Mining Real-World Big Data to Characterize Adverse Drug Reaction Quantitatively: Mixed Methods Study.

BACKGROUND: Adverse drug reactions (ADRs), which are the phenotypic manifestations of clinical drug toxicity in humans, are a major concern in precision clinical medicine. A comprehensive evaluation of ADRs is helpful for unbiased supervision of marketed drugs and for discovering new drugs with high success rates. OBJECTIVE: In current practice, drug safety evaluation is often oversimplified to the occurrence or nonoccurrence of ADRs. Given the limitations of current qualitative methods, there is an urgent need for a quantitative evaluation model to improve pharmacovigilance and the accurate assessment of drug safety. METHODS: In this study, we developed a mathematical model, namely the Adverse Drug Reaction Classification System (ADReCS) severity-grading model, for the quantitative characterization of ADR severity, a crucial feature for evaluating the impact of ADRs on human health. The model was constructed by mining millions of real-world historical adverse drug event reports. A new parameter called Severity_score was introduced to measure the severity of ADRs, and upper and lower score boundaries were determined for 5 severity grades. RESULTS: The ADReCS severity-grading model exhibited excellent consistency (99.22%) with the expert-grading system, the Common Terminology Criteria for Adverse Events. Hence, we graded the severity of 6277 standard ADRs for 129,407 drug-ADR pairs. Moreover, we calculated the occurrence rates of 6272 distinct ADRs for 127,763 drug-ADR pairs in large patient populations by mining real-world medication prescriptions. With the quantitative features, we demonstrated example applications in systematically elucidating ADR mechanisms and thereby discovered a list of drugs with improper dosages. CONCLUSIONS: In summary, this study represents the first comprehensive determination of both ADR severity grades and ADR frequencies. This endeavor establishes a strong foundation for future artificial intelligence applications in discovering new drugs with high efficacy and low toxicity. It also heralds a paradigm shift in clinical toxicity research, moving from qualitative description to quantitative evaluation.

PhosMap: An ensemble bioinformatic platform to empower interactive analysis of quantitative phosphoproteomics.

BACKGROUND: Liquid chromatography-mass spectrometry (LC-MS)-based quantitative phosphoproteomics has been widely used to detect thousands of protein phosphorylation modifications simultaneously from the biological specimens. However, the complicated procedures for analyzing phosphoproteomics data has become a bottleneck to widening its application. METHODS: Here, we develop PhosMap, a versatile and scalable tool to accomplish phosphoproteomics data analysis. A standardized phosphorylation data format was created for data analyses, from data preprocessing to downstream bioinformatic analyses such as dimension reduction, differential phosphorylation analysis, kinase activity, survival analysis, and so on. For better usability, we distribute PhosMap as a Docker image for easy local deployment upon any of Windows, Linux, and Mac system. RESULTS: The source code is deposited at https://github.com/BADD-XMU/PhosMap. A free PhosMap webserver (https://huggingface.co/spaces/Bio-Add/PhosMap), with easy-to-follow fashion of dashboards, is curated for interactive data analysis. CONCLUSIONS: PhosMap fills the technical gap of large-scale phosphorylation research by empowering researchers to process their own phosphoproteomics data expediently and efficiently, and facilitates better data interpretation.

ROS-induced oxidative stress is a major contributor to sperm cryoinjury.

STUDY QUESTION: What is the mechanism behind cryoinjury in human sperm, particularly concerning the interplay between reactive oxygen species (ROS) and autophagy, and how does it subsequently affect sperm fate? SUMMARY ANSWER: The freeze-thaw operation induces oxidative stress by generating abundant ROS, which impairs sperm motility and activates autophagy, ultimately guiding the sperm toward programmed cell death such as apoptosis and necrosis, as well as triggering premature capacitation. WHAT IS KNOWN ALREADY: Both ROS-induced oxidative stress and autophagy are thought to exert an influence on the quality of frozen-thawed sperm. STUDY DESIGN, SIZE, DURATION: Overall, 84 semen specimens were collected from young healthy fertile males, with careful quality evaluation. The specimens were split into three groups to investigate the ROS-induced cryoinjury: normal control without any treatment, sperm treated with 0.5 mM hydrogen peroxide (H2O2) for 1 h, and sperm thawed following cryopreservation. Samples from 48 individuals underwent computer-assisted human sperm analysis (CASA) to evaluate sperm quality in response to the treatments. Semen samples from three donors were analyzed for changes in the sperm proteome after H2O2 treatment, and another set of samples from three donors were analyzed for changes following the freeze-thaw process. The other 30 samples were used for fluorescence-staining and western blotting. PARTICIPANTS/MATERIALS, SETTING, METHODS: Sperm motility parameters, including progressive motility (PR %) and total motility (PR + NP %), were evaluated using the CASA system on a minimum of 200 spermatozoa. The proteomic profiles were determined with label-free mass spectrometry (MS/MS) and protein identification was performed via ion search against the NCBI human database. Subsequently, comprehensive bioinformatics was applied to detect significant proteomic changes and functional enrichment. Fluorescence-staining and western blot analyses were also conducted to confirm the proteomic changes on selected key proteins. The ROS level was measured using 2',7'-dichlorodihydrofluorescein diacetate labeling and the abundance of bioactive mitochondria was determined by evaluating the inner mitochondrial membrane potential (MMP) level. Molecular behaviors of sequestosome-1 (p62 or SQSTM1) and microtubule-associated proteins 1A/1B light chain 3 (LC3) were monitored to evaluate the state of apoptosis in human sperm. Fluorescent probes oxazole yellow (YO-PRO-1) and propidium iodide (PI) were utilized to monitor programmed cell death, namely apoptosis and necrosis. Additionally, gradient concentrations of antioxidant coenzyme Q10 (CoQ10) were introduced to suppress ROS impacts on sperm. MAIN RESULTS AND THE ROLE OF CHANCE: The CASA analysis revealed a significant decrease in sperm motility for both the H2O2-treatment and freeze-thaw groups. Fluorescence staining showed that high ROS levels were produced in the treated sperm and the MMPs were largely reduced. The introduction of CoQ10 at concentrations of 20 and 30 µM resulted in a significant rescue of progressive motility (P < 0.05). The result suggested that excessive ROS could be the major cause of sperm motility impairment, likely by damaging mitochondrial energy generation. Autophagy was significantly activated in sperm when they were under oxidative stress, as evidenced by the upregulation of p62 and the increased conversion of LC3 as well as the upregulation of several autophagy-related proteins, such as charged multivesicular body protein 2a, mitochondrial import receptor subunit TOM22 homolog, and WD repeat domain phosphoinositide-interacting protein 2. Additionally, fluorescent staining indicated the occurrence of apoptosis and necrosis in both H2O2-treated sperm and post-thaw sperm. The cell death process can be suppressed when CoQ10 is introduced, which consolidates the view that ROS could be the major contributor to sperm cryoinjury. The freeze-thaw process could also initiate sperm premature capacitation, demonstrated by the prominent increase in tyrosine phosphorylated proteins, verified with anti-phosphotyrosine antibody and immunofluorescence assays. The upregulation of capacitation-related proteins, such as hyaluronidase 3 and Folate receptor alpha, supported this finding. LARGE SCALE DATA: The data underlying this article are available in the article and its online supplementary material. LIMITATIONS, REASONS FOR CAUTION: The semen samples were obtained exclusively from young, healthy, and fertile males with progressive motility exceeding 60%, which might overemphasize the positive effects while possibly neglecting the negative impacts of cryoinjury. Additionally, the H2O2 treatment conditions in this study may not precisely mimic the oxidative stress experienced by sperm after thawing from cryopreservation, potentially resulting in the omission of certain molecular alterations. WIDER IMPLICATIONS OF THE FINDINGS: This study provides substantial proteomic data for a comprehensive and deeper understanding of the impact of cryopreservation on sperm quality. It will facilitate the design of optimal protocols for utilizing cryopreserved sperm to improve applications, such as ART, and help resolve various adverse situations caused by chemotherapy, radiotherapy, and surgery. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by grants from the Major Innovation Project of Research Institute of National Health Commission (#2022GJZD01-3) and the National Key R&D Program of China (#2018YFC1003600). All authors declare no competing interests. TRIAL REGISTRATION NUMBER: N/A.

TransIntegrator: capture nearly full protein-coding transcript variants via integrating Illumina and PacBio transcriptomes.

Genes have the ability to produce transcript variants that perform specific cellular functions. However, accurately detecting all transcript variants remains a long-standing challenge, especially when working with poorly annotated genomes or without a known genome. To address this issue, we have developed a new computational method, TransIntegrator, which enables transcriptome-wide detection of novel transcript variants. For this, we determined 10 Illumina sequencing transcriptomes and a PacBio full-length transcriptome for consecutive embryo development stages of amphioxus, a species of great evolutionary importance. Based on the transcriptomes, we employed TransIntegrator to create a comprehensive transcript variant library, namely iTranscriptome. The resulting iTrancriptome contained 91 915 distinct transcript variants, with an average of 2.4 variants per gene. This substantially improved current amphioxus genome annotation by expanding the number of genes from 21 954 to 38 777. Further analysis manifested that the gene expansion was largely ascribed to integration of multiple Illumina datasets instead of involving the PacBio data. Moreover, we demonstrated an example application of TransIntegrator, via generating iTrancriptome, in aiding accurate transcriptome assembly, which significantly outperformed other hybrid methods such as IDP-denovo and Trinity. For user convenience, we have deposited the source codes of TransIntegrator on GitHub as well as a conda package in Anaconda. In summary, this study proposes an affordable but efficient method for reliable transcriptomic research in most species.

An immune cell atlas reveals the dynamics of human macrophage specification during prenatal development.

Macrophages are heterogeneous and play critical roles in development and disease, but their diversity, function, and specification remain inadequately understood during human development. We generated a single-cell RNA sequencing map of the dynamics of human macrophage specification from PCW 4-26 across 19 tissues. We identified a microglia-like population and a proangiogenic population in 15 macrophage subtypes. Microglia-like cells, molecularly and morphologically similar to microglia in the CNS, are present in the fetal epidermis, testicle, and heart. They are the major immune population in the early epidermis, exhibit a polarized distribution along the dorsal-lateral-ventral axis, and interact with neural crest cells, modulating their differentiation along the melanocyte lineage. Through spatial and differentiation trajectory analysis, we also showed that proangiogenic macrophages are perivascular across fetal organs and likely yolk-sac-derived as microglia. Our study provides a comprehensive map of the heterogeneity and developmental dynamics of human macrophages and unravels their diverse functions during development.

Discovering Innate Driver Variants for Risk Assessment of Early Colorectal Cancer Metastasis.

Metastasis is the main fatal cause of colorectal cancer (CRC). Although enormous efforts have been made to date to identify biomarkers associated with metastasis, there is still a huge gap to translate these efforts into effective clinical applications due to the poor consistency of biomarkers in dealing with the genetic heterogeneity of CRCs. In this study, a small cohort of eight CRC patients was recruited, from whom we collected cancer, paracancer, and normal tissues simultaneously and performed whole-exome sequencing. Given the exomes, a novel statistical parameter LIP was introduced to quantitatively measure the local invasion power for every somatic and germline mutation, whereby we affirmed that the innate germline mutations instead of somatic mutations might serve as the major driving force in promoting local invasion. Furthermore, via bioinformatic analyses of big data derived from the public zone, we identified ten potential driver variants that likely urged the local invasion of tumor cells into nearby tissue. Of them, six corresponding genes were new to CRC metastasis. In addition, a metastasis resister variant was also identified. Based on these eleven variants, we constructed a logistic regression model for rapid risk assessment of early metastasis, which was also deployed as an online server, AmetaRisk (http://www.bio-add.org/AmetaRisk). In summary, we made a valuable attempt in this study to exome-wide explore the genetic driving force to local invasion, which provides new insights into the mechanistic understanding of metastasis. Furthermore, the risk assessment model can assist in prioritizing therapeutic regimens in clinics and discovering new drug targets, and thus substantially increase the survival rate of CRC patients.

Construction of integrative transcriptome to boost systematic exploration of Bougainvillea.

Members of the genus Bougainvillea are rich sources of natural dyes, pigments, and traditional medicines. They are also commonly used as ornamentals in roadside landscape construction. However, the horticultural development of Bougainvillea flowers with extended growth periods and coloration is not always feasible. One reason is limited molecular knowledge and no genomic information for Bougainvillea. Here, we compiled an integrative transcriptome of all expressed transcripts for Bougainvillea × buttiana Miss Manila by integrating 20 Illumina-sequencing RNA transcriptomes. The integrative transcriptome consisted of 97,623 distinct transcripts. Of these, 47,006 were protein-coding, 31,109 were non-coding, and 19,508 were unannotated. In addition, we affirmed that the integrative transcriptome could serve as a surrogate reference to the genome in aiding accurate transcriptome assembly. For convenience, we curated the integrative transcriptome database for Bougainvillea, namely InTransBo, which can be freely accessed at http://www.bio-add.org/InTransBo/index.jsp . To the best of our knowledge, the present study is the most comprehensive genomic resource for Bougainvillea up-to-date. The integrative transcriptome helps fill the genomic gap and elucidate the transcriptional nature of Bougainvillea. It may also advance progress in the precise regulation of flowering in horticulture. The same strategy can be readily applied toward the systematic exploration of other plant species lacking complete genomic information.

Segmental duplication as potential biomarkers for non-invasive prenatal testing of aneuploidies.

BACKGROUND: Segmental duplication (SD) regions are distinct targets for aneuploidy detection owing to the virtual elimination of amplification bias. The difficulty of searching SD sequences for assay design has hampered their applications. METHODS: We developed a computational program, ChAPDes, which integrates SD searching, refinement, and design of specific PCR primer/probe sets in a pipeline to remove most of the manual work. The generated primer/probe sets were first tested in a multiplex multicolour melting curve analysis for the detection of five common aneuploidies. The primer/probe sets were then tested in a digital PCR assay for the detection of trisomy 21. Finally, a digital PCR protocol was established to quantify maternal plasma DNA sequences for the non-invasive prenatal detection of fetal trisomy 21. FINDINGS: ChAPDes could output 21,772 candidate primer/probe sets for trisomy 13, 18, 21 and sex chromosome aneuploidies within 2 working days. Clinical evaluation of the multiplex multicolour melting curve analysis involving 463 fetal genomic DNA samples revealed a sensitivity of 100% and specificity of 99.64% in comparison with the reference methods. Using the established digital PCR protocol, we correctly identified two trisomy 21 fetuses and thirteen euploid foetuses from the maternal plasma samples. INTERPRETATION: The combination of ChAPDes with digital PCR detection could facilitate the use of SD as potential biomarkers for the non-invasive prenatal testing of fetal chromosomal aneuploidies. FUNDING: None.

Gene network analyses unveil possible molecular basis underlying drug-induced glaucoma.

BACKGROUND: Drug-induced glaucoma (DIG) is a kind of serious adverse drug reaction that can cause irreversible blindness. Up-to-date, the molecular mechanism of DIG largely remains unclear yet due to the medical complexity of glaucoma onset. METHODS: In this study, we conducted data mining of tremendous historical adverse drug events and genome-wide drug-regulated gene signatures to identify glaucoma-associated drugs. Upon these drugs, we carried out serial network analyses, including the weighted gene co-expression network analysis (WGCNA), to illustrate the gene interaction network underlying DIG. Furthermore, we applied pathogenic risk assessment to discover potential biomarker genes for DIG. RESULTS: As the results, we discovered 13 highly glaucoma-associated drugs, a glaucoma-related gene network, and 55 glaucoma-susceptible genes. These genes likely played central roles in triggering DIGs via an integrative mechanism of phototransduction dysfunction, intracellular calcium homeostasis disruption, and retinal ganglion cell death. Further pathogenic risk analysis manifested that a panel of nine genes, particularly OTOF gene, could serve as potential biomarkers for early-onset DIG prognosis. CONCLUSIONS: This study elucidates the possible molecular basis underlying DIGs systematically for the first time. It also provides prognosis clues for early-onset glaucoma and thus assists in designing better therapeutic regimens.

PTP-MEG2 regulates quantal size and fusion pore opening through two distinct structural bases and substrates.

Tyrosine phosphorylation of secretion machinery proteins is a crucial regulatory mechanism for exocytosis. However, the participation of protein tyrosine phosphatases (PTPs) in different exocytosis stages has not been defined. Here we demonstrate that PTP-MEG2 controls multiple steps of catecholamine secretion. Biochemical and crystallographic analyses reveal key residues that govern the interaction between PTP-MEG2 and its substrate, a peptide containing the phosphorylated NSF-pY83 site, specify PTP-MEG2 substrate selectivity, and modulate the fusion of catecholamine-containing vesicles. Unexpectedly, delineation of PTP-MEG2 mutants along with the NSF binding interface reveals that PTP-MEG2 controls the fusion pore opening through NSF independent mechanisms. Utilizing bioinformatics search and biochemical and electrochemical screening approaches, we uncover that PTP-MEG2 regulates the opening and extension of the fusion pore by dephosphorylating the DYNAMIN2-pY125 and MUNC18-1-pY145 sites. Further structural and biochemical analyses confirmed the interaction of PTP-MEG2 with MUNC18-1-pY145 or DYNAMIN2-pY125 through a distinct structural basis compared with that of the NSF-pY83 site. Our studies thus provide mechanistic insights in complex exocytosis processes.

Exploring the mechanism of PingTang No.5 capsule on nonalcoholic fatty liver disease through network pharmacology and experimental validation.

PingTang No.5 capsule (PT5), a modified Traditional Chinese Medicine (TCM) formula of Zexie Decoction, is used to treat patients with lipid metabolism disorders in our hospital. The present study was designed to investigate the mechanisms of PT5 in treating non-alcoholic fatty liver disease (NAFLD). PT5 information including ingredients, pharmacological properties, and potential targets was obtained from TCM databases. The candidate targets of PT5 were predicted by network pharmacological analysis, and the possible pathway and mechanism were obtained from DAVID database, followed by experimental validation in NAFLD mice model treated with PT5. Total 328 compounds were selected using the threshold oral bioactivity (OB) > 30% or drug-likeness (DL) > 0.1 of pharmacology characteristic, and 1033 candidate targets obtained to construct the network analysis. The 113 targets were selected from the intersection between candidate targets of PT5 and NAFLD relative gene. These targets were evaluated in diabetic complications, cancer, Hepatitis B, Fluid shear stress and atherosclerosis, and TNF signaling pathway. TNF-α was the important factor in protein interaction analysis of STRING and involved in the lipid regulation and oxidative stress in NAFLD. When administrated to the NAFLD mice, PT5 reduced weight, blood fatty acids, decreased the adipocyte size, and improved the metabolism. Besides, the molecular verification of lipid metabolism increased and oxidative stress reduced that interpreted the mechanism of PT5 preventing liver cell from lipid accumulation and injury of NAFLD. These results presented PT5 have the potential therapy as an alternative treatment for NAFLD.

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,156 distinct ADRs. We also designed a parameter ToxicityScore to quantify the overall drug safety. Moreover, we determined association strength for every 3,807,631 gene-ADR interactions, which clues mechanistic exploration of ADRs. For convenience, we deployed the model as a web service ADRAlert-gene at http://www.bio-add.org/ADRAlert/. In summary, this study offers insights into prioritizing safe drug therapy. It helps reduce the attrition rate of new drug discovery by providing a reliable ADR profile in the early preclinical stage.

Large-Scale Target Identification of Herbal Medicine Using a Reverse Docking Approach.

Herbal medicine has been used to countermine various diseases for centuries. However, most of the therapeutic targets underlying herbal therapy remain unclear, which largely slow down the novel drug discovery process from natural products. In this study, we developed a novel computational pipeline for assisting de novo identification of protein targets for herbal ingredients. The pipeline involves pharmacophore comparison and reverse ligand-protein docking simulation in a high throughput manner. We evaluated the pipeline using three traditional Chinese medicine ingredients such as acteoside, quercetin, and epigallocatechin gallate as examples. A majority of current known targets of these ingredients were successfully identified by the pipeline. Structural comparative analyses confirmed that the predicted ligand-target interactions used the same binding pockets and binding modes as those of known ligand-target interactions. Furthermore, we illustrated the mechanism of actions of the ingredients by constructing the pharmacological networks on the basis of the predicted target profiles. In summary, we proposed an efficient and economic option for large-scale target exploration in the herb study. This pipeline will be particularly valuable in aiding precise drug discovery and drug repurposing from natural products.

Biophysical characterization and ligand-binding properties of the elongation factor Tu from Mycobacterium tuberculosis.

Mycobacterium tuberculosis (Mtb) is the key devastating bacterial pathogen responsible for tuberculosis. Increasing emergence of multi-drug-resistant, extensively drug-resistant, and rifampicin/isoniazid-resistant strains of Mtb makes the discovery of validated drug targets an urgent priority. As a vital translational component of the protein biosynthesis system, elongation factor Tu (EF-Tu) is an important molecular switch responsible for selection and binding of the cognate aminoacyl-tRNA to the acceptor site on the ribosome. In addition, EF-Tu from Mtb (MtbEF-Tu) is involved in the initial step of trans-translation which is an effective system for rescuing the stalled ribosomes from non-stop translation complexes under stress conditions. Given its crucial role in protein biosynthesis, EF-Tu is identified as an excellent molecular target for drug design. Here, we reported the recombinant expression, purification, biophysical characterization, and structural modeling of the MtbEF-Tu protein. Our results demonstrated that prokaryotic expression plasmids of pET28a-MtbEF-Tu could be expressed efficiently in Escherichia coli. We successfully purified the 6× His-tagged proteins with a yield of 16.8 mg from 1 l of Luria Bertani medium. Dynamic light scattering experiments showed that MtbEF-Tu existed in a monomeric form, and circular dichroism experiments indicated that MtbEF-Tu was well structured. Moreover, isothermal titration calorimetry experiments displayed that the purified MtbEF-Tu protein possessed intermediate binding affinities for guanosine-5'-triphosphate (GTP) and GDP. The GTP/GDP-binding sites were predicted by flexible molecular docking approach which reveals that GTP/GDP binds to MtbEF-Tu mainly through hydrogen bonds. Our work lays the essential basis for further structural and functional studies of MtbEF-Tu as well as MtbEF-Tu-related novel drug developments.

ADReCS-Target: target profiles for aiding drug safety research and application.

Delivering safe and effective therapeutic treatment to patients is one of the grand challenges in modern medicine. However, drug safety research has been progressing slowly in recent years, compared to other fields such as biotechnologies and precision medicine, due to the mechanistic complexity of adverse drug reactions (ADRs). To fill up this gap, we develop a new database, the Adverse Drug Reaction Classification System-Target Profile (ADReCS-Target, http://bioinf.xmu.edu.cn/ADReCS-Target), which provides comprehensive information about ADRs caused by drug interaction with protein, gene and genetic variation. In total, ADReCS-Target includes 66,573 pairwise relations, among which 1710 are protein-ADR associations, 2613 are genetic variation-ADR associations, and 63,298 are gene-ADR associations. In a case study of exploring the mechanism of rash, we find that HLAs, C1QA and APOA1 are the key gene players and thus can be potential targets (or biomarkers) in monitoring or countermining rashes. In summary, ADReCS-Target can be a useful resource for the biomedical scientific community by serving researchers in the fields of drug development, clinical pharmacology, precision medicine, and from web lab to high-throughput computational platform. Particularly, it helps to identify drug with better ADR profile and design safer drug therapy regimen.

Evolutionary relationships between seryl-histidine dipeptide and modern serine proteases from the analysis based on mass spectrometry and bioinformatics.

Seryl-histidine dipeptide (Ser-His) has been recognized as the shortest peptide with hydrolysis cleavage activity; however, its protein cleavage spectrum has not yet been fully explored. Here, four differently folded proteins were treated with Ser-His, and the digestion products were evaluated with high-resolution mass spectrometry. The cleavage efficiency and cleavage propensity of Ser-His against these protein substrates were calculated at both the primary and secondary sequence levels. The above experiments show that Ser-His cleaves a broad spectrum of substrate proteins of varying secondary structures. Moreover, Ser-His could cleave at all 20 amino acids with different efficiencies according to the protein, which means that Ser-His has the original digestion function of serine proteases. Furthermore, we collected and compared the catalytic sites and cleavage sites of 340 extant serine proteases derived from 17 representative organisms. A consensus motif Ser-[X]-His was identified as the major pattern at the catalytic sites of serine proteases from all of the organisms represented except Danio rerio, which uses Ser-Lys instead. This finding indicates that Ser-His is the core component of the serine protease catalytic site. Moreover, our analysis revealed that the cleavage sites of modern serine proteases have become more specific over the evolutionary history of this family. Based on the above analysis results, it could be found that Ser-His is likely the original serine protease and maybe the evolutionary core of modern serine proteases.

Whole genome sequence of the Treponema pallidum subsp. pallidum strain Amoy: An Asian isolate highly similar to SS14.

Treponema pallidum ssp. pallidum (T. pallidum), the causative agent of the sexually transmitted disease syphilis, is an uncultivatable human pathogen. The geographical differences in T. pallidum genomes leading to differences in pathogenicity are not yet understood. Presently, twelve T. pallidum genomes are available to the public, all of which are American in origin and often co-infect patients with human immunodeficiency virus (HIV). In this study, we examined the T. pallidum subsp. pallidum strain Amoy, a syphilis pathogen found in Xiamen, China. We sequenced its genome using Illumina next-generation sequencing technology and obtained a nearly (98.83%) complete genome of approximately 1.12 Mbps. The new genome shows good synteny with its five T. pallidum sibling strains (Nichols, SS14, Mexico A, DAL-1, and Chicago), among which SS14 is the strain closest to the Amoy strain. Compared with strain SS14, the Amoy strain possesses four uncharacterized strain-specific genes and is likely missing six genes, including a gene encoding the TPR domain protein, which may partially account for the comparatively low virulence and toxicity of the Amoy strain in animal infection. Notably, we did not detect the 23S rRNA A2058G/A2059G mutation in the Amoy strain, which likely explains the sensitivity of Amoy strain to macrolides. The results of this study will lead to a better understanding of the pathogenesis of syphilis and the geographical distribution of T. pallidum genotypes.

BET Bromodomain Inhibition as a Therapeutic Strategy in Ovarian Cancer by Downregulating FoxM1.

Ovarian cancer is responsible for the highest mortality among all gynecologic malignancies, and novel therapies are urgently needed to improve patient outcome. Here we performed an integrative genomic analysis and identified the bromodomain and extraterminal domain (BET) protein BRD4 as a potential therapeutic target in ovarian cancer. Suppression of BRD4 using small-molecule BET inhibitors JQ1 and I-BET151, or dual kinase-bromodomain inhibitor volasertib, led to robust and broad antitumor effects across all subclasses of ovarian cancer. In contrast to many other cancers which are susceptible to BET inhibition due to downregulation of super-enhancer-dependent MYC transcript, we discovered that JQ1-sensitive ovarian cancer cells exhibited marked disruption of Forkhead box protein M1 (FoxM1) pathway, a key driver of ovarian carcinoma. These in vitro findings were further supported by in vivo efficacies of JQ1 targeting both cell line-based and patient-derived xenograft models. Our data establish a new treatment strategy against ovarian cancer by employing epigenetic vulnerabilities, and provide a mechanistic rationale for the clinical investigation of BET bromodomain inhibitors in this deadly disease.

Rapid Assessment of Adverse Drug Reactions by Statistical Solution of Gene Association Network.

Adverse drug reaction (ADR) is a common clinical problem, sometimes accompanying with high risk of mortality and morbidity. It is also one of the major factors that lead to failure in new drug development. Unfortunately, most of current experimental and computational methods are unable to evaluate clinical safety of drug candidates in early drug discovery stage due to the very limited knowledge of molecular mechanisms underlying ADRs. Therefore, in this study, we proposed a novel na€ive Bayesian model for rapid assessment of clinical ADRs with frequency estimation. This model was constructed on a gene-ADR association network, which covered 611 US FDA approved drugs, 14,251 genes, and 1,254 distinct ADR terms. An average detection rate of 99.86 and 99.73 percent were achieved eventually in identification of known ADRs in internal test data set and external case analyses respectively. Moreover, a comparative analysis between the estimated frequencies of ADRs and their observed frequencies was undertaken. It is observed that these two frequencies have the similar distribution trend. These results suggest that the naive Bayesian model based on gene-ADR association network can serve as an efficient and economic tool in rapid ADRs assessment.

ADReCS: an ontology database for aiding standardization and hierarchical classification of adverse drug reaction terms.

Adverse drug reactions (ADRs) are noxious and unexpected effects during normal drug therapy. They have caused significant clinical burden and been responsible for a large portion of new drug development failure. Molecular understanding and in silico evaluation of drug (or candidate) safety in laboratory is thus so desired, and unfortunately has been largely hindered by misuse of ADR terms. The growing impact of bioinformatics and systems biology in toxicological research also requires a specialized ADR term system that works beyond a simple glossary. Adverse Drug Reaction Classification System (ADReCS; http://bioinf.xmu.edu.cn/ADReCS) is a comprehensive ADR ontology database that provides not only ADR standardization but also hierarchical classification of ADR terms. The ADR terms were pre-assigned with unique digital IDs and at the same time were well organized into a four-level ADR hierarchy tree for building an ADR-ADR relation. Currently, the database covers 6544 standard ADR terms and 34,796 synonyms. It also incorporates information of 1355 single active ingredient drugs and 134,022 drug-ADR pairs. In summary, ADReCS offers an opportunity for direct computation on ADR terms and also provides clues to mining common features underlying ADRs.