Shiping Yang

Bio: Shiping Yang is an academic researcher from University of Minnesota. The author has contributed to research in topics: Xylanase & Arabidopsis. The author has an hindex of 15, co-authored 29 publications receiving 701 citations. Previous affiliations of Shiping Yang include China Agricultural University.

Prediction of human-virus protein-protein interactions through a sequence embedding-based machine learning method.

Abstract: The identification of human-virus protein-protein interactions (PPIs) is an essential and challenging research topic, potentially providing a mechanistic understanding of viral infection. Given that the experimental determination of human-virus PPIs is time-consuming and labor-intensive, computational methods are playing an important role in providing testable hypotheses, complementing the determination of large-scale interactome between species. In this work, we applied an unsupervised sequence embedding technique (doc2vec) to represent protein sequences as rich feature vectors of low dimensionality. Training a Random Forest (RF) classifier through a training dataset that covers known PPIs between human and all viruses, we obtained excellent predictive accuracy outperforming various combinations of machine learning algorithms and commonly-used sequence encoding schemes. Rigorous comparison with three existing human-virus PPI prediction methods, our proposed computational framework further provided very competitive and promising performance, suggesting that the doc2vec encoding scheme effectively captures context information of protein sequences, pertaining to corresponding protein-protein interactions. Our approach is freely accessible through our web server as part of our host-pathogen PPI prediction platform (http://zzdlab.com/InterSPPI/). Taken together, we hope the current work not only contributes a useful predictor to accelerate the exploration of human-virus PPIs, but also provides some meaningful insights into human-virus relationships.

SuccinSite: a computational tool for the prediction of protein succinylation sites by exploiting the amino acid patterns and properties

Abstract: Lysine succinylation is an emerging protein post-translational modification, which plays an important role in regulating the cellular processes in both eukaryotic and prokaryotic cells. However, the succinylation modification site is particularly difficult to detect because the experimental technologies used are often time-consuming and costly. Thus, an accurate computational method for predicting succinylation sites may help researchers towards designing their experiments and to understand the molecular mechanism of succinylation. In this study, a novel computational tool termed SuccinSite has been developed to predict protein succinylation sites by incorporating three sequence encodings, i.e., k-spaced amino acid pairs, binary and amino acid index properties. Then, the random forest classifier was trained with these encodings to build the predictor. The SuccinSite predictor achieves an AUC score of 0.802 in the 5-fold cross-validation set and performs significantly better than existing predictors on a comprehensive independent test set. Furthermore, informative features and predominant rules (i.e. feature combinations) were extracted from the trained random forest model for an improved interpretation of the predictor. Finally, we also compiled a database covering 4411 experimentally verified succinylation proteins with 12 456 lysine succinylation sites. Taken together, these results suggest that SuccinSite would be a helpful computational resource for succinylation sites prediction. The web-server, datasets, source code and database are freely available at http://systbio.cau.edu.cn/SuccinSite/.

Mapping regulatory variants controlling gene expression in drought response and tolerance in maize.

Abstract: Gene expression is a key determinant of cellular response. Natural variation in gene expression bridges genetic variation to phenotypic alteration. Identification of the regulatory variants controlling the gene expression in response to drought, a major environmental threat of crop production worldwide, is of great value for drought-tolerant gene identification. A total of 627 RNA-seq analyses are performed for 224 maize accessions which represent a wide genetic diversity under three water regimes; 73,573 eQTLs are detected for about 30,000 expressing genes with high-density genome-wide single nucleotide polymorphisms, reflecting a comprehensive and dynamic genetic architecture of gene expression in response to drought. The regulatory variants controlling the gene expression constitutively or drought-dynamically are unraveled. Focusing on dynamic regulatory variants resolved to genes encoding transcription factors, a drought-responsive network reflecting a hierarchy of transcription factors and their target genes is built. Moreover, 97 genes are prioritized to associate with drought tolerance due to their expression variations through the Mendelian randomization analysis. One of the candidate genes, Abscisic acid 8′-hydroxylase, is verified to play a negative role in plant drought tolerance. This study unravels the effects of genetic variants on gene expression dynamics in drought response which allows us to better understand the role of distal and proximal genetic effects on gene expression and phenotypic plasticity. The prioritized drought-associated genes may serve as direct targets for functional investigation or allelic mining.

Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2

Abstract: Human coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV) and 2019 novel coronavirus (2019-nCoV, also known as SARS-CoV-2), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV/SARS-CoV-2. Drug repurposing, representing as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV–host interactome and drug targets in the human protein–protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV/SARS-CoV-2 shares the highest nucleotide sequence identity with SARS-CoV (79.7%). Specifically, the envelope and nucleocapsid proteins of 2019-nCoV/SARS-CoV-2 are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and HCoV–host interactions in the human interactome, we prioritize 16 potential anti-HCoV repurposable drugs (e.g., melatonin, mercaptopurine, and sirolimus) that are further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. We further identify three potential drug combinations (e.g., sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the “Complementary Exposure” pattern: the targets of the drugs both hit the HCoV–host subnetwork, but target separate neighborhoods in the human interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations targeting 2019-nCoV/SARS-CoV-2.

Identification of Host Proteins Required for HIV Infection Through a Functional Genomic Screen

Abstract: Brass AL, Dykxhoorn DM, Benita Y, et al. Science . 2008;319(5865):921–926 PURPOSE OF THE STUDY. The HIV genome encodes only 15 proteins and, therefore, must use multiple host-cell collaborators for successful replication and transmission. Required host-derived proteins include CD4 as the primary virus receptor and chemokine receptors as coreceptors. This study identified multiple other host proteins required for HIV activity. METHODS. Human cells known to be susceptible to HIV were exposed in vitro to HIV. Using small interfering RNAs able to inhibit each known gene in the human genome 1 at a time, the investigators tested whether HIV could establish an infection and copy itself. HIV dependence on >21 000 human genes was examined. RESULTS. More than 250 human genes were identified to be required for efficient HIV replication. Termed “HIV-dependency factors,” the products of these genes are known to participate in a broad array of cellular functions and implicate unsuspected pathways in the virus life cycle. CONCLUSIONS. The extraordinary dependence of HIV on human host proteins for efficient transmission and replication provides many new potential targets for antiretroviral therapy. REVIEWER COMMENTS. An example of targeting host proteins is the use of chemokine receptor 5 (CCR5) inhibitors. Many people with CCR5 deficiency are very resistant to HIV infection yet have limited if any clinical consequences. Maraviroc CCR5 inhibitor is approved for treatment for HIV infection. This study identified many more such potential targets.

Identification of a Functional Transposon Insertion in the Maize Domestication Gene tb1

Abstract: Genetic diversity created by transposable elements is an important source of functional variation upon which selection acts during evolution. Transposable elements are associated with adaptation to temperate climates in Drosophila, a SINE element is associated with the domestication of small dog breeds from the gray wolf and there is evidence that transposable elements were targets of selection during human evolution. Although the list of examples of transposable elements associated with host gene function continues to grow, proof that transposable elements are causative and not just correlated with functional variation is limited. Here we show that a transposable element (Hopscotch) inserted in a regulatory region of the maize domestication gene, teosinte branched1 (tb1), acts as an enhancer of gene expression and partially explains the increased apical dominance in maize compared to its progenitor, teosinte. Molecular dating indicates that the Hopscotch insertion predates maize domestication by at least 10,000 years, indicating that selection acted on standing variation rather than new mutation.

Cold and Hot Extremozymes: Industrial Relevance and Current Trends

Abstract: The development of enzymes for industrial applications relies heavily on the use of microorganisms. The intrinsic properties of microbial enzymes, e.g., consistency, reproducibility, and high yields along with many others, have pushed their introduction into a wide range of products and industrial processes. Extremophilic microorganisms represent an underutilized and innovative source of novel enzymes. These microorganisms have developed unique mechanisms and molecular means to cope with extreme temperatures, acidic and basic pH, high salinity, high radiation, low water activity, and high metal concentrations among other environmental conditions. Extremophile-derived enzymes, or extremozymes, are able to catalyze chemical reactions under harsh conditions, like those found in industrial processes, which were previously not thought to be conducive for enzymatic activity. Due to their optimal activity and stability under extreme conditions, extremozymes offer new catalytic alternatives for current industrial applications. These extremozymes also represent the cornerstone for the development of environmentally friendly, efficient, and sustainable industrial technologies. Many advances in industrial biocatalysis have been achieved in recent years; however, the potential of biocatalysis through the use of extremozymes is far from being fully realized. In this article, the adaptations and significance of psychrophilic, thermophilic, and hyperthermophilic enzymes, and their applications in selected industrial markets will be reviewed. Also, the current challenges in the development and mass production of extremozymes as well as future prospects and trends for their biotechnological application will be discussed.