iDVEIP: A computer-aided approach for the prediction of viral entry inhibitory peptides.

With the notable surge in therapeutic peptide development, various peptides have emerged as potential agents against virus-induced diseases. Viral entry inhibitory peptides (VEIPs), a subset of antiviral peptides (AVPs), offer a promising avenue as entry inhibitors (EIs) with distinct advantages over chemical counterparts. Despite this, a comprehensive analytical platform for characterizing these peptides and their effectiveness in blocking viral entry remains lacking. In this study, we introduce a groundbreaking in silico approach that leverages bioinformatics analysis and machine learning to characterize and identify novel VEIPs. Cross-validation results demonstrate the efficacy of a model combining sequence-based features in predicting VEIPs with high accuracy, validated through independent testing. Additionally, an EI type model has been developed to distinguish peptides specifically acting as Eis from AVPs with alternative activities. Notably, we present iDVEIP, a web-based tool accessible at http://mer.hc.mmh.org.tw/iDVEIP/, designed for automatic analysis and prediction of VEIPs. Emphasizing its capabilities, the tool facilitates comprehensive analyses of peptide characteristics, providing detailed amino acid composition data for each prediction. Furthermore, we showcase the tool's utility in identifying EIs against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

Efficient methods for multiple types of precise gene-editing in Chlamydomonas.

Precise gene-editing using CRISPR/Cas9 technology remains a long-standing challenge, especially for genes with low expression and no selectable phenotypes in Chlamydomonas reinhardtii, a classic model for photosynthesis and cilia research. Here, we developed a multi-type and precise genetic manipulation method in which a DNA break was generated by Cas9 nuclease and the repair was mediated using a homologous DNA template. The efficacy of this method was demonstrated for several types of gene editing, including inactivation of two low-expression genes (CrTET1 and CrKU80), the introduction of a FLAG-HA epitope tag into VIPP1, IFT46, CrTET1 and CrKU80 genes, and placing a YFP tag into VIPP1 and IFT46 for live-cell imaging. We also successfully performed a single amino acid substitution for the FLA3, FLA10 and FTSY genes, and documented the attainment of the anticipated phenotypes. Lastly, we demonstrated that precise fragment deletion from the 3'-UTR of MAA7 and VIPP1 resulted in a stable knock-down effect. Overall, our study has established efficient methods for multiple types of precise gene editing in Chlamydomonas, enabling substitution, insertion and deletion at the base resolution, thus improving the potential of this alga in both basic research and industrial applications.

iDVIP: identification and characterization of viral integrase inhibitory peptides.

Antiretroviral peptides are a kind of bioactive peptides that present inhibitory activity against retroviruses through various mechanisms. Among them, viral integrase inhibitory peptides (VINIPs) are a class of antiretroviral peptides that have the ability to block the action of integrase proteins, which is essential for retroviral replication. As the number of experimentally verified bioactive peptides has increased significantly, the lack of in silico machine learning approaches can effectively predict the peptides with the integrase inhibitory activity. Here, we have developed the first prediction model for identifying the novel VINIPs using the sequence characteristics, and the hybrid feature set was considered to improve the predictive ability. The performance was evaluated by 5-fold cross-validation based on the training dataset, and the result indicates the proposed model is capable of predicting the VINIPs, with a sensitivity of 85.82%, a specificity of 88.81%, an accuracy of 88.37%, a balanced accuracy of 87.32% and a Matthews correlation coefficient value of 0.64. Most importantly, the model also consistently provides effective performance in independent testing. To sum up, we propose the first computational approach for identifying and characterizing the VINIPs, which can be considered novel antiretroviral therapy agents. Ultimately, to facilitate further research and development, iDVIP, an automatic computational tool that predicts the VINIPs has been developed, which is now freely available at http://mer.hc.mmh.org.tw/iDVIP/.

Integrating In Silico and In Vitro Approaches to Identify Natural Peptides with Selective Cytotoxicity against Cancer Cells.

Anticancer peptides (ACPs) are bioactive compounds known for their selective cytotoxicity against tumor cells via various mechanisms. Recent studies have demonstrated that in silico machine learning methods are effective in predicting peptides with anticancer activity. In this study, we collected and analyzed over a thousand experimentally verified ACPs, specifically targeting peptides derived from natural sources. We developed a precise prediction model based on their sequence and structural features, and the model's evaluation results suggest its strong predictive ability for anticancer activity. To enhance reliability, we integrated the results of this model with those from other available methods. In total, we identified 176 potential ACPs, some of which were synthesized and further evaluated using the MTT colorimetric assay. All of these putative ACPs exhibited significant anticancer effects and selective cytotoxicity against specific tumor cells. In summary, we present a strategy for identifying and characterizing natural peptides with selective cytotoxicity against cancer cells, which could serve as novel therapeutic agents. Our prediction model can effectively screen new molecules for potential anticancer activity, and the results from in vitro experiments provide compelling evidence of the candidates' anticancer effects and selective cytotoxicity.

Transdermal nanolipoplex simultaneously inhibits subcutaneous melanoma growth and suppresses systemically metastatic melanoma by activating host immunity.

Benefit for clinical melanoma treatments, the transdermal neoadjuvant therapy could reduce surgery region and increase immunotherapy efficacy. Using lipoplex (Lipo-PEG-PEI-complex, LPPC) encapsulated doxorubicin (DOX) and carrying CpG oligodeoxynucleotide; the transdermally administered nano-liposomal drug complex (LPPC-DOX-CpG) would have high cytotoxicity and immunostimulatory activity to suppress systemic metastasis of melanoma. LPPC-DOX-CpG dramatically suppressed subcutaneous melanoma growth by inducing tumor cell apoptosis and recruiting immune cells into the tumor area. Animal studies further showed that the colonization and growth of spontaneously metastatic melanoma cells in the liver and lung were suppressed by transdermal LPPC-DOX-CpG. Furthermore, NGS analysis revealed IFN-γ and NF-κB pathways were triggered to recruit and activate the antigen-presenting-cells and effecter cells, which could activate the anti-tumor responses as the major mechanism responsible for the therapeutic effect of LPPC-DOX-CpG. Finally, we have successfully proved transdermal LPPC-DOX-CpG as a promising penetrative carrier to activate systemic anti-tumor immunity against subcutaneous and metastatic tumor.

M-Sn-Q (M = Zn, Cd; Q = S, Se) Compounds Templated by (Alkyl)ammonium Species: Synthesis, Crystal Structure, and Sr2+ Adsorption Property.

Deep investigations on the synthetic and structural chemistry of heterometallic chalcogenidostannates bear fundamental significance for the establishment of the structure-property relationship that would offer guidance on the functional material innovation. Presented here are four ammonium- and/or alkylammonium-directed M-Sn-Q (M = Zn, Cd; Q = S, Se) compounds, namely, [NH4]7[H3O]3Zn4Sn4S17 (1), [NH4]5[(CH3)2NH2]Zn4Sn5S17 (2), [CH3CH2NH3]22Zn16Sn12Se51(H2O)4·16H2O (3), and [NH4]2CdSnSe4 (4). All four compounds were synthesized in deep eutectic solvents (DESs) or ethylamine aqueous solution, both of which function simultaneously as reaction media and structure-directing agents. Compound 1 consists of discrete P1-[Zn4Sn4S17]10- clusters templated by mixed [NH4]+/[H3O]+ cations. In compound 2, such P1 clusters are bridged by Sn4+ ions in a 4,4-connection mode to form a [Zn4Sn5S17]n6n- framework with three types of cavities (I-III) varying in size. The two smaller cavities (I and II) accommodate NH4+ while the larger one(III) is occupied by [(CH3)2NH2]+, reflecting the rational size-dependence of cations on cavities. Compound 3 features an [Zn16Sn12Se51(H2O)4]n22n- open framework constructed from the 4,3-connection of P1-[Zn4Sn4Se17]10- clusters and {Zn(H2O)}2+ bridges. This linkage mode contributes to a large cage-like subunit (inner dimension: 21.99 × 9.06 Å2) and therefore an ultrahigh porosity that are occupied by [CH3CH2NH3]+ cations and water molecules (volume fraction: 57.7%). Compound 4 exists as a stacking of [CdSnSe4]n2n- chains, which are composed of alternatively arranged {CdSe4} and {SnSe4} tetrahedra, in combination with [NH4]+ cations as both charge-compensating and space-filling agents. Detailed synthetic, structural, and topological analyses were performed on these solid materials, coupled with extensive investigations on their optical and thermal properties. Compound 3 exhibits an efficient Sr2+ adsorption performance, featuring ultrafast kinetics (94.69% in 5 min), high removal rate (98.57% in 20 min) at equilibrium, and high capacity (104.17 ± 23.53 mg g-1).

Tailoring Hybrid Aluminoborate Frameworks by Incorporating Multicomponent Cadmium-Amine Complexes with Various Conformations.

Inorganic-organic hybrid aluminoborates represent a subclass of porous materials, which rely on effective construction method and structure-directing agents. Herein, we prepared a series of hybrid aluminoborates through covalent decoration of unsaturated Cd2+ complexes, whose formation take advantage of chelating amine and long-chain diamine as mixed ligands. These isolated compounds, that is, [Cd(en)(1,4-dab)0.5][AlB5O10] (1a; its analogue with discrete complex [Cd(en)(dien)H2O][AlB5O10] is denoted as 1b), [Cd(1,2-dap)1.5(1,4-dabH)0.5]{Al[B5O8(OH)2](B5O10)0.5} (2), and [Cd(en)(1,3-dap)][AlB5O10] (3) feature open frameworks (1a, 1b, and 3) or a sandwich-like porous layer (2) that are constructed by AlO4 tetrahedra and [B5O10]5-/[B5O8(OH)2]3- clusters. However, they exhibit different structural features in interconnection, channel environment, and topology as a result of diversified interactions between unsaturated complexes and aluminoborate frameworks, that is, through forming two Cd-O bonds with (i) a pair of neighboring BO3 and AlO4, (ii) the same AlO4, or (iii) the same BO3. The variation in connection mode exerts essential influence on binding effects and steric hindrance that are reflected by changes in interatomic distance, bond angle, window configuration, and interlinkage of units. In addition, the incorporation of unsaturated Cd2+ complexes endows these aluminoborate materials with photoluminescence function. Compound 3 with a noncentrosymmetric structure exhibits second harmonic generation (SHG) response approximately 0.7 times that of KDP. The preparation strategy for hybrid aluminoborates proposed here combines well molecular design with templating assembly, whose synergistic effect would be crucial for drawing a rational pathway for inorganic synthesis, especially with focus on structural and functional innovation.

Anticancer peptide Q7 suppresses the growth and migration of human endometrial cancer by inhibiting DHCR24 expression and modulating the AKT-mediated pathway.

Endometrial cancer is one of the most common malignancy affecting women in developed countries. Resection uterus or lesion area is usually the first option for a simple and efficient therapy. Therefore, it is necessary to find a new therapeutic drug to reduce surgery areas to preserve fertility. Anticancer peptides (ACP) are bioactive amino acids with lower toxicity and higher specificity than chemical drugs. This study is to address an ACP, herein named Q7, which could downregulate 24-Dehydrocholesterol Reductase (DHCR24) to disrupt lipid rafts formation, and sequentially affect the AKT signal pathway of HEC-1-A cells to suppress their tumorigenicity such as proliferation and migration. Moreover, lipo-PEI-PEG-complex (LPPC) was used to enhance Q7 anticancer activity in vitro and efficiently show its effects on HEC-1-A cells. Furthermore, LPPC-Q7 exhibited a synergistic effect in combination with doxorubicin or paclitaxel. To summarize, Q7 was firstly proved to exhibit an anticancer effect on endometrial cancer cells and combined with LPPC efficiently improved the cytotoxicity of Q7.

miRTarBase 2020: updates to the experimentally validated microRNA-target interaction database.

MicroRNAs (miRNAs) are small non-coding RNAs (typically consisting of 18-25 nucleotides) that negatively control expression of target genes at the post-transcriptional level. Owing to the biological significance of miRNAs, miRTarBase was developed to provide comprehensive information on experimentally validated miRNA-target interactions (MTIs). To date, the database has accumulated >13,404 validated MTIs from 11,021 articles from manual curations. In this update, a text-mining system was incorporated to enhance the recognition of MTI-related articles by adopting a scoring system. In addition, a variety of biological databases were integrated to provide information on the regulatory network of miRNAs and its expression in blood. Not only targets of miRNAs but also regulators of miRNAs are provided to users for investigating the up- and downstream regulations of miRNAs. Moreover, the number of MTIs with high-throughput experimental evidence increased remarkably (validated by CLIP-seq technology). In conclusion, these improvements promote the miRTarBase as one of the most comprehensively annotated and experimentally validated miRNA-target interaction databases. The updated version of miRTarBase is now available at http://miRTarBase.cuhk.edu.cn/.

Involvement of AMPKα and MAPK-ERK/-JNK Signals in Docetaxel-Induced Human Tongue Squamous Cell Carcinoma Cell Apoptosis.

Cancers of the oral cavity can develop in the anatomic area extending from the lip, gum, tongue, mouth, and to the palate. Histologically, about 85-90% of oral cavity cancers are of the type squamous cells carcinomas (SCCs). The incidence of oral tongue SCC is higher in the tongue than any other anatomic area of the oral cavity. Here, we investigated the therapeutic effects and molecular mechanisms of docetaxel, which is a paclitaxel antitumor agent, on the cell growth of a human tongue SCC-derived SAS cell line. The results showed that docetaxel (10-300 nM) induced cytotoxicity and caspase-3 activity in SAS cells. Moreover, docetaxel (100 nM) promoted the expression of apoptosis-related signaling molecules, including the cleavages of caspase-3, caspase-7, and poly (ADP-ribose) polymerase (PARP). In mitochondria, docetaxel (100 nM) decreased the mitochondrial membrane potential (MMP) and Bcl-2 mRNA and protein expression and increased cytosolic cytochrome c protein expression and Bax mRNA and protein expression. In terms of mitogen-activated protein kinase (MAPK) and adenosine monophosphate-activated protein kinase (AMPK) signaling, docetaxel increased the expression of phosphorylated (p)-extracellular signal-regulated kinase (ERK), p-c-Jun N-terminal kinase (JNK), and p-AMPKα protein expression but not p-p38 protein expression. Moreover, the increase in caspase-3/-7 activity and Bax protein expression and decreased Bcl-2 protein expression and MMP depolarization observed in docetaxel-treated SAS cells could be reversed by treatment with either SP600125 (a JNK inhibitor), PD98059 (an MEK1/2 (mitogen-activated protein kinase kinase 1/2) inhibitor), or compound c (an AMPK inhibitor). The docetaxel-induced increases in p-JNK, p-ERK, and p-AMPKα protein expression could also be reversed by treatment with either SP600125, PD98059, or compound c. These results indicate that docetaxel induces human tongue SCC cell apoptosis via interdependent MAPK-JNK, MAPK-ERK1/2, and AMPKα signaling pathways. Our results show that docetaxel could possibly exert a potent pharmacological effect on human oral tongue SCC cell growth.

Norketamine, the Main Metabolite of Ketamine, Induces Mitochondria-Dependent and ER Stress-Triggered Apoptotic Death in Urothelial Cells via a Ca2+-Regulated ERK1/2-Activating Pathway.

Ketamine-associated cystitis is characterized by suburothelial inflammation and urothelial cell death. Norketamine (NK), the main metabolite of ketamine, is abundant in urine following ketamine exposure. NK has been speculated to exert toxic effects in urothelial cells, similarly to ketamine. However, the molecular mechanisms contributing to NK-induced urothelial cytotoxicity are almost unclear. Here, we aimed to investigate the toxic effects of NK and the potential mechanisms underlying NK-induced urothelial cell injury. In this study, NK exposure significantly reduced cell viability and induced apoptosis in human urinary bladder epithelial-derived RT4 cells that NK (0.01-0.5 mM) exhibited greater cytotoxicity than ketamine (0.1-3 mM). Signals of mitochondrial dysfunction, including mitochondrial membrane potential (MMP) loss and cytosolic cytochrome c release, were found to be involved in NK-induced cell apoptosis and death. NK exposure of cells also triggered the expression of endoplasmic reticulum (ER) stress-related proteins including GRP78, CHOP, XBP-1, ATF-4 and -6, caspase-12, PERK, eIF-2α, and IRE-1. Pretreatment with 4-phenylbutyric acid (an ER stress inhibitor) markedly prevented the expression of ER stress-related proteins and apoptotic events in NK-exposed cells. Additionally, NK exposure significantly activated JNK, ERK1/2, and p38 signaling and increased intracellular calcium concentrations ([Ca2+]i). Pretreatment of cells with both PD98059 (an ERK1/2 inhibitor) and BAPTA/AM (a cell-permeable Ca2+ chelator), but not SP600125 (a JNK inhibitor) and SB203580 (a p38 inhibitor), effectively suppressed NK-induced mitochondrial dysfunction, ER stress-related signals, and apoptotic events. The elevation of [Ca2+]i in NK-exposed cells could be obviously inhibited by BAPTA/AM, but not PD98059. Taken together, these findings suggest that NK exposure exerts urothelial cytotoxicity via a [Ca2+]i-regulated ERK1/2 activation, which is involved in downstream mediation of the mitochondria-dependent and ER stress-triggered apoptotic pathway, consequently resulting in urothelial cell death. Our findings suggest that regulating [Ca2+]i/ERK signaling pathways may be a promising strategy for treatment of NK-induced urothelial cystitis.

Mixed Solvothermal Synthesis of Tn Cluster-Based Indium and Gallium Sulfides Using Versatile Ammonia or Amine Structure-Directing Agents.

Metal chalcogenide supertetrahedral Tn clusters are of current interest for their unique compositions and structures, which rely highly on the structure-directing agents. Herein, we report four novel Tn cluster-based indium and gallium sulfides, namely, [NH(CH3)3]4In4S10H4 (1), (NH3)4Ga4S6 (2), [NH3CH2CH3]5(NH2CH2CH3)2Ga11S19 (3), and [NH3CH2CH2OH]6Ga10S18·2NH2CH2CH2OH (4). All four compounds were solvothermally synthesized in mixed amine-ethanol solutions or deep eutectic solvent (DES), where ammonia/amine molecules play significant structure-directing roles in the speciation and crystal growth. (1) Being protonated, the trimethylamine and ethanolamine molecules surround the T2-[In4S10H4]4- clusters (for 1) and [Ga10S18]n6n- open framework (for 4), respectively, compensating for the negative charge of the inorganic moieties. (2) With the lone pair of electrons, the ammonia molecules in 2 coordinate directly to corner Ga3+ ions of the {Ga4S6} cage to give a neutral T2-(NH3)4Ga4S6 cluster. (3) For compound 3, part of the ethylamine molecules act as terminating ligands for the T1 and T3 units in the [Ga11S19(NH2CH2CH3)2]n5n- layer, while the rest act as interlamellar countercations upon protonation. Theoretical studies reveal the contributions of N, C, and H to the density of states (DOS) for 2 and 3 because of their hybrid structures that combine the ammonia/amine ligands with sulfide moieties together.

dbAMP: an integrated resource for exploring antimicrobial peptides with functional activities and physicochemical properties on transcriptome and proteome data.

Antimicrobial peptides (AMPs), naturally encoded from genes and generally contained 10-100 amino acids, are crucial components of the innate immune system and can protect the host from various pathogenic bacteria, as well as viruses. In recent years, the widespread use of antibiotics has inspired the rapid growth of antibiotic-resistant microorganisms that usually induce critical infection and pathogenesis. An increasing interest therefore was motivated to explore natural AMPs that enable the development of new antibiotics. With the potential of AMPs being as new drugs for multidrug-resistant pathogens, we were thus motivated to develop a database (dbAMP, http://csb.cse.yzu.edu.tw/dbAMP/) by accumulating comprehensive AMPs from public domain and manually curating literature. Currently in dbAMP there are 12 389 unique entries, including 4271 experimentally verified AMPs and 8118 putative AMPs along with their functional activities, supported by 1924 research articles. The advent of high-throughput biotechnologies, such as mass spectrometry and next-generation sequencing, has led us to further expand dbAMP as a database-assisted platform for providing comprehensively functional and physicochemical analyses for AMPs based on the large-scale transcriptome and proteome data. Significant improvements available in dbAMP include the information of AMP-protein interactions, antimicrobial potency analysis for 'cryptic' region detection, annotations of AMP target species, as well as AMP detection on transcriptome and proteome datasets. Additionally, a Docker container has been developed as a downloadable package for discovering known and novel AMPs on high-throughput omics data. The user-friendly visualization interfaces have been created to facilitate peptide searching, browsing, and sequence alignment against dbAMP entries. All the facilities integrated into dbAMP can promote the functional analyses of AMPs and the discovery of new antimicrobial drugs.

dbPTM in 2019: exploring disease association and cross-talk of post-translational modifications.

The dbPTM (http://dbPTM.mbc.nctu.edu.tw/) has been maintained for over 10 years with the aim to provide functional and structural analyses for post-translational modifications (PTMs). In this update, dbPTM not only integrates more experimentally validated PTMs from available databases and through manual curation of literature but also provides PTM-disease associations based on non-synonymous single nucleotide polymorphisms (nsSNPs). The high-throughput deep sequencing technology has led to a surge in the data generated through analysis of association between SNPs and diseases, both in terms of growth amount and scope. This update thus integrated disease-associated nsSNPs from dbSNP based on genome-wide association studies. The PTM substrate sites located at a specified distance in terms of the amino acids encoded from nsSNPs were deemed to have an association with the involved diseases. In recent years, increasing evidence for crosstalk between PTMs has been reported. Although mass spectrometry-based proteomics has substantially improved our knowledge about substrate site specificity of single PTMs, the fact that the crosstalk of combinatorial PTMs may act in concert with the regulation of protein function and activity is neglected. Because of the relatively limited information about concurrent frequency and functional relevance of PTM crosstalk, in this update, the PTM sites neighboring other PTM sites in a specified window length were subjected to motif discovery and functional enrichment analysis. This update highlights the current challenges in PTM crosstalk investigation and breaks the bottleneck of how proteomics may contribute to understanding PTM codes, revealing the next level of data complexity and proteomic limitation in prospective PTM research.

iDPGK: characterization and identification of lysine phosphoglycerylation sites based on sequence-based features.

BACKGROUND: Protein phosphoglycerylation, the addition of a 1,3-bisphosphoglyceric acid (1,3-BPG) to a lysine residue of a protein and thus to form a 3-phosphoglyceryl-lysine, is a reversible and non-enzymatic post-translational modification (PTM) and plays a regulatory role in glucose metabolism and glycolytic process. As the number of experimentally verified phosphoglycerylated sites has increased significantly, statistical or machine learning methods are imperative for investigating the characteristics of phosphoglycerylation sites. Currently, research into phosphoglycerylation is very limited, and only a few resources are available for the computational identification of phosphoglycerylation sites. RESULT: We present a bioinformatics investigation of phosphoglycerylation sites based on sequence-based features. The TwoSampleLogo analysis reveals that the regions surrounding the phosphoglycerylation sites contain a high relatively of positively charged amino acids, especially in the upstream flanking region. Additionally, the non-polar and aliphatic amino acids are more abundant surrounding phosphoglycerylated lysine following the results of PTM-Logo, which may play a functional role in discriminating between phosphoglycerylation and non-phosphoglycerylation sites. Many types of features were adopted to build the prediction model on the training dataset, including amino acid composition, amino acid pair composition, positional weighted matrix and position-specific scoring matrix. Further, to improve the predictive power, numerous top features ranked by F-score were considered as the final combination for classification, and thus the predictive models were trained using DT, RF and SVM classifiers. Evaluation by five-fold cross-validation showed that the selected features was most effective in discriminating between phosphoglycerylated and non-phosphoglycerylated sites. CONCLUSION: The SVM model trained with the selected sequence-based features performed well, with a sensitivity of 77.5%, a specificity of 73.6%, an accuracy of 74.9%, and a Matthews Correlation Coefficient value of 0.49. Furthermore, the model also consistently provides the effective performance in independent testing set, yielding sensitivity of 75.7% and specificity of 64.9%. Finally, the model has been implemented as a web-based system, namely iDPGK, which is now freely available at http://mer.hc.mmh.org.tw/iDPGK/ .

Genome-wide discovery of viral microRNAs based on phylogenetic analysis and structural evolution of various human papillomavirus subtypes.

In mammals, microRNAs (miRNAs) play key roles in controlling posttranscriptional regulation through binding to the mRNAs of target genes. Recently, it was discovered that viral miRNAs may be involved in human cancers and diseases. It is likely that viral miRNAs help viruses enter the latent phase of their life cycle and become undetected by the host's immune system, while increasing the host's risk for cancer development. Cervical cancer is typically related to the infection of human papillomavirus (HPV) through sexual transmission. To further understand the molecular mechanisms underlying the associations of HPV infection with genital diseases, we developed a systematic method for viral miRNA identification and viral miRNA-mediated regulatory network construction based on genome-wide sequence analysis. The complete genomes of certain high-risk HPV subtypes were used to predict putative viral pre-miRNAs by bioinformatics approaches. In addition, small RNA libraries in human cervical lesions from existing publications were collected to validate the predicted HPV pre-miRNAs. For the construction of virally encoded miRNA-mediated regulatory network of HPV infection, cervical squamous epithelial carcinoma gene expression data were extracted from the RNA sequencing platform in The Cancer Genome Atlas; the differentially expressed genes were used to identify the putative targets of viral miRNAs. Predicted cellular target genes of HPV-encoded miRNAs provide an overview of these viral miRNA's putative functions. Finally, a large-scale genome analysis was carried out to examine the phylogenetic relationship and structural evolution among genital HPV types that have the potential to cause genital cancer. In this study, we discovered putative HPV-encoded miRNAs, which were validated against the small RNA libraries in human cervical lesions. Furthermore, as indicated by their biological functions, host genes targeted by HPV-encoded miRNAs may play significant roles in virus infection and carcinogenesis. These viral miRNAs pose as promising candidates for the development of antiviral drugs. More importantly, the identified subtype-specific miRNAs have the potential to be used as biomarkers for HPV subtype determination.

Efficient Cs+-Sr2+ Separation over a Microporous Silver Selenidostannate Synthesized in Deep Eutectic Solvent.

Efficient Cs+-Sr2+ separation, highly desirable for radionuclide recovery in medical and industrial applications, was achieved by the ion exchange technique over a novel microporous silver selenidostannate, [NH3CH3]0.5[NH2(CH3)2]0.25Ag1.25SnSe3 (AgSnSe-1). This material was synthesized in deep eutectic solvent (DES), where the alkylammonium cations play significant structure-directing roles in the construction of micropores that allow for selective ion exchange toward Cs+ against Sr2+. The much greater KdCs (1.06 × 104 mL g-1) over KdSr (87.7 mL g-1) contributes to an outstanding separation factor SFCs/Sr of ∼121.4 that is top-ranked among inorganic materials. An ion exchange column filled with AgSnSe-1 exhibits a remarkable separation effect for 10 000 bed volumes of continuous flow, with removal rates of ∼99.9% and ∼0 ± 5.5% for Cs+ and Sr2+, respectively. AgSnSe-1 exhibits excellent ß and γ radiation resistances and a chemical stability over a broad pH range of 1-12. The Se leaching level below the safe guideline value for drinking water highlights the environmental-friendly nature of AgSnSe-1. The high Cs+ exchange performance is almost unaffected by Na+, Mg2+, and Ca2+ cations. The Cs+-laden product AgSnSe-1Cs can be facilely eluted for recycling use, highlighting the great potential of open framework metal selenides in nuclear waste treatment and renewable energy utilization.

Removal of Sr2+ Ions by a High-Capacity Indium Sulfide Exchanger Containing Permeable Layers with Large Pores.

An ethylammonium-templated indium sulfide, [CH3CH2NH3]6In8S15 (InS-2), featuring anionic layers perforated with large, 24-membered rings that facilitate the accommodation of hydrated Sr2+ ions is reported. InS-2 exhibits an excellent adsorption performance toward Sr2+ with a top-ranked capacity (qm = 143.29 mg g-1), rapid kinetics, wide pH durability (3-14), ß- and γ-radiation resistances, and a facile elution.

Characterization and identification of lysine glutarylation based on intrinsic interdependence between positions in the substrate sites.

BACKGROUND: Glutarylation, the addition of a glutaryl group (five carbons) to a lysine residue of a protein molecule, is an important post-translational modification and plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified glutarylated peptides increases, it becomes imperative to investigate substrate motifs to enhance the study of protein glutarylation. We carried out a bioinformatics investigation of glutarylation sites based on amino acid composition using a public database containing information on 430 non-homologous glutarylation sites. RESULTS: The TwoSampleLogo analysis indicates that positively charged and polar amino acids surrounding glutarylated sites may be associated with the specificity in substrate site of protein glutarylation. Additionally, the chi-squared test was utilized to explore the intrinsic interdependence between two positions around glutarylation sites. Further, maximal dependence decomposition (MDD), which consists of partitioning a large-scale dataset into subgroups with statistically significant amino acid conservation, was used to capture motif signatures of glutarylation sites. We considered single features, such as amino acid composition (AAC), amino acid pair composition (AAPC), and composition of k-spaced amino acid pairs (CKSAAP), as well as the effectiveness of incorporating MDD-identified substrate motifs into an integrated prediction model. Evaluation by five-fold cross-validation showed that AAC was most effective in discriminating between glutarylation and non-glutarylation sites, according to support vector machine (SVM). CONCLUSIONS: The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/ .

Rapid classification of group B Streptococcus serotypes based on matrix-assisted laser desorption ionization-time of flight mass spectrometry and machine learning techniques.

BACKGROUND: Group B streptococcus (GBS) is an important pathogen that is responsible for invasive infections, including sepsis and meningitis. GBS serotyping is an essential means for the investigation of possible infection outbreaks and can identify possible sources of infection. Although it is possible to determine GBS serotypes by either immuno-serotyping or geno-serotyping, both traditional methods are time-consuming and labor-intensive. In recent years, the matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been reported as an effective tool for the determination of GBS serotypes in a more rapid and accurate manner. Thus, this work aims to investigate GBS serotypes by incorporating machine learning techniques with MALDI-TOF MS to carry out the identification. RESULTS: In this study, a total of 787 GBS isolates, obtained from three research and teaching hospitals, were analyzed by MALDI-TOF MS, and the serotype of the GBS was determined by a geno-serotyping experiment. The peaks of mass-to-charge ratios were regarded as the attributes to characterize the various serotypes of GBS. Machine learning algorithms, such as support vector machine (SVM) and random forest (RF), were then used to construct predictive models for the five different serotypes (Types Ia, Ib, III, V, and VI). After optimization of feature selection and model generation based on training datasets, the accuracies of the selected models attained 54.9-87.1% for various serotypes based on independent testing data. Specifically, for the major serotypes, namely type III and type VI, the accuracies were 73.9 and 70.4%, respectively. CONCLUSION: The proposed models have been adopted to implement a web-based tool (GBSTyper), which is now freely accessible at http://csb.cse.yzu.edu.tw/GBSTyper/, for providing efficient and effective detection of GBS serotypes based on a MALDI-TOF MS spectrum. Overall, this work has demonstrated that the combination of MALDI-TOF MS and machine intelligence could provide a practical means of clinical pathogen testing.