Molecular and Evolutionary Characteristics of Chicken Parvovirus (ChPV) Genomes Detected in Chickens with Runting-Stunting Syndrome.

Chicken Parvovirus (ChPV) belongs to the genus Aveparvovirus and is implicated in enteric diseases like runting-stunting syndrome (RSS) in poultry. In RSS, chicken health is affected by diarrhea, depression, and increased mortality, causing significant economic losses in the poultry industry. This study aimed to characterize the ChPV genomes detected in chickens with RSS through a metagenomic approach and compare the molecular and evolutionary characteristics within the Aveparvovirus galliform1 species. The intestinal content of broiler flocks affected with RSS was submitted to viral metagenomics. The assembled prevalent genomes were identified as ChPV after sequence and phylogenetic analysis, which consistently clustered separately from Turkey Parvovirus (TuPV). The strain USP-574-A presented signs of genomic recombination. The selective pressure analysis indicated that most of the coding genes in A. galliform1 are evolving under diversifying (negative) selection. Protein modeling of ChPV and TuPV viral capsids identified high conservancy over the VP2 region. The prediction of epitopes identified several co-localized antigenic peptides from ChPV and TuPV, especially for T-cell epitopes, highlighting the immunological significance of these sites. However, most of these peptides presented host-specific variability, obeying an adaptive scenario. The results of this study show the evolutionary path of ChPV and TuPV, which are influenced by diversifying events such as genomic recombination and selective pressure, as well as by adaptation processes, and their subsequent immunological impact.

CAPRI-Q: The CAPRI resource evaluating the quality of predicted structures of protein complexes.

Protein interactions are essential for cellular processes. In recent years there has been significant progress in computational prediction of 3D structures of individual protein chains, with the best-performing algorithms reaching sub-Ångström accuracy. These techniques are now finding their way into the prediction of protein interactions, adding to the existing modeling approaches. The community-wide Critical Assessment of Predicted Interactions (CAPRI) has been a catalyst for the development of procedures for the structural modeling of protein assemblies by organizing blind prediction experiments. The predicted structures are assessed against unpublished experimentally determined structures using a set of metrics with proven robustness that have been established in the CAPRI community. In addition, several advanced benchmarking databases provide targets against which users can test docking and assembly modeling software. These include the Protein-Protein Docking Benchmark, the CAPRI Scoreset, and the Dockground database, all developed by members of the CAPRI community. Here we present CAPRI-Q, a stand-alone model quality assessment tool, which can be freely downloaded or used via a publicly available web server. This tool applies the CAPRI metrics to assess the quality of query structures against given target structures, along with other popular quality metrics such as DockQ, TM-score and l-DDT, and classifies the models according to the CAPRI model quality criteria. The tool can handle a variety of protein complex types including those involving peptides, nucleic acids, and oligosaccharides. The source code is freely available from https://gitlab.in2p3.fr/cmsb-public/CAPRI-Q and its web interface through the Dockground resource at https://dockground.compbio.ku.edu/assessment/.

AI-Driven Deep Learning Techniques in Protein Structure Prediction.

Protein structure prediction is important for understanding their function and behavior. This review study presents a comprehensive review of the computational models used in predicting protein structure. It covers the progression from established protein modeling to state-of-the-art artificial intelligence (AI) frameworks. The paper will start with a brief introduction to protein structures, protein modeling, and AI. The section on established protein modeling will discuss homology modeling, ab initio modeling, and threading. The next section is deep learning-based models. It introduces some state-of-the-art AI models, such as AlphaFold (AlphaFold, AlphaFold2, AlphaFold3), RoseTTAFold, ProteinBERT, etc. This section also discusses how AI techniques have been integrated into established frameworks like Swiss-Model, Rosetta, and I-TASSER. The model performance is compared using the rankings of CASP14 (Critical Assessment of Structure Prediction) and CASP15. CASP16 is ongoing, and its results are not included in this review. Continuous Automated Model EvaluatiOn (CAMEO) complements the biennial CASP experiment. Template modeling score (TM-score), global distance test total score (GDT_TS), and Local Distance Difference Test (lDDT) score are discussed too. This paper then acknowledges the ongoing difficulties in predicting protein structure and emphasizes the necessity of additional searches like dynamic protein behavior, conformational changes, and protein-protein interactions. In the application section, this paper introduces some applications in various fields like drug design, industry, education, and novel protein development. In summary, this paper provides a comprehensive overview of the latest advancements in established protein modeling and deep learning-based models for protein structure predictions. It emphasizes the significant advancements achieved by AI and identifies potential areas for further investigation.

Generative artificial intelligence performs rudimentary structural biology modeling.

Natural language-based generative artificial intelligence (AI) has become increasingly prevalent in scientific research. Intriguingly, capabilities of generative pre-trained transformer (GPT) language models beyond the scope of natural language tasks have recently been identified. Here we explored how GPT-4 might be able to perform rudimentary structural biology modeling. We prompted GPT-4 to model 3D structures for the 20 standard amino acids and an α-helical polypeptide chain, with the latter incorporating Wolfram mathematical computation. We also used GPT-4 to perform structural interaction analysis between the anti-viral nirmatrelvir and its target, the SARS-CoV-2 main protease. Geometric parameters of the generated structures typically approximated close to experimental references. However, modeling was sporadically error-prone and molecular complexity was not well tolerated. Interaction analysis further revealed the ability of GPT-4 to identify specific amino acid residues involved in ligand binding along with corresponding bond distances. Despite current limitations, we show the current capacity of natural language generative AI to perform basic structural biology modeling and interaction analysis with atomic-scale accuracy.

T and Z, partial seed coat patterning genes in common bean, provide insight into the structure and protein interactions of a plant MBW complex.

Flavonoids are secondary metabolites associated with plant seed coat and flower color. These compounds provide health benefits to humans as anti-inflammatory and antioxidant compounds. The expression of the late biosynthetic genes in the flavonoid pathway is controlled by a ternary MBW protein complex consisting of interfacing MYB, beta-helix-loop-helix (bHLH), and WD40 Repeat (WDR) proteins. P, the master regulator gene of the flavonoid expression in common bean (Phaseolus vulgaris L.), was recently determined to encode a bHLH protein. The T and Z genes control the distribution of color in bean seeds and flowers and have historically been considered regulators of the flavonoid gene expression. T and Z candidates were identified using reverse genetics based on genetic mapping, phylogenetic analysis, and mutant analysis. Domain and AlphaFold2 structure analyses determined that T encodes a seven-bladed ß-propeller WDR protein, while Z encodes a R2R3 MYB protein. Deletions and SNPs in T and Z mutants, respectively, altered the 3D structure of these proteins. Modeling of the Z MYB/P bHLH/T WDR MBW complex identified interfacing sequence domains and motifs in all three genes that are conserved in dicots. One Z MYB motif is a possible beta-molecular recognition feature (ß-MoRF) that only appears in a structured state when Z MYB is modeled as a component of a MBW complex. Complexes containing mutant T and Z proteins changed the interaction of members of the complex in ways that would alter their role in regulating the expression of genes in the flavonoid pathway.

AlphaFold2 for Protein Structure Prediction: Best Practices and Critical Analyses.

AlphaFold2 (AF2) has emerged in recent years as a groundbreaking innovation that has revolutionized several scientific fields, in particular structural biology, drug design, and the elucidation of disease mechanisms. Many scientists now use AF2 on a daily basis, including non-specialist users. This chapter is aimed at the latter. Tips and tricks for getting the most out of AF2 to produce a high-quality biological model are discussed here. We suggest to non-specialist users how to maintain a critical perspective when working with AF2 models and provide guidelines on how to properly evaluate them. After showing how to perform our own structure prediction using ColabFold, we list several ways to improve AF2 models by adding information that is missing from the original AF2 model. By using software such as AlphaFill to add cofactors and ligands to the models, or MODELLER to add disulfide bridges between cysteines, we guide users to build a high-quality biological model suitable for applications such as drug design, protein interaction, or molecular dynamics studies.

Exploring the Structurally Conserved Regions and Functional Significance in Bacterial N-Terminal Nucleophile (Ntn) Amide-Hydrolases.

The initial adoption of penicillin as an antibiotic marked the start of exploring other compounds essential for pharmaceuticals, yet resistance to penicillins and their side effects has compromised their efficacy. The N-terminal nucleophile (Ntn) amide-hydrolases S45 family plays a key role in catalyzing amide bond hydrolysis in various compounds, including antibiotics like penicillin and cephalosporin. This study comprehensively analyzes the structural and functional traits of the bacterial N-terminal nucleophile (Ntn) amide-hydrolases S45 family, covering penicillin G acylases, cephalosporin acylases, and D-succinylase. Utilizing structural bioinformatics tools and sequence analysis, the investigation delineates structurally conserved regions (SCRs) and substrate binding site variations among these enzymes. Notably, sixteen SCRs crucial for substrate interaction are identified solely through sequence analysis, emphasizing the significance of sequence data in characterizing functionally relevant regions. These findings introduce a novel approach for identifying targets to enhance the biocatalytic properties of N-terminal nucleophile (Ntn) amide-hydrolases, while facilitating the development of more accurate three-dimensional models, particularly for enzymes lacking structural data. Overall, this research advances our understanding of structure-function relationships in bacterial N-terminal nucleophile (Ntn) amide-hydrolases, providing insights into strategies for optimizing their enzymatic capabilities.

Defects in Glabrous 3 (GL3) functionality underlie the absence of trichomes in Brassica napus.

Previously, expression of the Arabidopsis thaliana GLABRA3 (GL3) induced trichome formation in Brassica napus. GL3 orthologues were examined from glabrous (B. oleracea), semi-glabrous (B. napus), moderately hirsute (B. rapa), and very hirsute (B. villosa) Brassica species. Ectopic expression of BnGL3, BrGL3 alleles, or BvGL3 induced trichome formation in glabrous B. napus with the effect on trichome number commensurate with density in the original accessions. Chimeric GL3 proteins in which the B. napus amino terminal region, which interacts with MYB proteins, or the middle region, which interacts with the WD40 protein TTG1, was exchanged with corresponding regions from A. thaliana were as stimulatory to trichome production as AtGL3. Exchange of the carboxy-terminal region containing a bHLH domain and an ACT domain did not alter the trichome stimulatory activity, although modeling of the ACT domain identified differences that could affect GL3 dimerization. B. napus A- and C-genomes orthologues differed in their abilities to form homo- and heterodimers. Modeling of the amino-terminal region revealed a conserved domain that may represent the MYB factor binding pocket. This region interacted with the MYB factors GL1, CPC, and TRY, as well as with JAZ8, which is involved in jasmonic acid-mediated regulation of MYC-like transcription factors. Protein interaction studies indicated that GL1 interaction with GL3 from B. napus and A. thaliana may underlie the difference in their respective abilities to induce trichome formation.

Molecular genetics, neuroimaging outcomes, and structural analyses of novel and recurrent variants of WDR62 gene in two consanguineous Pakistani families with autosomal recessive primary microcephaly.

BACKGROUND: Autosomal recessive primary microcephaly (MCPH) is a rare neurodevelopmental and genetically heterogeneous disorder, characterized by small cranium size (> - 3 SD below mean) and often results in varying degree of intellectual disability. Thirty genes have been identified for the etiology of this disorder due to its clinical and genetic heterogeneity. METHODS AND RESULTS: Here, we report two consanguineous Pakistani families affected with MCPH exhibiting mutation in WDR62 gene. The investigation approach involved Next Generation Sequencing (NGS) gene panel sequencing coupled with linkage analysis followed by validation of identified variants through automated Sanger sequencing and Barcode-Tagged (BT) sequencing. The molecular genetic analysis revealed one novel splice site variant (NM_001083961.2(WDR62):c.1372-1del) in Family A and one known exonic variant NM_001083961.2(WDR62):c.3936dup (p.Val1313Argfs*18) in Family B. Magnetic Resonance Imaging (MRI) scans were also employed to gain insights into the structural architecture of affected individuals. Neurological assessments showed the reduced gyral and sulcal patterns along with normal corpus callosum in affected individuals harboring novel variant. In silico assessments of the identified variants were conducted using different tools to confirm the pathogenicity of these variants. Through In silico analyses, both variants were identified as disease causing and protein modeling of exonic variant indicates subtle conformational alterations in prophesied protein structure. CONCLUSION: This study identifies a novel variant (c.1372-1del) and a recurrent pathogenic variant c.3936dup (p.Val1313Argfs*18) in the WDR62 gene among the Pakistani population, expanding the mutation spectrum for MCPH. These findings emphasize the importance of genetic counseling and awareness to reduce consanguinity and address the burden of this disorder.

A survey of the Sli gene in wild and cultivated potato.

Inbred-hybrid breeding of diploid potatoes necessitates breeding lines that are self-compatible. One way of incorporating self-compatibility into incompatible cultivated potato (Solanum tuberosum) germplasm is to introduce the S-locus inhibitor gene (Sli), which functions as a dominant inhibitor of gametophytic self-incompatibility. To learn more about Sli diversity and function in wild species relatives of cultivated potato, we obtained Sli gene sequences that extended from the 5'UTR to the 3'UTR from 133 individuals from 22 wild species relatives of potato and eight diverse cultivated potato clones. DNA sequence alignment and phylogenetic trees based on genomic and protein sequences show that there are two highly conserved groups of Sli sequences. DNA sequences in one group contain the 533 bp insertion upstream of the start codon identified previously in self-compatible potato. The second group lacks the insertion. Three diploid and four polyploid individuals of wild species collected from geographically disjointed localities contained Sli with the 533 bp insertion. For most of the wild species clones examined, however, Sli did not have the insertion. Phylogenetic analysis indicated that Sli sequences with the insertion, in wild species and in cultivated clones, trace back to a single origin. Some diploid wild potatoes that have Sli with the insertion were self-incompatible and some wild potatoes that lack the insertion were self-compatible. Although there is evidence of positive selection for some codon positions in Sli, there is no evidence of diversifying selection at the gene level. In silico analysis of Sli protein structure did not support the hypothesis that amino acid changes from wild-type (no insertion) to insertion-type account for changes in protein function. Our study demonstrated that genetic factors besides the Sli gene must be important for conditioning a switch in the mating system from self-incompatible to self-compatible in wild potatoes.

Bioinformatics approach for structure modeling, vaccine design, and molecular docking of Brucella candidate proteins BvrR, OMP25, and OMP31.

Brucellosis is a zoonotic disease with significant economic and healthcare costs. Despite the eradication efforts, the disease persists. Vaccines prevent disease in animals while antibiotics cure humans with limitations. This study aims to design vaccines and drugs for brucellosis in animals and humans, using protein modeling, epitope prediction, and molecular docking of the target proteins (BvrR, OMP25, and OMP31). Tertiary structure models of three target proteins were constructed and assessed using RMSD, TM-score, C-score, Z-score, and ERRAT. The best models selected from AlphaFold and I-TASSER due to their superior performance according to CASP 12 - CASP 15 were chosen for further analysis. The motif analysis of best models using MotifFinder revealed two, five, and five protein binding motifs, however, the Motif Scan identified seven, six, and eight Post-Translational Modification sites (PTMs) in the BvrR, OMP25, and OMP31 proteins, respectively. Dominant B cell epitopes were predicted at (44-63, 85-93, 126-137, 193-205, and 208-237), (26-46, 52-71, 98-114, 142-155, and 183-200), and (29-45, 58-82, 119-142, 177-198, and 222-251) for the three target proteins. Additionally, cytotoxic T lymphocyte epitopes were detected at (173-181, 189-197, and 202-210), (61-69, 91-99, 159-167, and 181-189), and (3-11, 24-32, 167-175, and 216-224), while T helper lymphocyte epitopes were displayed at (39-53, 57-65, 150-158, 163-171), (79-87, 95-108, 115-123, 128-142, and 189-197), and (39-47, 109-123, 216-224, and 245-253), for the respective target protein. Furthermore, structure-based virtual screening of the ZINC and DrugBank databases using the docking MOE program was followed by ADMET analysis. The best five compounds of the ZINC database revealed docking scores ranged from (- 16.8744 to - 15.1922), (- 16.0424 to - 14.1645), and (- 14.7566 to - 13.3222) for the BvrR, OMP25, and OMP31, respectively. These compounds had good ADMET parameters and no cytotoxicity, while DrugBank compounds didn't meet Lipinski's rule criteria. Therefore, the five selected compounds from the ZINC20 databases may fulfill the pharmacokinetics and could be considered lead molecules for potentially inhibiting Brucella's proteins.

Invariant point message passing for protein side chain packing.

Protein side chain packing (PSCP) is a fundamental problem in the field of protein engineering, as high-confidence and low-energy conformations of amino acid side chains are crucial for understanding (and designing) protein folding, protein-protein interactions, and protein-ligand interactions. Traditional PSCP methods (such as the Rosetta Packer) often rely on a library of discrete side chain conformations, or rotamers, and a forcefield to guide the structure to low-energy conformations. Recently, deep learning (DL) based methods (such as DLPacker, AttnPacker, and DiffPack) have demonstrated state-of-the-art predictions and speed in the PSCP task. Building off the success of geometric graph neural networks for protein modeling, we present the Protein Invariant Point Packer (PIPPack) which effectively processes local structural and sequence information to produce realistic, idealized side chain coordinates using χ $$ \chi $$ -angle distribution predictions and geometry-aware invariant point message passing (IPMP). On a test set of ∼1400 high-quality protein chains, PIPPack is highly competitive with other state-of-the-art PSCP methods in rotamer recovery and per-residue RMSD but is significantly faster.

Computational Approaches to Drug Repurposing: Methods, Challenges, and Opportunities.

Drug repurposing refers to the inference of therapeutic relationships between a clinical indication and existing compounds. As an emerging paradigm in drug development, drug repurposing enables more efficient treatment of rare diseases, stratified patient populations, and urgent threats to public health. However, prioritizing well-suited drug candidates from among a nearly infinite number of repurposing options continues to represent a significant challenge in drug development. Over the past decade, advances in genomic profiling, database curation, and machine learning techniques have enabled more accurate identification of drug repurposing candidates for subsequent clinical evaluation. This review outlines the major methodologic classes that these approaches comprise, which rely on (a) protein structure, (b) genomic signatures, (c) biological networks, and (d) real-world clinical data. We propose that realizing the full impact of drug repurposing methodologies requires a multidisciplinary understanding of each method's advantages and limitations with respect to clinical practice.

Decoding the Structure-Function Relationship of the Muramidase Domain in E. coli O157.H7 Bacteriophage Endolysin: A Potential Building Block for Chimeric Enzybiotics.

Bacteriophage endolysins are potential alternatives to conventional antibiotics for treating multidrug-resistant gram-negative bacterial infections. However, their structure-function relationships are poorly understood, hindering their optimization and application. In this study, we focused on the individual functionality of the C-terminal muramidase domain of Gp127, a modular endolysin from E. coli O157:H7 bacteriophage PhaxI. This domain is responsible for the enzymatic activity, whereas the N-terminal domain binds to the bacterial cell wall. Through protein modeling, docking experiments, and molecular dynamics simulations, we investigated the activity, stability, and interactions of the isolated C-terminal domain with its ligand. We also assessed its expression, solubility, toxicity, and lytic activity using the experimental data. Our results revealed that the C-terminal domain exhibits high activity and toxicity when tested individually, and its expression is regulated in different hosts to prevent self-destruction. Furthermore, we validated the muralytic activity of the purified refolded protein by zymography and standardized assays. These findings challenge the need for the N-terminal binding domain to arrange the active site and adjust the gap between crucial residues for peptidoglycan cleavage. Our study shed light on the three-dimensional structure and functionality of muramidase endolysins, thereby enriching the existing knowledge pool and laying a foundation for accurate in silico modeling and the informed design of next-generation enzybiotic treatments.

Genetic mechanisms of co-emergence of INH-resistant Mycobacterium tuberculosis strains during the standard course of antituberculosis therapy.

The incidence of isoniazid (INH) resistant Mycobacterium tuberculosis is increasing globally. This study aimed to identify the molecular mechanisms behind the development of INH resistance in M. tuberculosis strains collected from the same patients during the standard course of treatment. Three M. tuberculosis strains were collected from a patient before and during antituberculosis (anti-TB) therapy. The strains were characterized using phenotypic drug susceptibility tests, Mycobacterial Interspersed Repeated Unit-Variable-Number Tandem Repeats (MIRU-VNTR), and whole-genome sequencing (WGS) to identify mutations associated with INH resistance. To validate the role of the novel mutations in INH resistance, the mutated katG genes were electroporated into a KatG-deleted M. tuberculosis strain (GA03). Three-dimensional structures of mutated KatG were modeled to predict their impact on INH binding. The pre-treatment strain was susceptible to INH. However, two INH-resistant strains were isolated from the patient after anti-TB therapy. MIRU-VNTR and WGS revealed that the three strains were clonally identical. A missense mutation (P232L) and a nonsense mutation (Q461Stop) were identified in the katG of the two post-treatment strains, respectively. Transformation experiments showed that katG of the pre-treatment strain restored INH susceptibility in GA03, whereas the mutated katG genes from the post-treatment strains rendered negative catalase activity and INH resistance. The protein model indicated that P232L reduced INH-KatG binding affinity while Q461Stop truncated gene transcription. Our results showed that the two katG mutations, P232L and Q461Stop, accounted for the co-emergence of INH-resistant clones during anti-TB therapy. The inclusion of these mutations in the design of molecular assays could increase the diagnostic performance.IMPORTANCEThe evolution of drug-resistant strains of Mycobacterium tuberculosis within the lung lesions of a patient has a detrimental impact on treatment outcomes. This is particularly concerning for isoniazid (INH), which is the most potent first-line antimycobacterial drug. However, the precise genetic factors responsible for drug resistance in patients have not been fully elucidated, with approximately 15% of INH-resistant strains harboring unknown genetic factors. This raises concerns about the emergence of drug-resistant clones within patients, further contributing to the global epidemic of resistance. In this study, we revealed the presence of two novel katG mutations, which emerged independently due to the stress exerted by antituberculosis (anti-TB) treatment on a parental strain. Importantly, we experimentally demonstrated the functional significance of both mutations in conferring resistance to INH. Overall, this research sheds light on the genetic mechanisms underlying the evolution of INH resistance within patients and provides valuable insights for improving diagnostic performance by targeting specific mutations.

In silico characterization and identification of compound heterozygous variants in H/ACA Ribonucleoprotein Assembly Factor (SHQ1) from Indian population.

Background: H/ACA small nucleolar ribonucleoproteins (snoRNP) form a complex with multiple proteins to accomplish the pseudouridylation of rRNA. The assembly of H/ACA small nucleolar ribonucleoproteins (snoRNP) is initiated by H/ACA ribonucleoprotein Assembly factor, that is, SHQ1. Mutations in SHQ1 have been reported to cause two disorders namely, dystonia-35 childhood onset (OMIM*619921) and neurodevelopmental disorder with seizures and dystonia (OMIM*619922), both of which are inherited in an autosomal recessive manner. Considering the high genetic and clinical diversity of SHQ1-related clinical features and the importance of SHQ1 in the assembly of the H/ACA snoRNP complex, it is important to take a systematic approach to delineate the genetic diagnosis and impact of mutations on protein structure and stability. Methods: Whole exome sequencing followed by Sanger validation was performed in an individual with the clinical features of neurodevelopmental disorder with seizures and dystonia (OMIM*619922). Protein modeling studies of all the reported SHQ1 variants to date were performed using freely available web servers Interactive Tree of Life, String, BioGrid, ShinyGO, DAVID, and Pathvix. Protein structures were visualized using Pymol. Results and Discussion: We identified compound heterozygous variants, one known frameshift deletion c. 828_831del, p.(Asp277Serfs*27) and the other novel missense variant c. 1157A>C, p.(Tyr386Ser) found in an individual with neurodevelopmental disorder, seizures, movement disorder, and hypomyelination leukodystrophy on neuroimaging. Protein-interactome studies identified potential genetic interactors that include GAR1, NAF1, TRUB1, UTP15, DKC1, NOP10, NPHOSPH 10, KRR1, NOP58, NOP56, FBL, RRP9, NHP2, RUVBL1, and RUVBL2. Ribosome biogenesis in eukaryotes, RNA polymerase, RNA transport, spliceosome, ribosome, cytosolic DNA-sensing pathway, DNA replication, mismatch repair, base excision repair, nucleotide excision repair, and basal transcription factors process were identified as the linked pathways with the prioritized genes. Conclusion: In conclusion, a sophisticated genotype and phenotype correlation followed by linking the genes to the key biological pathways opens new avenues to understand disease pathology and plan for therapeutic interventions.

Molecular Prediction and Correlation of the Structure and Function of Universal Stress Protein A (UspA) from Salmonella Typhimurium.

Salmonella Typhimurium (ST) is a zoonotic pathogen that can cause gastroenteritis in humans when they consume contaminated food or water. When exposed to various stressors, both from living organisms (biotic) and the environment (abiotic), Salmonella Typhimurium produces Universal Stress Proteins (USPs). These proteins are gaining recognition for their crucial role in bacterial stress resistance and the ability to enter a prolonged state of growth arrest. Additionally, USPs exhibit diverse structures due to the fusion of the USP domain with different catalytic motifs, enabling them to participate in various reactions and cellular activities during stressful conditions. In this particular study, researchers cloned and analyzed the uspA gene obtained from poultry-derived strains of Salmonella Typhimurium. The gene comprises 435 base pairs, encoding a USP family protein consisting of 144 amino acids. Phylogenetic analysis demonstrated a close relationship between the uspA genes of Salmonella Typhimurium and those found in other bacterial species. We used molecular dynamics simulations and 3D structure prediction to ensure that the USPA protein was stable. Furthermore, we also carried out motif search and network analysis of protein-protein interactions. The findings from this study offer valuable insights for the development of inhibitors targeted against Salmonella Typhimurium.

Cytonuclear interplay in auto- and allopolyploids: a multifaceted perspective from the Festuca-Lolium complex.

Restoring cytonuclear stoichiometry is necessary after whole-genome duplication (WGD) and interspecific/intergeneric hybridization in plants. We investigated this phenomenon in auto- and allopolyploids of the Festuca-Lolium complex providing insights into the mechanisms governing cytonuclear interactions in early polyploid and hybrid generations. Our study examined the main processes potentially involved in restoring the cytonuclear balance after WGD comparing diploids and new and well-established autopolyploids. We uncovered that both the number of chloroplasts and the number of chloroplast genome copies were significantly higher in the newly established autopolyploids and grew further in more established autopolyploids. The increase in the copy number of the chloroplast genome exceeded the rise in the number of chloroplasts and fully compensated for the doubling of the nuclear genome. In addition, changes in nuclear and organelle gene expression were insignificant. Allopolyploid Festuca × Lolium hybrids displayed potential structural conflicts in parental protein variants within the cytonuclear complexes. While biased maternal allele expression has been observed in numerous hybrids, our results suggest that its role in cytonuclear stabilization in the Festuca × Lolium hybrids is limited. This study provides insights into the restoration of the cytonuclear stoichiometry, yet it emphasizes the need for future research to explore post-transcriptional regulation and its impact on cytonuclear gene expression stoichiometry. Our findings may enhance the understanding of polyploid plant evolution, with broader implications for the study of cytonuclear interactions in diverse biological contexts.

Haplotype analysis, regulatory elements and docking simulation of structural models of different AT3 copies in the genus Capsicum.

Capsaicinoids are responsible for the pungency in Capsicum species. These are synthesized by the Capsaicin synthase (CS) encoded by the AT3 gene, which catalyzes the transference of an acyl moiety from a branched-chain fatty acid-CoA ester to the vanillylamine to produce capsaicinoids. Some AT3 gene copies have been identified on the Capsicum genome. The absence of capsaicinoid in some nonpungent accessions is related to mutant AT3 alleles. The differences between CS protein copies can affect the tridimensional structure of the protein and the affinity for its substrates, and this could affect fruit pungency. This study characterized 32 AT3 sequences covering Capsicum pungent and non-pungent accessions. These were clustered in AT3-D1 and AT3-D2 groups and representative sequences were analyzed. Genomic upstream analysis shows different regulatory elements, mainly responsive to light and abiotic stress. AT3-D1 and AT3-D2 gene expression was confirmed in fruit tissues of C. annuum. Amino acid substitutions close to the predictable HXXXD and DFGWG motifs were also identified. AT3 sequences were modeled showing a BAHD acyltransferase structure with two connected domains. A pocket with different shape, size and composition between AT3 models was found inside the protein, with the conserved motif HXXXD exposed to it, and a channel for their accessibility. CS substrates exhibit high interaction energies with the His and Asp conserved residues. AT3 models have different interaction affinities with the (E)-8-methylnon-6-enoyl-CoA, 8-methylnonanoyl-CoA and vanillylamine substrates. These results suggested that AT3-D1 and AT3-D2 sequences encode CS enzymes with different regulatory factors and substratum affinities.Communicated by Ramaswamy H. Sarma.

Sugar-binding and split domain combinations in repeats-in-toxin adhesins from Vibrio cholerae and Aeromonas veronii mediate cell-surface recognition and hemolytic activities.

Many pathogenic Gram-negative bacteria use repeats-in-toxin adhesins for colonization and biofilm formation. In the cholera agent Vibrio cholerae, flagellar-regulated hemagglutinin A (FrhA) enables these functions. Using bioinformatic analysis, a sugar-binding domain was identified in FrhA adjacent to a domain of unknown function. AlphaFold2 indicated the boundaries of both domains to be slightly shorter than previously predicted and assisted in the recognition of the unknown domain as a split immunoglobulin-like fold that can assist in projecting the sugar-binding domain toward its target. The AlphaFold2-predicted structure is in excellent agreement with the molecular envelope obtained from small-angle X-ray scattering analysis of a recombinant construct spanning the sugar-binding and unknown domains. This two-domain construct was probed by glycan micro-array screening and showed binding to mammalian fucosylated glycans, some of which are characteristic erythrocyte markers and intestinal cell epitopes. Isothermal titration calorimetry further showed the construct-bound l-fucose with a Kd of 21 µM. Strikingly, this recombinant protein construct bound and lysed erythrocytes in a concentration-dependent manner, and its hemolytic activity was blocked by the addition of l-fucose. A protein ortholog construct from Aeromonas veronii was also produced and showed a similar glycan-binding pattern, binding affinity, erythrocyte-binding, and hemolytic activities. As demonstrated here with Hep-2 cells, fucose-based inhibitors of this sugar-binding domain can potentially be developed to block colonization by V. cholerae and other pathogenic bacteria that share this adhesin domain.IMPORTANCEThe bacterium, Vibrio cholerae, which causes cholera, uses an adhesion protein to stick to human cells and begin the infection process. One part of this adhesin protein binds to a particular sugar, fucose, on the surface of the target cells. This binding can lead to colonization and killing of the cells by the bacteria. Adding l-fucose to the bacteria before they bind to the human cells can prevent attachment and has promise as a preventative drug to protect against cholera.