Gene ontology based transfer learning for protein subcellular localization

<p>Abstract</p> <p>Background</p> <p>Prediction of protein subcellular localization generally involves many complex factors, and using only one or two aspects of data information may not tell the true story. For this reason, some recent predictive models are deliberately designed to integrate multiple heterogeneous data sources for exploiting multi-aspect protein feature information. Gene ontology, hereinafter referred to as <it>GO</it>, uses a controlled vocabulary to depict biological molecules or gene products in terms of biological process, molecular function and cellular component. With the rapid expansion of annotated protein sequences, gene ontology has become a general protein feature that can be used to construct predictive models in computational biology. Existing models generally either concatenated the <it>GO </it>terms into a flat binary vector or applied majority-vote based ensemble learning for protein subcellular localization, both of which can not estimate the individual discriminative abilities of the three aspects of gene ontology.</p> <p>Results</p> <p>In this paper, we propose a Gene Ontology Based Transfer Learning Model (<it>GO-TLM</it>) for large-scale protein subcellular localization. The model transfers the signature-based homologous <it>GO </it>terms to the target proteins, and further constructs a reliable learning system to reduce the adverse affect of the potential false <it>GO </it>terms that are resulted from evolutionary divergence. We derive three <it>GO </it>kernels from the three aspects of gene ontology to measure the <it>GO </it>similarity of two proteins, and derive two other spectrum kernels to measure the similarity of two protein sequences. We use simple non-parametric cross validation to explicitly weigh the discriminative abilities of the five kernels, such that the time & space computational complexities are greatly reduced when compared to the complicated semi-definite programming and semi-indefinite linear programming. The five kernels are then linearly merged into one single kernel for protein subcellular localization. We evaluate <it>GO-TLM </it>performance against three baseline models: <it>MultiLoc, MultiLoc-GO </it>and <it>Euk-mPLoc </it>on the benchmark datasets the baseline models adopted. 5-fold cross validation experiments show that <it>GO-TLM </it>achieves substantial accuracy improvement against the baseline models: 80.38% against model <it>Euk-mPLoc </it>67.40% with <it>12.98% </it>substantial increase; 96.65% and 96.27% against model <it>MultiLoc-GO </it>89.60% and 89.60%, with <it>7.05% </it>and <it>6.67% </it>accuracy increase on dataset <it>MultiLoc plant </it>and dataset <it>MultiLoc animal</it>, respectively; 97.14%, 95.90% and 96.85% against model <it>MultiLoc-GO </it>83.70%, 90.10% and 85.70%, with accuracy increase <it>13.44%</it>, <it>5.8% </it>and <it>11.15% </it>on dataset <it>BaCelLoc plant</it>, dataset <it>BaCelLoc fungi </it>and dataset <it>BaCelLoc animal </it>respectively. For <it>BaCelLoc </it>independent sets, <it>GO-TLM </it>achieves 81.25%, 80.45% and 79.46% on dataset <it>BaCelLoc plant holdout</it>, dataset <it>BaCelLoc plant holdout </it>and dataset <it>BaCelLoc animal holdout</it>, respectively, as compared against baseline model <it>MultiLoc-GO </it>76%, 60.00% and 73.00%, with accuracy increase <it>5.25%</it>, <it>20.45% </it>and <it>6.46%</it>, respectively.</p> <p>Conclusions</p> <p>Since direct homology-based <it>GO </it>term transfer may be prone to introducing noise and outliers to the target protein, we design an explicitly weighted kernel learning system (called Gene Ontology Based Transfer Learning Model, <it>GO-TLM</it>) to transfer to the target protein the known knowledge about related homologous proteins, which can reduce the risk of outliers and share knowledge between homologous proteins, and thus achieve better predictive performance for protein subcellular localization. Cross validation and independent test experimental results show that the homology-based <it>GO </it>term transfer and explicitly weighing the <it>GO </it>kernels substantially improve the prediction performance.</p

Update on the Risk of Hepatocellular Carcinoma in Chronic Hepatitis B Virus Infection

Chronic hepatitis B virus infection is an important cause of liver-related morbidity and mortality, with hepatocellular carcinoma being the most life-threatening complication. Because of the highly variable clinical course of the disease, enormous research efforts have been made with the aim of revealing the factors in the natural history that are relevant to hepatocarcinogenesis. These include epidemiological studies of predisposing risk groups, viral studies of mutations within the hepatitis B viral genome, and clinical correlation of these risk factors in predicting the likelihood of development of hepatocellular cancer in susceptible hosts. This update addresses these risks, with emphasis on the latest research relevant to hepatocarcinogenesis

Identification of a Phytase Gene in Barley (Hordeum vulgare L.)

Background: Endogenous phytase plays a crucial role in phytate degradation and is thus closely related to nutrient efficiency in barley products. The understanding of genetic information of phytase in barley can provide a useful tool for breeding new barley varieties with high phytase activity. Methodology/Principal Findings: Quantitative trait loci (QTL) analysis for phytase activity was conducted using a doubled haploid population. Phytase protein was purified and identified by the LC-ESI MS/MS Shotgun method. Purple acid phosphatase (PAP) gene was sequenced and the position was compared with the QTL controlling phytase activity. A major QTL for phytase activity was mapped to chromosome 5 H in barley. The gene controlling phytase activity in the region was named as mqPhy. The gene HvPAP a was mapped to the same position as mqPhy, supporting the colinearity between HvPAP a and mqPhy. Conclusions/Significance: It is the first report on QTLs for phytase activity and the results showed that HvPAP a, which shares a same position with the QTL, is a major phytase gene in barley grains

TSPY is a cancer testis antigen expressed in human hepatocellular carcinoma

In search for genes associated with hepatocellular carcinoma (HCC) by cDNA microarray, we found that the transcription of TSPY, ‘testis-specific protein Y-encoded', was upregulated in HCC. Investigation of a broad spectrum of normal and malignant tissues by RT–PCR revealed the TSPY transcript selectively expressed in normal testis, different histological types of human neoplastic tissues, and tumour cell lines. The expression of TSPY in cancer cells was further confirmed by in situ hybridisation. Indirect immunofluorescence microscopy analysis showed that TSPY was localised mainly in the cytoplasm of transiently transfected cells. Testis-specific protein Y-encoded was detected in 50% (16 of 32) of well- and moderately differentiated HCC patients, in 16% (four of 25) of poorly differentiated HCC patients, and in 5% (one of 19) of renal cell cancer patients. A serological survey revealed that 6.6% (seven of 106) HCC patients had anti-TSPY antibody response, demonstrating the immunogenicity of TSPY in humans. In conclusion, these data suggest that TSPY is a novel cancer/testis (CT) antigen and may be a potential candidate in vaccine strategy for immunotherapy in HCC patients

Tumour antigen expression in hepatocellular carcinoma in a low-endemic western area

Background: Identification of tumour antigens is crucial for the development of vaccination strategies against hepatocellular carcinoma (HCC). Most studies come from eastern-Asia, where hepatitis-B is the main cause of HCC. However, tumour antigen expression is poorly studied in low-endemic, western areas where the aetiology of HCC differs. Methods: We constructed tissue microarrays from resected HCC tissue of 133 patients. Expression of a comprehensive panel of cancer-testis (MAGE-A1, MAGE-A3/4, MAGE-A10, MAGE-C1, MAGE-C2, NY-ESO-1, SSX-2, sperm protein 17), onco-fetal (AFP, Glypican-3) and overexpressed tumour antigens (Annexin-A2, Wilms tumor-1, Survivin, Midkine, MUC-1) was determined by immunohistochemistry. Results: A higher prevalence of MAGE antigens was observed in patients with hepatitis-B. Patients with expression of more tumour antigens in general had better HCC-specific survival (P=0.022). The four tumour antigens with high expression in HCC and no, or weak, expression in surrounding tumour-free-liver tissue, were Annexin-A2, GPC-3, MAGE-C1 and MAGE-C2, expressed in 90, 39, 17 and 20% of HCCs, respectively. Ninety-five percent of HCCs expressed at least one of these four tumour antigens. Interestingly, GPC-3 was associated with SALL-4 expression (P=0.001), an oncofetal transcription factor highly expressed in embryonal stem cells. SALL-4 and GPC-3 expression levels were correlated with vascular invasion, poor differentiation and higher AFP levels before surgery. Moreover, patients who co-expressed higher levels of both GPC-3 and SALL-4 had worse HCC-specific survival (P=0.018). Conclusions: We describe a panel of four tumour antigens with excellent coverage and good tumour specificity in a western area, low-endemic for hepatitis-B. The association between GPC-3 and SALL-4 is a novel finding and suggests that GPC-3 targeting may specifically attack the tumour stem-cell compartment

Transient receptor potential canonical 4 and 5 proteins as targets in cancer therapeutics

Novel approaches towards cancer therapy are urgently needed. One approach might be to target ion channels mediating Ca²+ entry because of the critical roles played by Ca²+ in many cell types, including cancer cells. There are several types of these ion channels, but here we address those formed by assembly of transient receptor potential canonical (TRPC) proteins, particularly those which involve two closely related members of the family: TRPC4 and TRPC5. We focus on these proteins because recent studies point to roles in important aspects of cancer: drug resistance, transmission of drug resistance through extracellular vesicles, tumour vascularisation, and evoked cancer cell death by the TRPC4/5 channel activator (−)-englerin A. We conclude that further research is both justified and necessary before these proteins can be considered as strong targets for anti-cancer cell drug discovery programmes. It is nevertheless already apparent that inhibitors of the channels would be unlikely to cause significant adverse effects, but, rather, have other effects which may be beneficial in the context of cancer and chemotherapy, potentially including suppression of innate fear, visceral pain and pathological cardiac remodelling

In vitro generation of cytotoxic and regulatory T cells by fusions of human dendritic cells and hepatocellular carcinoma cells

<p>Abstract</p> <p>Background</p> <p>Human hepatocellular carcinoma (HCC) cells express WT1 and/or carcinoembryonic antigen (CEA) as potential targets for the induction of antitumor immunity. In this study, generation of cytotoxic T lymphocytes (CTL) and regulatory T cells (Treg) by fusions of dendritic cells (DCs) and HCC cells was examined.</p> <p>Methods</p> <p>HCC cells were fused to DCs either from healthy donors or the HCC patient and investigated whether supernatants derived from the HCC cell culture (HCCsp) influenced on the function of DCs/HCC fusion cells (FCs) and generation of CTL and Treg.</p> <p>Results</p> <p>FCs coexpressed the HCC cells-derived WT1 and CEA antigens and DCs-derived MHC class II and costimulatory molecules. In addition, FCs were effective in activating CD4⁺and CD8⁺T cells able to produce IFN-γ and inducing cytolysis of autologous tumor or semiallogeneic targets by a MHC class I-restricted mechanism. However, HCCsp induced functional impairment of DCs as demonstrated by the down-regulation of MHC class I and II, CD80, CD86, and CD83 molecules. Moreover, the HCCsp-exposed DCs failed to undergo full maturation upon stimulation with the Toll-like receptor 4 agonist penicillin-inactivated <it>Streptococcus pyogenes</it>. Interestingly, fusions of immature DCs generated in the presence of HCCsp and allogeneic HCC cells promoted the generation of CD4⁺CD25^highFoxp3⁺Treg and inhibited CTL induction in the presence of HCCsp. Importantly, up-regulation of MHC class II, CD80, and CD83 on DCs was observed in the patient with advanced HCC after vaccination with autologous FCs. In addition, the FCs induced WT1- and CEA-specific CTL that were able to produce high levels of IFN-γ.</p> <p>Conclusion</p> <p>The current study is one of the first demonstrating the induction of antigen-specific CTL and the generation of Treg by fusions of DCs and HCC cells. The local tumor-related factors may favor the generation of Treg through the inhibition of DCs maturation; however, fusion cell vaccination results in recovery of the DCs function and induction of antigen-specific CTL responses in vitro. The present study may shed new light about the mechanisms responsible for the generation of CTL and Treg by FCs.</p

Adventures in the Enormous: A 1.8 Million Clone BAC Library for the 21.7 Gb Genome of Loblolly Pine

Loblolly pine (LP; Pinus taeda L.) is the most economically important tree in the U.S. and a cornerstone species in southeastern forests. However, genomics research on LP and other conifers has lagged behind studies on flowering plants due, in part, to the large size of conifer genomes. As a means to accelerate conifer genome research, we constructed a BAC library for the LP genotype 7-56. The LP BAC library consists of 1,824,768 individually-archived clones making it the largest single BAC library constructed to date, has a mean insert size of 96 kb, and affords 7.6X coverage of the 21.7 Gb LP genome. To demonstrate the efficacy of the library in gene isolation, we screened macroarrays with overgos designed from a pine EST anchored on LP chromosome 10. A positive BAC was sequenced and found to contain the expected full-length target gene, several gene-like regions, and both known and novel repeats. Macroarray analysis using the retrotransposon IFG-7 (the most abundant repeat in the sequenced BAC) as a probe indicates that IFG-7 is found in roughly 210,557 copies and constitutes about 5.8% or 1.26 Gb of LP nuclear DNA; this DNA quantity is eight times the Arabidopsis genome. In addition to its use in genome characterization and gene isolation as demonstrated herein, the BAC library should hasten whole genome sequencing of LP via next-generation sequencing strategies/technologies and facilitate improvement of trees through molecular breeding and genetic engineering. The library and associated products are distributed by the Clemson University Genomics Institute (www.genome.clemson.edu)

Molecular and physiological basis of Saccharomyces cerevisiae tolerance to adverse lignocellulose-based process conditions

Lignocellulose-based biorefineries have been gaining increasing attention to substitute current petroleum-based refineries. Biomass processing requires a pretreatment step to break lignocellulosic biomass recalcitrant structure, which results in the release of a broad range of microbial inhibitors, mainly weak acids, furans, and phenolic compounds. Saccharomyces cerevisiae is the most commonly used organism for ethanol production; however, it can be severely distressed by these lignocellulose-derived inhibitors, in addition to other challenging conditions, such as pentose sugar utilization and the high temperatures required for an efficient simultaneous saccharification and fermentation step. Therefore, a better understanding of the yeast response and adaptation towards the presence of these multiple stresses is of crucial importance to design strategies to improve yeast robustness and bioconversion capacity from lignocellulosic biomass. This review includes an overview of the main inhibitors derived from diverse raw material resultants from different biomass pretreatments, and describes the main mechanisms of yeast response to their presence, as well as to the presence of stresses imposed by xylose utilization and high-temperature conditions, with a special emphasis on the synergistic effect of multiple inhibitors/stressors. Furthermore, successful cases of tolerance improvement of S. cerevisiae are highlighted, in particular those associated with other process-related physiologically relevant conditions. Decoding the overall yeast response mechanisms will pave the way for the integrated development of sustainable yeast cell--based biorefineries.This study was supported by the Portuguese Foundation for Science and Technology (FCT) by the strategic funding of UID/BIO/04469/2013 unit, MIT Portugal Program (Ph.D. grant PD/BD/128247/ 2016 to Joana T. Cunha), Ph.D. grant SFRH/BD/130739/2017 to Carlos E. Costa, COMPETE 2020 (POCI-01-0145-FEDER-006684), BioTecNorte operation (NORTE-01-0145-FEDER-000004), YeasTempTation (ERA-IB-2-6/0001/2014), and MultiBiorefinery project (POCI-01-0145-FEDER-016403). Funding by the Institute for Bioengineering and Biosciences (IBB) from FCT (UID/BIO/04565/2013) and from Programa Operacional Regional de Lisboa 2020 (Project N. 007317) was also receiveinfo:eu-repo/semantics/publishedVersio