Deleterious genetic changes in AGTPBP1 result in teratozoospermia with sperm head and flagella defects.

Approximately 10%-15% of couples worldwide are infertile, and male factors account for approximately half of these cases. Teratozoospermia is a major cause of male infertility. Although various mutations have been identified in teratozoospermia, these can vary among ethnic groups. In this study, we performed whole-exome sequencing to identify genetic changes potentially causative of teratozoospermia. Out of seven genes identified, one, ATP/GTP Binding Protein 1 (AGTPBP1), was characterized, and three missense changes were identified in two patients (Affected A: p.Glu423Asp and p.Pro631Leu; Affected B: p.Arg811His). In those two cases, severe sperm head and tail defects were observed. Moreover, AGTPBP1 localization showed a fragmented pattern compared to control participants, with specific localization in the neck and annulus regions. Using murine models, we found that AGTPBP1 is localized in the manchette structure, which is essential for sperm structure formation. Additionally, in Agtpbp1-null mice, we observed sperm head and tail defects similar to those in sperm from AGTPBP1-mutated cases, along with abnormal polyglutamylation tubulin and decreasing △-2 tubulin levels. In this study, we established a link between genetic changes in AGTPBP1 and human teratozoospermia for the first time and identified the role of AGTPBP1 in deglutamination, which is crucial for sperm formation.

NIgPred: Class-Specific Antibody Prediction for Linear B-Cell Epitopes Based on Heterogeneous Features and Machine-Learning Approaches.

Upon invasion by foreign pathogens, specific antibodies can identify specific foreign antigens and disable them. As a result of this ability, antibodies can help with vaccine production and food allergen detection in patients. Many studies have focused on predicting linear B-cell epitopes, but only two prediction tools are currently available to predict the sub-type of an epitope. NIgPred was developed as a prediction tool for IgA, IgE, and IgG. NIgPred integrates various heterologous features with machine-learning approaches. Differently from previous studies, our study considered peptide-characteristic correlation and autocorrelation features. Sixty kinds of classifier were applied to construct the best prediction model. Furthermore, the genetic algorithm and hill-climbing algorithm were used to select the most suitable features for improving the accuracy and reducing the time complexity of the training model. NIgPred was found to be superior to the currently available tools for predicting IgE epitopes and IgG epitopes on independent test sets. Moreover, NIgPred achieved a prediction accuracy of 100% for the IgG epitopes of a coronavirus data set. NIgPred is publicly available at our website.

QUATgo: Protein quaternary structural attributes predicted by two-stage machine learning approaches with heterogeneous feature encoding.

Many proteins exist in natures as oligomers with various quaternary structural attributes rather than as single chains. Predicting these attributes is an essential task in computational biology for the advancement of proteomics. However, the existing methods do not consider the integration of heterogeneous coding and the accuracy of subunit categories with limited data. To this end, we proposed a tool that can predict more than 12 subunit protein oligomers, QUATgo. Meanwhile, three kinds of sequence coding were used, including dipeptide composition, which was used for the first time to predict protein quaternary structural attributes, and protein half-life characteristics, and we modified the coding method of the functional domain composition proposed by predecessors to solve the problem of large feature vectors. QUATgo solves the problem of insufficient data for a single subunit using a two-stage architecture and uses 10-fold cross-validation to test the predictive accuracy of the classifier. QUATgo has 49.0% cross-validation accuracy and 31.1% independent test accuracy. In the case study, the accuracy of QUATgo can reach 61.5% for predicting the quaternary structure of influenza virus hemagglutinin proteins. Finally, QUATgo is freely accessible to the public as a web server via the site http://predictor.nchu.edu.tw/QUATgo.

SUMOgo: Prediction of sumoylation sites on lysines by motif screening models and the effects of various post-translational modifications.

Most modern tools used to predict sites of small ubiquitin-like modifier (SUMO) binding (referred to as SUMOylation) use algorithms, chemical features of the protein, and consensus motifs. However, these tools rarely consider the influence of post-translational modification (PTM) information for other sites within the same protein on the accuracy of prediction results. This study applied the Random Forest machine learning method, as well as motif screening models and a feature selection combination mechanism, to develop a SUMOylation prediction system, referred to as SUMOgo. With regard to prediction method, PTM sites were coded as new functional features in addition to structural features, such as sequence-based binary coding, encoded chemical features of proteins, and encoded secondary structure information that is important for PTM. Twenty cycles of prediction were conducted with a 1:1 combination of positive test data and random negative data. Matthew's correlation coefficient of SUMOgo reached 0.511, which is higher than that of current commonly used tools. This study further verified the important role of PTM in SUMOgo and includes a case study on CREB binding protein (CREBBP). The website for the final tool is http://predictor.nchu.edu.tw/SUMOgo .

Optimization-Based Image Reconstruction From Low-Count, List-Mode TOF-PET Data.

OBJECTIVE: We investigate an optimization-based approach to image reconstruction from list-mode data in digital time-of-flight (TOF) positron emission tomography (PET) imaging. METHOD: In the study, the image to be reconstructed is designed as a solution to a convex, non-smooth optimization program, and a primal-dual algorithm is developed for image reconstruction by solving the optimization program. The algorithm is first applied to list-mode TOF-PET data of a typical count level from physical phantoms and a human subject. Subsequently, we explore the algorithm's potential for image reconstruction in low-dose and/or fast TOF-PET imaging of practical interest by applying the algorithm to list-mode TOF-PET data of different, low-count levels from the same physical phantoms and human subject. RESULTS: Visual inspection and quantitative-metric analysis reveal that the optimization reconstruction approach investigated can yield images with enhanced spatial and contrast resolution, suppressed image noise, and increased axial volume coverage over the reference images obtained with a standard clinical reconstruction algorithm especially for low-dose TOF-PET data. SIGNIFICANCE: The optimization-based reconstruction approach can be exploited for yielding insights into potential quality upper bound of reconstructed images in, and design of scanning protocols of, TOF-PET imaging of practical significance.

Functional Characterization of Acinetobacter baumannii Lacking the RNA Chaperone Hfq.

The RNA chaperone Hfq is involved in the riboregulation of diverse genes via small RNAs. Recent studies have demonstrated that Hfq contributes to the stress response and the virulence of several pathogens, and the roles of Hfq vary among bacterial species. Here, we attempted to elucidate the role of Hfq in Acinetobacter baumannii ATCC 17978. In the absence of hfq, A. baumannii exhibited retarded cell growth and was highly sensitive to environmental stress, including osmotic and oxidative pressure, pH, and temperature. Compared to the wild-type, the Hfq mutant had reduced outer membrane vesicles secretion and fimbriae production as visualized by atomic force microscopy. The absence of hfq reduced biofilm formation, airway epithelial cell adhesion and invasion, and survival in macrophage. Further, the hfq mutant induced significantly higher IL-8 levels in airway epithelial cells, which would promote bacterial clearance by the host. In addition to results similar to those reported for other bacteria, our findings demonstrate that Hfq is required in the regulation of the iron-acquisition system via downregulating the bauA and basD genes, the stress-related outer membrane proteins carO, A1S_0820, ompA, and nlpE, and the stress-related cytosolic proteins uspA and groEL. Our data indicate that Hfq plays a critical role in environmental adaptation and virulence in A. baumannii by modulating stress responses, surface architectures, and virulence factors. This study is the first to illustrate the functional role of Hfq in A. baumannii.

Predicting human protein subcellular localization by heterogeneous and comprehensive approaches.

Drug development and investigation of protein function both require an understanding of protein subcellular localization. We developed a system, REALoc, that can predict the subcellular localization of singleplex and multiplex proteins in humans. This system, based on comprehensive strategy, consists of two heterogeneous systematic frameworks that integrate one-to-one and many-to-many machine learning methods and use sequence-based features, including amino acid composition, surface accessibility, weighted sign aa index, and sequence similarity profile, as well as gene ontology function-based features. REALoc can be used to predict localization to six subcellular compartments (cell membrane, cytoplasm, endoplasmic reticulum/Golgi, mitochondrion, nucleus, and extracellular). REALoc yielded a 75.3% absolute true success rate during five-fold cross-validation and a 57.1% absolute true success rate in an independent database test, which was >10% higher than six other prediction systems. Lastly, we analyzed the effects of Vote and GANN models on singleplex and multiplex localization prediction efficacy. REALoc is freely available at http://predictor.nchu.edu.tw/REALoc.

Longitudinal monitoring of reconstructed activity concentration on a clinical time-of-flight PET/CT scanner.

Positron emission tomography (PET) images are potential quantitative biomarkers. Understanding long-term (months/years) biomarker variability is important for establishing confidence intervals on studies using such biomarkers over these time frames. PET biomarkers are derived from activity concentration ([Formula: see text]) extracted from PET images. Over 30 months, we measured the stability of decay-normalized counts ([Formula: see text]) and [Formula: see text] by scanning the same 4.5-cm-diameter Ge-68 cylinder weekly, the same Na-22 point source daily, and a refilled 20-cm F-18 cylinder phantom monthly on a clinical TOF-PET/CT scanner. Longitudinal and adjacent-measurement variability was characterized. We found no drift in [Formula: see text] or [Formula: see text] for properly calibrated images over 24 months. During this time, [Formula: see text] ranged [Formula: see text] to 6% for count-matched Ge-68 and F-18 images, with coefficient of variation (COV) across time of 2.3% (Ge-68, 81 scans) and 3.2% (F-18, 24 scans). At typical patient image count levels the Ge-68 [Formula: see text] ([Formula: see text]) COV across time was 6.9% (9.6%). Changes in [Formula: see text] between adjacent F-18 scans ([Formula: see text]) ranged between [Formula: see text], with corresponding date-matched changes in Ge-68 [Formula: see text] ranging [Formula: see text]. We recommend (1) tracking trends in [Formula: see text] with image [Formula: see text] as a check of quantitative data corrections/calibrations and (2) tracking both mean and COV of [Formula: see text] (single time point measures) to hundredths precision using standardized uptake values.

QuaBingo: A Prediction System for Protein Quaternary Structure Attributes Using Block Composition.

Background. Quaternary structures of proteins are closely relevant to gene regulation, signal transduction, and many other biological functions of proteins. In the current study, a new method based on protein-conserved motif composition in block format for feature extraction is proposed, which is termed block composition. Results. The protein quaternary assembly states prediction system which combines blocks with functional domain composition, called QuaBingo, is constructed by three layers of classifiers that can categorize quaternary structural attributes of monomer, homooligomer, and heterooligomer. The building of the first layer classifier uses support vector machines (SVM) based on blocks and functional domains of proteins, and the second layer SVM was utilized to process the outputs of the first layer. Finally, the result is determined by the Random Forest of the third layer. We compared the effectiveness of the combination of block composition, functional domain composition, and pseudoamino acid composition of the model. In the 11 kinds of functional protein families, QuaBingo is 23% of Matthews Correlation Coefficient (MCC) higher than the existing prediction system. The results also revealed the biological characterization of the top five block compositions. Conclusions. QuaBingo provides better predictive ability for predicting the quaternary structural attributes of proteins.

Investigation of optimization-based reconstruction with an image-total-variation constraint in PET.

Interest remains in reconstruction-algorithm research and development for possible improvement of image quality in current PET imaging and for enabling innovative PET systems to enhance existing, and facilitate new, preclinical and clinical applications. Optimization-based image reconstruction has been demonstrated in recent years of potential utility for CT imaging applications. In this work, we investigate tailoring the optimization-based techniques to image reconstruction for PET systems with standard and non-standard scan configurations. Specifically, given an image-total-variation (TV) constraint, we investigated how the selection of different data divergences and associated parameters impacts the optimization-based reconstruction of PET images. The reconstruction robustness was explored also with respect to different data conditions and activity up-takes of practical relevance. A study was conducted particularly for image reconstruction from data collected by use of a PET configuration with sparsely populated detectors. Overall, the study demonstrates the robustness of the TV-constrained, optimization-based reconstruction for considerably different data conditions in PET imaging, as well as its potential to enable PET configurations with reduced numbers of detectors. Insights gained in the study may be exploited for developing algorithms for PET-image reconstruction and for enabling PET-configuration design of practical usefulness in preclinical and clinical applications.

fastSCOP: a fast web server for recognizing protein structural domains and SCOP superfamilies.

The fastSCOP is a web server that rapidly identifies the structural domains and determines the evolutionary superfamilies of a query protein structure. This server uses 3D-BLAST to scan quickly a large structural classification database (SCOP1.71 with <95% identity with each other) and the top 10 hit domains, which have different superfamily classifications, are obtained from the hit lists. MAMMOTH, a detailed structural alignment tool, is adopted to align these top 10 structures to refine domain boundaries and to identify evolutionary superfamilies. Our previous works demonstrated that 3D-BLAST is as fast as BLAST, and has the characteristics of BLAST (e.g. a robust statistical basis, effective search and reliable database search capabilities) in large structural database searches based on a structural alphabet database and a structural alphabet substitution matrix. The classification accuracy of this server is approximately 98% for 586 query structures and the average execution time is approximately 5. This server was also evaluated on 8700 structures, which have no annotations in the SCOP; the server can automatically assign 7311 (84%) proteins (9420 domains) to the SCOP superfamilies in 9.6 h. These results suggest that the fastSCOP is robust and can be a useful server for recognizing the evolutionary classifications and the protein functions of novel structures. The server is accessible at http://fastSCOP.life.nctu.edu.tw.

Kappa-alpha plot derived structural alphabet and BLOSUM-like substitution matrix for rapid search of protein structure database.

We present a novel protein structure database search tool, 3D-BLAST, that is useful for analyzing novel structures and can return a ranked list of alignments. This tool has the features of BLAST (for example, robust statistical basis, and effective and reliable search capabilities) and employs a kappa-alpha (kappa, alpha) plot derived structural alphabet and a new substitution matrix. 3D-BLAST searches more than 12,000 protein structures in 1.2 s and yields good results in zones with low sequence similarity.

Protein structure database search and evolutionary classification.

As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].