Targeting autophagy for drug-induced hepatotoxicity

Autophagy is a lysosomal degradation pathway for bulk cytosolic proteins and damaged organelles, and is well known to act as a cell survival mechanism. Acetaminophen (APAP) overdose can cause liver injury in animals and humans by inducing necrosis due to mitochondrial damage. We recently found that pharmacological induction of autophagy by rapamycin protects against, whereas pharmacological suppression of autophagy by chloroquine exacerbates, APAP-induced liver injury in mice. Autophagy is induced to remove APAP-induced damaged mitochondria and thus attenuates APAP-induced hepatocyte necrosis. To our surprise, we found that liver-specific Atg5 knockout mice are not more susceptible, but are resistant to APAP-induced liver injury due to compensatory effects. Our work suggests that pharmacological modulation of autophagy is a novel therapeutic approach to ameliorate APAP-induced liver injury. Moreover, our work also suggests that caution needs to be exercised when using genetic autophagy gene knockout mice for pathophysiological studies.     

Targeting autophagy for drug-induced hepatotoxicity

Autophagy is a lysosomal degradation pathway for bulk cytosolic proteins and damaged organelles, and is well known to act as a cell survival mechanism. Acetaminophen (APAP) overdose can cause liver injury in animals and humans by inducing necrosis due to mitochondrial damage. We recently found that pharmacological induction of autophagy by rapamycin protects against, whereas pharmacological suppression of autophagy by chloroquine exacerbates, APAP-induced liver injury in mice. Autophagy is induced to remove APAP-induced damaged mitochondria and thus attenuates APAP-induced hepatocyte necrosis. To our surprise, we found that liver-specific Atg5 knockout mice are not more susceptible, but are resistant to APAP-induced liver injury due to compensatory effects. Our work suggests that pharmacological modulation of autophagy is a novel therapeutic approach to ameliorate APAP-induced liver injury. Moreover, our work also suggests that caution needs to be exercised when using genetic autophagy gene knockout mice for pathophysiological studies.     

Prediction of hepatotoxicity for drugs using human pluripotent stem cell-derived hepatocytes

Drug-induced liver toxicity is a main reason for withdrawals of new drugs in late clinical phases and post-launch of the drugs. Thus, hepatotoxicity screening of drug candidates in pre-clinical stage is important for reducing drug attrition rates during the clinical development process. Here, we show commercially available hepatocytes that could be used for early toxicity evaluation of drug candidates. From our hepatic differentiation technology, we obtained highly pure (≥98%) hepatocytes from human embryonic stem cells (hESCs) having mature phenotypes and similar gene expression profiles with those of primary human tissues. Furthermore, we optimized 96-well culture condition of hESC-derived hepatocytes suitable for toxicity tests in vitro. To this end, we demonstrated the efficacy of our optimized hepatocyte model for predicting hepatotoxicity against the Chinese herbal medicines and showed that toxicity patterns from our hepatocyte model was similar to those of human primary cultured hepatocytes. We conclude that toxicity test using our hepatocyte model could be a good alternative cell source for pre-clinical study to predict potential hepatotoxicity in drug discovery industries.     

Evaluation of HepaRG cells for the assessment of indirect drug-induced hepatotoxicity using INH as a model substance

HepaRG cells are widely used as an in vitro model to assess drug-induced hepatotoxicity. However, only few studies exist so far regarding their suitability to detect the effects of drugs requiring a preceding activation via the cytochrome P450 (CYP) system. A prototypic substance is the anti-tuberculosis agent INH, which is metabolized into N-acetylhydrazine, which then triggers hepatotoxicity. Therefore, the aim of the present study was to test if this effect can also be detected in HepaRG cells and if it can be counteracted by the known hepatoprotectant silibinin. For this purpose, differentiated HepaRG cells were treated with increasing concentrations of INH (0.1–100 mM) or 10 mM INH plus escalating concentrations of silibinin (1–100 µM). After 48 h of treatment, cell morphology and parameters indicating cell vitality, oxidative stress, and liver cell function were assessed. High concentrations of INH led to severe histopathological changes, reduced cell vitality and glutathione content, increased LDH and ASAT release into the medium, enhanced lipid peroxidation, and elevated cleaved caspase-3 expression. Additionally, glycogen depletion and reduced biotransformation capacity were seen at high INH concentrations, whereas at low concentrations an induction of biotransformation enzymes was noticed. Silibinin caused clear-cut protective effects, but with few parameters INH toxicity was even aggravated, most probably due to increased metabolization of INH into its toxic metabolite. In conclusion, HepaRG cells are excellently suited to evaluate the effects of substances requiring prior toxification via the CYP system, such as INH. They additionally enable the identification of complex substance interactions.     

Animal models of drug-induced pulmonary fibrosis: an overview of molecular mechanisms and characteristics

Cell Biology and Toxicology - Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease characterized by progressive loss of pulmonary function. Drug-induced interstitial lung...     

Automatic procedure for using models of proteins in molecular replacement

In a crystallography experiment, a crystal is irradiated with X-rays whose diffracted waves are collected and measured. The reconstruction of the structure of the molecule in the crystal requires knowledge of the phase of the diffracted waves, information that is lost in the passage from the three-dimensional structure of the molecule to its diffraction pattern. It can be recovered using experimental methods such as heavy-atom isomorphous replacement and anomalous scattering or by molecular replacement, which relies on the availability of an atomic model of the target structure. This can be the structure of the target protein itself, if a previous structure determination is available, or a computational model or, in some cases, the structure of a homologous protein. It is not straightforward to predict beforehand whether or not a computational model will work in a molecular replacement experiment, although some rules of thumb exist. The consensus is that even minor differences in the quality of the model, which are rather difficult to estimate a priori, can have a significant effect on the outcome of the procedure. We describe here a method for quickly assessing whether a protein structure can be solved by molecular replacement. The procedure consists in submitting the sequence of the target protein to a selected list of freely available structure prediction servers, cluster the resulting models, select the representative structures of each cluster and use them as search models in an automatic phasing procedure. We tested the procedure using the structure factors of newly released proteins of known structure downloaded from the Protein Data Bank as soon as they were made available. Using our automatic procedure we were able to obtain an interpretable electron density map in more than half the cases.     

Low-cost image processing system for analyzing molecular RNA fingerprints.

A complete image digitizing and processing system is described for capturing, enhancing and analyzing molecular fingerprints. The low-cost, high-resolution system features a Motorola 68000 processor, multi-tasking, a separate video coprocessor, and color or gray scale processing. Thousands of manipulations are possible using functions which include histographic equalization, edge detection, filtering, overlays, false coloring, zoom, pan and print. All operations are initiated and controlled with a mouse. Techniques for enhancing, scaling and comparing molecular fingerprints are described. The techniques all involve using a graphical interface to select and manipulate the various processes. The system has been used successfully for about 1.5 years, and it has been ideal for our application which requires human judgment at many steps between processing and which probably would not lend itself to a completely automated analysis. Similar techniques could probably be used with this system on many other applications.     

Prediction using partly conditional time-varying coefficients regression models

Data collected longitudinally in time provide the opportunity to develop predictive models of future observations given current data for an individual. Such models may be of particular value in defining individuals at high risk and thereby in suggesting subgroups for targeting of prevention intervention research efforts. In this paper, we propose a method for estimating predictive functions. The method uses an extension of the marginal regression analysis methods of Liang and Zeger (1986, Biometrika 73, 13-22) and is implemented using simple estimating equations. A key feature of the models is that regression coefficients are modelled as smooth functions of the times both at and for prediction. Data from a study of obesity in childhood and early adulthood is used to demonstrate the methodology. Criteria for defining individuals to be at high risk can be defined on the basis of estimated predictive functions. We suggest methods for evaluating the diagnostic accuracy (sensitivity and specificity) of such rules using cross-validation. The method holds promise as a robust and technically easy way of evaluating information about future prognosis that may be gleaned from a patient's current and past clinical status.     

Bacterial classification using genomic fingerprints obtained by virtual hybridization

In silico genomic fingerprints were produced by virtual hybridization of 191 fully sequenced bacterial genomes using a set of 15,264 13-mer probes specially designed to produce universal whole genome fingerprints. A novel approach for constructing phylogenetic trees, based on comparative analysis of genomic fingerprints, was developed. The resultant bacterial phylogenetic tree had strong similarities to those produced from the alignment of conserved sequences. Notably, the trees derived from the alignment of other conserved COG genes divided the Bacillus and Corynebacterium genera into the same subgroups produced by the novel bacterial tree. A number of discrepancies between both techniques were observed for the grouping of some Lactobacillus species. However, a detailed analysis of the alignment of these genomes using other bioinformatics tools revealed that the grouping of these organisms in the novel tree was more satisfactory than the groupings from previous classifications, which used only a few conserved genes. All these data suggest that the bacterial taxonomy produced by genomic fingerprints is satisfactory, but sometimes different from classical taxonomies. Discrepancies probably arise because the fingerprinting technique analyzes genomic sequences and reveals more information than previously used approaches.     

Bacterial classification using genomic fingerprints obtained by virtual hybridization

In silico genomic fingerprints were produced by virtual hybridization of 191 fully sequenced bacterial genomes using a set of 15,264 13-mer probes specially designed to produce universal whole genome fingerprints. A novel approach for constructing phylogenetic trees, based on comparative analysis of genomic fingerprints, was developed. The resultant bacterial phylogenetic tree had strong similarities to those produced from the alignment of conserved sequences. Notably, the trees derived from the alignment of other conserved COG genes divided the Bacillus and Corynebacterium genera into the same subgroups produced by the novel bacterial tree. A number of discrepancies between both techniques were observed for the grouping of some Lactobacillus species. However, a detailed analysis of the alignment of these genomes using other bioinformatics tools revealed that the grouping of these organisms in the novel tree was more satisfactory than the groupings from previous classifications, which used only a few conserved genes. All these data suggest that the bacterial taxonomy produced by genomic fingerprints is satisfactory, but sometimes different from classical taxonomies. Discrepancies probably arise because the fingerprinting technique analyzes genomic sequences and reveals more information than previously used approaches.     

Display algorithm for space-filling molecular models using a video array processor

A new algorithm for the generation of coloured, space-filling molecular models is described. It relies on the parallel processing facilities of a DeAnza IP8500 raster graphics system to increase the speed of display generation. Using suitable storage of the information about the type as well as the colour of each atom, it becomes possible to switch rapidly between various schemes of colouring. Results are shown with DNA and protein molecules.     

Prediction of protein subcellular localization by weighted gene ontology terms

We develop a new weighting approach of gene ontology (GO) terms for predicting protein subcellular localization. The weights of individual GO terms, corresponding to their contribution to the prediction algorithm, are determined by the term-weighting methods used in text categorization. We evaluate several term-weighting methods, which are based on inverse document frequency, information gain, gain ratio, odds ratio, and chi-square and its variants. Additionally, we propose a new term-weighting method based on the logarithmic transformation of chi-square. The proposed term-weighting method performs better than other term-weighting methods, and also outperforms state-of-the-art subcellular prediction methods. Our proposed method achieves 98.1%, 99.3%, 98.1%, 98.1%, and 95.9% overall accuracies for the animal BaCelLo independent dataset (IDS), fungal BaCelLo IDS, animal Höglund IDS, fungal Höglund IDS, and PLOC dataset, respectively. Furthermore, the close correlation between high-weighted GO terms and subcellular localizations suggests that our proposed method appropriately weights GO terms according to their relevance to the localizations.     

Testing macro-evolutionary models using incomplete molecular phylogenies.

Phylogenies reconstructed from gene sequences can be used to investigate the tempo and mode of species diversification. Here we develop and use new statistical methods to infer past patterns of speciation and extinction from molecular phylogenies. Specifically, we test the null hypothesis that per-lineage speciation and extinction rates have remained constant through time. Rejection of this hypothesis may provide evidence for evolutionary events such as adaptive radiations or key adaptations. In contrast to previous approaches, our methods are robust to incomplete taxon sampling and are conservative with respect to extinction. Using simulation we investigate, first, the adverse effects of failing to take incomplete sampling into account and, second, the power and reliability of our tests. When applied to published phylogenies our tests suggest that, in some cases, speciation rates have decreased through time.     

Prediction of nuclear proteins using SVM and HMM models

Background  

The nucleus, a highly organized organelle, plays important role in cellular homeostasis. The nuclear proteins are crucial for chromosomal maintenance/segregation, gene expression, RNA processing/export, and many other processes. Several methods have been developed for predicting the nuclear proteins in the past. The aim of the present study is to develop a new method for predicting nuclear proteins with higher accuracy.     

Refinement of comparative models of protein structure by using multicanonical molecular dynamics simulations

Comparative modelling is a powerful method that easily predicts a considerably accurate structure of a protein by using a template structure having a similar amino-acid sequence to the target protein. However, in the region where the amino-acid sequence is different between the target and the template, the predicted structure remains unreliable. In such a case, the model has to be refined. In the present study, we explored the possibility of a molecular dynamics-based method, using the human SAP Src Homology 2 (SH2) domain as the modelling target. The multicanonical method was used to alleviate the multiple-minima problem and the generalised Born/surface area model was used to reduce the computational cost. In addition, position restraints were imposed on the atoms in the reliable regions to avoid unnecessary conformational sampling. We analyzed the conformational distribution of the ligand-recognition loop of the domain and found that the most populated conformational clusters in the ensemble of the model agreed well with one of the two major clusters in the ensemble of the reference simulation starting from the crystal structure. This demonstrates that the current refinement method can significantly improve the accuracy of an unreliable region in a comparative model.     

A new method for taking fingerprints using photographic film

A new method for obtaining dermatoglyphic prints is described. Photographic film is used enabling prints to be obtained directly, and at any enlargement. The sweat-pores can be shown in detail, and counted.     

Comparison of molecular species identification for North Sea calanoid copepods (Crustacea) using proteome fingerprints and DNA sequences

Calanoid copepods play an important role in the pelagic ecosystem making them subject to various taxonomic and ecological studies, as well as indicators for detecting changes in the marine habitat. For all these investigations, valid identification, mainly of sibling and cryptic species as well as early life history stages, represents a central issue. In this study, we compare species identification methods for pelagic calanoid copepod species from the North Sea and adjacent regions in a total of 333 specimens. Morphologically identified specimens were analysed on the basis of nucleotide sequences (i.e. partial mitochondrial cytochrome c oxidase subunit I (COI) and complete 18S rDNA) and on proteome fingerprints using the technology of matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS). On all three molecular approaches, all specimens were classified to species level indicated by low intraspecific and high interspecific variability. Sequence divergences in both markers revealed a second Pseudocalanus species for the southern North Sea identified as Pseudocalanus moultoni by COI sequence comparisons to GenBank. Proteome fingerprints were valid for species clusters irrespective of high intraspecific variability, including significant differences between early developmental stages and adults. There was no effect of sampling region or time; thus, trophic effect, when analysing the whole organisms, was observed in species‐specific protein mass spectra, underlining the power of this tool in the application on metazoan species identification. Because of less sample preparation steps, we recommend proteomic fingerprinting using the MALDI‐TOF MS as an alternative or supplementary approach for rapid, cost‐effective species identification.