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Medicine Jun 2024Thyroglossal duct carcinoma, a rare clinical condition characterized by ectopic thyroid adenocarcinoma within thyroglossal duct cysts (TGDCs), typically confirmed... (Review)
Review
RATIONALE
Thyroglossal duct carcinoma, a rare clinical condition characterized by ectopic thyroid adenocarcinoma within thyroglossal duct cysts (TGDCs), typically confirmed through intraoperative rapid pathology, this condition generally has a favorable prognosis. Nevertheless, comprehensive treatment guidelines across all disease stages are lacking, the purpose of this study is to report 1 case of the disease and propose the treatment plan for each stage of the disease.
PATIENT CONCERNS
A patient presented with thyroid swelling, classified as C-TIRADS 4A following a physical examination. Preoperative thyroid puncture identified papillary thyroid carcinoma, and genetic testing revealed a BRAF gene exon 15-point mutation. Ancillary tests showed a slightly decreased thyroid stimulating hormone (TSH) level (0.172) with no other significant abnormalities.
DIAGNOSES
Preoperative fine-needle aspiration cytology (FNAC) confirmed right-side thyroid cancer. Intraoperative exploration uncovered a TGDC and intraoperative rapid pathology confirmed thyroglossal duct carcinoma.
INTERVENTIONS
A Sistrunk operation and ipsilateral thyroidectomy were performed.
OUTCOMES
Postoperative recovery was satisfactory.
LESSONS
Thyroglossal duct carcinoma is a rare disease affecting the neck. Due to limited clinical cases and the favorable prognosis associated with this condition, there is currently no established set of diagnostic and treatment guidelines. According to tumor size, lymph node metastasis, thyroid status and other factors, the corresponding treatment methods were established for each stage of thyroglossal duct cancer, which laid the foundation for the subsequent treatment development of this disease.
Topics: Humans; Thyroglossal Cyst; Thyroid Neoplasms; Thyroid Cancer, Papillary; Female; Thyroidectomy; Male; Proto-Oncogene Proteins B-raf; Adult; Biopsy, Fine-Needle
PubMed: 38941410
DOI: 10.1097/MD.0000000000038540 -
ELife Jun 2024Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we...
Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also observe functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.
Topics: SARS-CoV-2; Coronavirus Nucleocapsid Proteins; Mutation; COVID-19; Humans; Intrinsically Disordered Proteins; Phosphoproteins; Nucleocapsid Proteins; Thermodynamics; Protein Stability
PubMed: 38941236
DOI: 10.7554/eLife.94836 -
Bioinformatics (Oxford, England) Jun 2024Mutations are the crucial driving force for biological evolution as they can disrupt protein stability and protein-protein interactions which have notable impacts on...
MOTIVATION
Mutations are the crucial driving force for biological evolution as they can disrupt protein stability and protein-protein interactions which have notable impacts on protein structure, function, and expression. However, existing computational methods for protein mutation effects prediction are generally limited to single point mutations with global dependencies, and do not systematically take into account the local and global synergistic epistasis inherent in multiple point mutations.
RESULTS
To this end, we propose a novel spatial and sequential message passing neural network, named DDAffinity, to predict the changes in binding affinity caused by multiple point mutations based on protein 3D structures. Specifically, instead of being on the whole protein, we perform message passing on the k-nearest neighbor residue graphs to extract pocket features of the protein 3D structures. Furthermore, to learn global topological features, a two-step additive Gaussian noising strategy during training is applied to blur out local details of protein geometry. We evaluate DDAffinity on benchmark datasets and external validation datasets. Overall, the predictive performance of DDAffinity is significantly improved compared with state-of-the-art baselines on multiple point mutations, including end-to-end and pre-training based methods. The ablation studies indicate the reasonable design of all components of DDAffinity. In addition, applications in nonredundant blind testing, predicting mutation effects of SARS-CoV-2 RBD variants, and optimizing human antibody against SARS-CoV-2 illustrate the effectiveness of DDAffinity.
AVAILABILITY AND IMPLEMENTATION
DDAffinity is available at https://github.com/ak422/DDAffinity.
Topics: Point Mutation; SARS-CoV-2; Computational Biology; Protein Conformation; Humans; Neural Networks, Computer; Protein Binding; COVID-19; Proteins; Algorithms
PubMed: 38940145
DOI: 10.1093/bioinformatics/btae232 -
Bioinformatics (Oxford, England) Jun 2024Insertions and deletions (indels) influence the genetic code in fundamentally distinct ways from substitutions, significantly impacting gene product structure and...
MOTIVATION
Insertions and deletions (indels) influence the genetic code in fundamentally distinct ways from substitutions, significantly impacting gene product structure and function. Despite their influence, the evolutionary history of indels is often neglected in phylogenetic tree inference and ancestral sequence reconstruction, hindering efforts to comprehend biological diversity determinants and engineer variants for medical and industrial applications.
RESULTS
We frame determining the optimal history of indel events as a single Mixed-Integer Programming (MIP) problem, across all branch points in a phylogenetic tree adhering to topological constraints, and all sites implied by a given set of aligned, extant sequences. By disentangling the impact on ancestral sequences at each branch point, this approach identifies the minimal indel events that jointly explain the diversity in sequences mapped to the tips of that tree. MIP can recover alternate optimal indel histories, if available. We evaluated MIP for indel inference on a dataset comprising 15 real phylogenetic trees associated with protein families ranging from 165 to 2000 extant sequences, and on 60 synthetic trees at comparable scales of data and reflecting realistic rates of mutation. Across relevant metrics, MIP outperformed alternative parsimony-based approaches and reported the fewest indel events, on par or below their occurrence in synthetic datasets. MIP offers a rational justification for indel patterns in extant sequences; importantly, it uniquely identifies global optima on complex protein data sets without making unrealistic assumptions of independence or evolutionary underpinnings, promising a deeper understanding of molecular evolution and aiding novel protein design.
AVAILABILITY AND IMPLEMENTATION
The implementation is available via GitHub at https://github.com/santule/indelmip.
Topics: Phylogeny; INDEL Mutation; Evolution, Molecular; Algorithms; Computational Biology
PubMed: 38940131
DOI: 10.1093/bioinformatics/btae254 -
Biology Methods & Protocols 2024Real-time polymerase chain reaction (real-time PCR) is a powerful tool for the precise quantification of nucleic acids in various applications. In cancer management, the...
Real-time polymerase chain reaction (real-time PCR) is a powerful tool for the precise quantification of nucleic acids in various applications. In cancer management, the monitoring of circulating tumor DNA (ctDNA) from liquid biopsies can provide valuable information for precision care, including treatment selection and monitoring, prognosis, and early detection. However, the rare and heterogeneous nature of ctDNA has made its precise detection and quantification challenging, particularly for ctDNA containing hotspot mutations. We have developed a new real-time PCR tool, PROMER technology, which enables the precise and sensitive detection of ctDNA containing cancer-driven single-point mutations. The PROMER functions as both a PRObe and priMER, providing enhanced detection specificity. We validated PROMER technology using synthetic templates with known KRAS point mutations and demonstrated its sensitivity and linearity of quantification. Using genomic DNA from human cancer cells with mutant and wild-type KRAS, we confirmed that PROMER PCR can detect mutant DNA. Furthermore, we demonstrated the ability of PROMER technology to efficiently detect mutation-carrying ctDNA from the plasma of mice with human cancers. Our results suggest that PROMER technology represents a promising new tool for the precise detection and quantification of DNA containing point mutations in the presence of a large excess of wild-type counterpart.
PubMed: 38938409
DOI: 10.1093/biomethods/bpae041 -
MSystems Jun 2024The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial...
UNLABELLED
The alarming rise of antibiotic-resistant bacterial infections is driving efforts to develop alternatives to conventional antibiotics. In this context, antimicrobial peptides (AMPs) have emerged as promising candidates for their ability to target a broad range of microorganisms. However, the development of AMPs with optimal potency, selectivity, and/or stability profiles remains a challenge. To address it, computational tools for predicting AMP properties and designing novel peptides have gained increasing attention. PyAMPA is a novel platform for AMP discovery. It consists of five modules, namely AMPScreen, AMPValidate, AMPSolve, AMPMutate, and AMPOptimize, that allow high-throughput proteome inspection, candidate screening, and optimization through point-mutation and genetic algorithms. The platform also offers additional tools for predicting and evaluating AMP properties, including antimicrobial and cytotoxic activity, and peptide half-life. By providing innovative and accessible inroads into AMP motifs in proteomes, PyAMPA will enable advances in AMP development and potential translation into clinically useful molecules. PyAMPA is available at: https://github.com/SysBioUAB/PyAMPA.
IMPORTANCE
This paper introduces PyAMPA, a new bioinformatics platform designed for the discovery and optimization of antimicrobial peptides (AMPs). It addresses the urgent need for new antimicrobials due to the rise of antibiotic-resistant infections. PyAMPA, with its five predictive modules -AMPScreen, AMPValidate, AMPSolve, AMPMutate and AMPOptimize, enables high-throughput screening of proteomes to identify potential AMP motifs and optimize them for clinical use. Its unique approach, combining prediction, design, and optimization tools, makes PyAMPA a robust solution for developing new AMP-based therapies, offering a significant advance in combatting antibiotic resistance.
PubMed: 38934543
DOI: 10.1128/msystems.01358-23 -
Emerging Microbes & Infections Dec 2024A positive-sense (+) single-stranded RNA (ssRNA) virus (e.g. enterovirus A71, EV-A71) depends on viral polypeptide translation for initiation of virus replication after...
A positive-sense (+) single-stranded RNA (ssRNA) virus (e.g. enterovirus A71, EV-A71) depends on viral polypeptide translation for initiation of virus replication after entry. We reported that EV-A71 hijacks Hsp27 to induce hnRNP A1 cytosol redistribution to initiate viral protein translation, but the underlying mechanism is still elusive. Here, we show that phosphorylation-deficient Hsp27-3A (Hsp27) and Hsp27 fail to translocate into the nucleus and induce hnRNP A1 cytosol redistribution, while Hsp27 and Hsp27 display similar effects to the wild type Hsp27. Furthermore, we demonstrate that the viral 2A protease (2A) activity is a key factor in regulating Hsp27/hnRNP A1 relocalization. Hsp27 dramatically decreases the IRES activity and viral replication, which are partially reduced by Hsp27. However, Hsp27 displays the same activity as the wild-type Hsp27. Peptide S78 potently suppresses EV-A71 protein translation and reproduction through blockage of EV-A71-induced Hsp27 phosphorylation and Hsp27/hnRNP A1 relocalization. A point mutation (S78A) on S78 impairs its inhibitory functions on Hsp27/hnRNP A1 relocalization and viral replication. Taken together, we demonstrate the importance of Ser78 phosphorylation of Hsp27 regulated by virus infection in nuclear translocation, hnRNP A1 cytosol relocation, and viral replication, suggesting a new path (such as peptide S78) for target-based antiviral strategy.
Topics: Enterovirus A, Human; Phosphorylation; Humans; Virus Replication; Heterogeneous Nuclear Ribonucleoprotein A1; HSP27 Heat-Shock Proteins; Enterovirus Infections; Antiviral Agents; Viral Proteins; Serine; HeLa Cells; Protein Biosynthesis; Cysteine Endopeptidases; Molecular Chaperones; Heat-Shock Proteins
PubMed: 38932432
DOI: 10.1080/22221751.2024.2368221 -
Viruses May 2024When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection or reverse-genetic...
When designing live-attenuated respiratory syncytial virus (RSV) vaccine candidates, attenuating mutations can be developed through biologic selection or reverse-genetic manipulation and may include point mutations, codon and gene deletions, and genome rearrangements. Attenuation typically involves the reduction in virus replication, due to direct effects on viral structural and replicative machinery or viral factors that antagonize host defense or cause disease. However, attenuation must balance reduced replication and immunogenic antigen expression. In the present study, we explored a new approach in order to discover attenuating mutations. Specifically, we used protein structure modeling and computational methods to identify amino acid substitutions in the RSV nonstructural protein 1 (NS1) predicted to cause various levels of structural perturbation. Twelve different mutations predicted to alter the NS1 protein structure were introduced into infectious virus and analyzed in cell culture for effects on viral mRNA and protein expression, interferon and cytokine expression, and caspase activation. We found the use of structure-based machine learning to predict amino acid substitutions that reduce the thermodynamic stability of NS1 resulted in various levels of loss of NS1 function, exemplified by effects including reduced multi-cycle viral replication in cells competent for type I interferon, reduced expression of viral mRNAs and proteins, and increased interferon and apoptosis responses.
Topics: Humans; Machine Learning; Viral Nonstructural Proteins; Respiratory Syncytial Virus Vaccines; Respiratory Syncytial Virus, Human; Virus Replication; Vaccines, Attenuated; Respiratory Syncytial Virus Infections; Amino Acid Substitution; Mutation; Cell Line
PubMed: 38932114
DOI: 10.3390/v16060821 -
International Journal of Molecular... Jun 2024is an important opportunistic pathogenic bacterium widely distributed in the environment. Pyolysin (PLO) is a primary virulence factor of and capable of lysing many...
is an important opportunistic pathogenic bacterium widely distributed in the environment. Pyolysin (PLO) is a primary virulence factor of and capable of lysing many different cells. PLO is a member of the cholesterol-dependent cytolysin (CDC) family of which the primary structure only presents a low level of homology with other members from 31% to 45%. By deeply studying PLO, we can understand the overall pathogenic mechanism of CDC family proteins. This study established a mouse muscle tissue model infected with recombinant PLO (rPLO) and its single-point mutations, rPLO N139K and rPLO F240A, and explored its mechanism of causing inflammatory damage. The inflammatory injury abilities of rPLO N139K and rPLO F240A are significantly reduced compared to rPLO. This study elaborated on the inflammatory mechanism of PLO by examining its unit point mutations in detail. Our data also provide a theoretical basis and practical significance for future research on toxins and bacteria.
Topics: Animals; Point Mutation; Mice; Hemolysin Proteins; NLR Family, Pyrin Domain-Containing 3 Protein; Bacterial Proteins; Inflammation; Potassium; Signal Transduction; Bacterial Toxins; Inflammasomes; Humans
PubMed: 38928408
DOI: 10.3390/ijms25126703 -
International Journal of Molecular... Jun 2024Our study investigates the genetic mechanisms underlying the spotted leaf phenotype in rice, focusing on the mutant. This mutant is characterized by persistent...
Our study investigates the genetic mechanisms underlying the spotted leaf phenotype in rice, focusing on the mutant. This mutant is characterized by persistent reddish-brown leaf spots from the seedling stage to maturity, leading to extensive leaf necrosis. Using map-based cloning, we localized the responsible locus to a 330 Kb region on chromosome 2. We identified , named , as the causative gene. A point mutation in , substituting valine for glutamic acid, was identified as the critical factor for the phenotype. Functional complementation and the generation of CRISPR/Cas9-mediated knockout lines in the IR64 background confirmed the central role of OsRPT5A in controlling this trait. The qPCR results from different parts of the rice plant revealed that is constitutively expressed across various tissues, with its subcellular localization unaffected by the mutation. Notably, we observed an abnormal accumulation of reactive oxygen species (ROS) in mutants by examining the physiological indexes of leaves, suggesting a disruption in the ROS system. Complementation studies indicated OsRPT5A's involvement in ROS homeostasis and catalase activity regulation. Moreover, the mutant exhibited enhanced resistance to pv. (), highlighting OsRPT5A's role in rice pathogen resistance mechanisms. Overall, our results suggest that OsRPT5A plays a critical role in regulating ROS homeostasis and enhancing pathogen resistance in rice.
Topics: Oryza; Plant Leaves; Plant Proteins; Chromosome Mapping; Xanthomonas; Plant Diseases; Reactive Oxygen Species; Disease Resistance; Mutation; Phenotype; Gene Expression Regulation, Plant
PubMed: 38928342
DOI: 10.3390/ijms25126637