three phases of colonization of a susceptible chickpea host (Cicer arietinum) and performed co-regulatory analysis to identify putative small secreted protein (SSP) effectors that influence timing of the BNS in a quantitative pathosystem. Results: The genome of P. medicaginis is ~78 Mb, comparable to P. fragariae and P. rubi which also cause root rot. Despite this, it encodes the second smallest number of RxLR (arginine-any amino acid-leucine-arginine) containing proteins of currently sequenced Phytophthora species. Only quantitative resistance is known in chickpea to P. medicaginis, however, we found that many RxLR, Crinkler (CRN), and Nep1-like protein (NLP) proteins and carbohydrate active enzymes (CAZymes) were regulated during infection. Characterization of one of these, Phytmed_10271, which encodes an RxLR effector demonstrates that it plays a role in the timing of the BNS phase and root cell death. Discussion: These findings provide an important framework and resource for understanding the role of pathogenicity factors in purely quantitative Phytophthora pathosystems and their implications to the timing of the BNS phase. [ABSTRACT FROM AUTHOR]

The inversion of substrate size specificity is an evolutionary roadblock for proteins. The Duf4243 dioxygenases GedK and BTG13 are known to catalyze the aromatic cleavage of bulky tricyclic hydroquinone. In this study, we discover a Duf4243 dioxygenase PaD that favors small monocyclic hydroquinones from the penicillic-acid biosynthetic pathway. Sequence alignments between PaD and GedK and BTG13 suggest PaD has three additional motifs, namely motifs 1-3, distributed at different positions in the protein sequence. X-ray crystal structures of PaD with the substrate at high resolution show motifs 1-3 determine three loops (loops 1-3). Most intriguing, loops 1-3 stack together at the top of the pocket, creating a lid-like tertiary structure with a narrow channel and a clearly constricted opening. This drastically changes the substrate specificity by determining the entry and binding of much smaller substrates. Further genome mining suggests Duf4243 dioxygenases with motifs 1-3 belong to an evolutionary branch that is extensively involved in the biosynthesis of natural products and has the ability to degrade diverse monocyclic hydroquinone pollutants. This study showcases how natural enzymes alter the substrate specificity fundamentally by incorporating new small motifs, with a fixed overall scaffold-architecture. It will also offer a theoretical foundation for the engineering of substrate specificity in enzymes and act as a guide for the identification of aromatic dioxygenases with distinct substrate specificities. The Duf4243 dioxygenases GedK and BTG13 are known to catalyze the aromatic cleavage of bulky tricyclic hydroquinone. Here, the authors discover a distinct Duf4243 dioxygenase PaD that favors small monocyclic hydroquinones from the penicillic-acid biosynthetic pathway and determine the structural basis for its changed substrate specificity. [ABSTRACT FROM AUTHOR]

Strigolactones (SLs), carotenoid-derived plant hormones, govern the growth and development of both monocotyledonous and dicotyledonous plants. DWARF27 (D27), a plastid-targeted protein located at the initiation site of the core pathway in SL synthesis, plays a crucial role in regulating plant tillering (branching). In rice (Oryza sativa) and wheat (Triticum aestivum), OsD27 and TaD27-B proteins modulate the number of plant tillers by participating in SL biosynthesis. Similarly, AtD27 in Arabidopsis thaliana is required for SL production and has a significant impact on phenotypic changes related to branching. At the same time, TaD27 in wheat has been confirmed as a functional orthologue of AtD27 in Arabidopsis , and both Psathyrostachys juncea and wheat belong to the Triticeae , so we speculate that PjD27 gene may also have the same function as AtD27 in Arabidopsis. In this study, we initially screened the PjD27 gene significantly associated with tillering regulation through transcriptome data analysis and subsequently validated its expression levels using qRT-PCR analysis. Furthermore, we conducted phylogenetic analysis using amino acid sequences from 41 species, including P. juncea , to identify closely related species of P. juncea. Here, we analyze the conservation of D27 protein among P. juncea , rice, wheat, and Arabidopsis and provide preliminary evidence suggesting that PjD27 protein is an orthologue of D27 protein in Arabidopsis. Through reverse genetics, we demonstrate the crucial role of PjD27 in regulating plant branching, establishing it as a functional orthologue of D27 in Arabidopsis. Furthermore, following transient expression in tobacco (Nicotiana tabacum), we demonstrate that the subcellular location of the PjD27 protein is consistent with the cellular location of TaD27-B in wheat. Quantitative analysis of SLs shows that PjD27 is a key gene regulating tillering (branching) by participating in SL biosynthesis. By elucidating the function of the PjD27 gene, our findings provide valuable genetic resources for new germplasm creation and improving grain yield in P. juncea. [ABSTRACT FROM AUTHOR]

Fungi infection, especially derived from Plasmopara viticola, causes severe grapevine economic losses worldwide. Despite the availability of chemical treatments, looking for eco-friendly ways to control Vitis vinifera infection is gaining much more attention. When a plant is infected, multiple disease-control molecular mechanisms are activated. PRRs (Pattern Recognition Receptors) and particularly RLKs (receptor-like kinases) take part in the first barrier of the immune system, and, as a consequence, the kinase signaling cascade is activated, resulting in an immune response. In this context, discovering new lectin-RLK (LecRLK) membrane-bounded proteins has emerged as a promising strategy. The genome-wide localization of potential LecRLKs involved in disease defense was reported in two grapevine varieties of great economic impact: Chardonnay and Pinot Noir. A total of 23 potential amino acid sequences were identified, exhibiting high-sequence homology and evolution related to tandem events. Based on the domain architecture, a carbohydrate specificity ligand assay was conducted with docking, revealing two sequences as candidates for specific Vitis vinifera–Plasmopara viticola host–pathogen interaction. This study confers a starting point for designing new effective antifungal treatments directed at LecRLK targets in Vitis vinifera. [ABSTRACT FROM AUTHOR]