Due to its highly reproducible and quantitative nature, and minimal requirements for sample preparation or separation, 1H nuclear magnetic resonance (NMR) spectroscopy is widely used for profiling small-molecule metabolites in biofluids. However 1H NMR spectra contain many overlapped peaks. In particular, blood serum/plasma and diabetic urine samples contain high concentrations of glucose, which produce strong peaks between 3.2 ppm – 4.0 ppm. Signals from most metabolites in this region are overwhelmed by the glucose background signals and become invisible. We propose a simple “Add to Subtract” background subtraction method, and show that it can reduce the glucose signals by 98% to allow retrieval of the hidden information. This procedure includes adding a small drop of concentrated glucose solution to the sample in the NMR tube, mixing, waiting for an equilibration time, and acquisition of a second spectrum. The glucose-free spectra are then generated by spectral subtraction using Bruker Topspin software. Subsequent multivariate statistical analysis can then be used to identify biomarker candidate signals for distinguishing different types of biological samples. The principle of this approach is generally applicable for all quantitative spectral data and should find utility in a variety of NMR-based mixture analyses as well as in metabolite profiling.

Zinc-binding proteins are the most abundant metalloproteins in the Protein Data Bank where the zinc ions usually have catalytic, regulatory or structural roles critical for the function of the protein. Accurate prediction of zinc-binding sites is not only useful for the inference of protein function but also important for the prediction of 3D structure. Here, we present a new integrative framework that combines multiple sequence and structural properties and graph-theoretic network features, followed by an efficient feature selection to improve prediction of zinc-binding sites. We investigate what information can be retrieved from the sequence, structure and network levels that is relevant to zinc-binding site prediction. We perform a two-step feature selection using random forest to remove redundant features and quantify the relative importance of the retrieved features. Benchmarking on a high-quality structural dataset containing 1,103 protein chains and 484 zinc-binding residues, our method achieved >80% recall at a precision of 75% for the zinc-binding residues Cys, His, Glu and Asp on 5-fold cross-validation tests, which is a 10%-28% higher recall at the 75% equal precision compared to SitePredict and zincfinder at residue level using the same dataset. The independent test also indicates that our method has achieved recall of 0.790 and 0.759 at residue and protein levels, respectively, which is a performance better than the other two methods. Moreover, AUC (the Area Under the Curve) and AURPC (the Area Under the Recall-Precision Curve) by our method are also respectively better than those of the other two methods. Our method can not only be applied to large-scale identification of zinc-binding sites when structural information of the target is available, but also give valuable insights into important features arising from different levels that collectively characterize the zinc-binding sites. The scripts and datasets are available at http://protein.cau.edu.cn/zincidentifier/.

The Dynesys dynamics stabilisation system was developed to maintain the mobility of motion segment of the lumbar spine in order to reduce the incidence of negative effects at the adjacent segments. However, the magnitude of cord pretension may change the stiffness of the Dynesys system and result in a diverse clinical outcome, and the effects of Dynesys cord pretension remain unclear. Displacement-controlled finite element analysis was used to evaluate the biomechanical behaviour of the lumbar spine after insertion of Dynesys with three different cord pretensions. For the implanted level, increasing the cord pretension from 100 to 300 N resulted in an increase in flexion stiffness from 19.0 to 64.5 Nm/deg, a marked increase in facet contact force (FCF) of 35% in extension and 32% in torsion, a 40% increase of the annulus stress in torsion, and an increase in the high-stress region of the pedicle screw in flexion and lateral bending. For the adjacent levels, varying the cord pretension from 100 to 300 N only had a minor influence on range of motion (ROM), FCF, and annulus stress, with changes of 6, 12, and 9%, respectively. This study found that alteration of cord pretension affects the ROM and FCF, and annulus stress within the construct but not the adjacent segment. In addition, use of a 300 N cord pretension causes a much higher stiffness at the implanted level when compared with the intact lumbar spine.

Motivation: Nuclear magnetic resonance (NMR) spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, accurate interpretation of the spectra in terms of identities and abundances of metabolites can be challenging, in particular in crowded regions with heavy peak overlap. Although a number of computational approaches for this task have recently been proposed, they are not entirely satisfactory in either accuracy or extent of automation.

Results: We introduce a probabilistic approach Bayesian Quantification (BQuant), for fully automated database-based identification and quantification of metabolites in local regions of 1H NMR spectra. The approach represents the spectra as mixtures of reference profiles from a database, and infers the identities and the abundances of metabolites by Bayesian model selection. We show using a simulated dataset, a spike-in experiment and a metabolomic investigation of plasma samples that BQuant outperforms the available automated alternatives in accuracy for both identification and quantification.

Availability: The R package BQuant is available at: http://www.stat.purdue.edu/~ovitek/BQuant-Web/.

Contact: ovitek@stat.purdue.edu; zhengc@purdue.edu

Supplementary Information: Supplementary data are available at Bioinformatics online.

Many plant and animal viruses counteract RNA silencing-mediated defense by encoding diverse RNA silencing suppressors. We characterized HVT063, a multifunctional protein encoded by turkey herpesvirus (HVT), as a silencing suppressor in coinfiltration assays with green fluorescent protein transgenic Nicotiana benthamiana line 16c. Our results indicated that HVT063 could strongly suppress both local and systemic RNA silencing induced by either sense RNA or double-stranded RNA (dsRNA). HVT063 could reverse local silencing, but not systemic silencing, in newly emerging leaves. The local silencing suppression activity of HVT063 was also verified using the heterologous vector PVX. Further, single alanine substitution of arginine or lysine residues of the HVT063 protein showed that each selected single amino acid contributed to the suppression activity of HVT063 and region 1 (residues 138 to 141) was more important, because three of four single amino acid mutations in this region could abolish the silencing suppressor activity of HVT063. Moreover, HVT063 seemed to induce a cell death phenotype in the infiltrated leaf region, and the HVT063 dilutions could decrease the silencing suppressor activity and alleviate the cell death phenotype. Collectively, these results suggest that HVT063 functions as a viral suppressor of RNA silencing that targets a downstream step of the dsRNA formation in the RNA silencing process. Positively charged amino acids in HVT063, such as arginine and lysine, might contribute to the suppressor activity by boosting the interaction between HVT063 and RNA, since HVT063 has been demonstrated to be an RNA binding protein.

Bamboo mosaic virus (BaMV) is a positive-sense RNA virus belonging to the genus Potexvirus. Open reading frame 1 (ORF1) encodes the viral replication protein that consists of a capping enzyme domain, a helicase-like domain (HLD), and an RNA-dependent RNA polymerase domain from the N to C terminus. ORF5 encodes the viral coat protein (CP) required for genome encapsidation and the virus movement in plants. In this study, application of a yeast-two hybrid assay detected an interaction between the viral HLD and CP. However, the interaction did not affect the NTPase activity of the HLD. To identify the critical amino acids of CP interacting with the HLD, a random mutational library of CP was created using error-prone PCR, and the mutations adversely affecting the interaction were screened by a bacterial two-hybrid system. As a result, the mutations A209G and N210S in CP were found to weaken the interaction. To determine the significance of the interaction, the mutations were introduced into a BaMV infectious clone, and the mutational effects on viral replication, movement, and genome encapsidation were investigated. There was no effect on accumulations of BaMV CP and genomic RNAs within protoplasts; however, the virus cell-to-cell movement in plants was restricted. Sequence alignment revealed that A209 of BaMV CP is conserved in many potexviruses. Mutation of the corresponding residue in Foxtail mosaic virus CP also reduced the viral HLD-CP interaction and restricted the virus movement, suggesting that interaction between CP and a widely conserved HLD in the potexviral replication protein is crucial for viral trafficking through plasmodesmata.

Diagnosis of human bladder cancer in untreated tissue sections is achieved by using imaging data from desorption electrospray ionization mass spectrometry (DESI-MS) combined with multivariate statistical analysis. We use the distinctive DESI-MS glycerophospholipid (GP) mass spectral profiles to visually characterize and formally classify twenty pairs (40 tissue samples) of human cancerous and adjacent normal bladder tissue samples. The individual ion images derived from the acquired profiles correlate with standard histological hematoxylin and eosin (H&E)-stained serial sections. The profiles allow us to classify the disease status of the tissue samples with high accuracy as judged by reference histological data. To achieve this, the data from the twenty pairs were divided into a training set and a validation set. Spectra from the tumor and normal regions of each of the tissue sections in the training set were used for orthogonal projection to latent structures (O-PLS) treated partial least-square discriminate analysis (PLS-DA). This predictive model was then validated by using the validation set and showed a 5% error rate for classification and a misclassification rate of 12%. It was also used to create synthetic images of the tissue sections showing pixel-by-pixel disease classification of the tissue and these data agreed well with the independent classification that uses histological data by a certified pathologist. This represents the first application of multivariate statistical methods for classification by ambient ionization although these methods have been applied previously to other MS imaging methods. The results are encouraging in terms of the development of a method that could be utilized in a clinical setting through visualization and diagnosis of intact tissue.

Background and Aims

Aluminium (Al) toxicity is one of the factors limiting crop production on acid soils. However, genotypic differences exist among plant species or cultivars in response to Al toxicity. This study aims to investigate genotypic differences among eight cultivars of tatary buckwheat (Fagopyrum tataricum) for Al resistance and explore the possible mechanisms of Al resistance.

Methods

Al resistance was evaluated based on relative root elongation (root elongation with Al/root elongation without Al). Root apex Al content, pectin content and exudation of root organic acids were determined and compared.

Key Results

Genotypic differences among the eight cultivars were correlated with exclusion of Al from the root apex. However, there was a lack of correlation between Al exclusion and Al-induced oxalate secretion. Interestingly, cell-wall pectin content of the root apex was generally lower in Al-resistant cultivars than in Al-sensitive cultivars. Although we were unable to establish a significant correlation between Al exclusion and pectin content among the eight cultivars, a strong correlation could be established among six cultivars, in which the pectin content in the most Al-resistant cultivar ‘Chuan’ was significantly lower than that in the most Al-sensitive cultivar ‘Liuku2’. Furthermore, root apex cell-wall pectin methylesterase activity (PME) was similar in ‘Chuan’ and ‘Liuku2’ in the absence of Al, but Al treatment resulted in increased PME activity in ‘Liuku2’ compared with ‘Chuan’. Immunolocalization of pectins also showed that the two cultivars had similar amounts of either low-methyl-ester pectins or high-methyl-ester pectins in the absence of Al, but Al treatment resulted in a more significant increase of low-methyl-ester pectins and decrease of high-methyl-ester pectins in ‘Liuku2’.

Conclusions

Cell-wall pectin content may contribute, at least in part, to differential Al resistance among tatary buckwheat cultivars.

A large number of proteins transferred by the Legionella pneumophila Dot/Icm system have been identified by various strategies. With no exceptions, these strategies are based on one or more characteristics associated with the tested proteins. Given the high level of diversity exhibited by the identified proteins, it is possible that some substrates have been missed in these screenings. In this study, we took a systematic method to survey the L. pneumophila genome by testing hypothetical orfs larger than 300 base pairs for Dot/Icm-dependent translocation. 798 of the 832 analyzed orfs were successfully fused to the carboxyl end of β-lactamase. The transfer of the fusions into mammalian cells was determined using the β-lactamase reporter substrate CCF4-AM. These efforts led to the identification of 164 proteins positive in translocation. Among these, 70 proteins are novel substrates of the Dot/Icm system. These results brought the total number of experimentally confirmed Dot/Icm substrates to 275. Sequence analysis of the C-termini of these identified proteins revealed that Lpg2844, which contains few features known to be important for Dot/Icm-dependent protein transfer can be translocated at a high efficiency. Thus, our efforts have identified a large number of novel substrates of the Dot/Icm system and have revealed the diverse features recognizable by this protein transporter.

Metabolic profiling of urine presents challenges due to the extensive random variation of metabolite concentrations, and to dilution resulting from changes in the overall urine volume. Thus statistical analysis methods play a particularly important role, however appropriate choices of these methods are not straightforward. Here we investigate constant and variance-stabilization normalization of raw and peak picked spectra, for use with exploratory analysis (principal component analysis) and confirmatory analysis (ordinary and Empirical Bayes t-test) in 1H NMR-based metabolic profiling of urine. We compare the performance of these methods using urine samples spiked with known metabolites according to a Latin square design. We find that analysis of peak picked and log-transformed spectra is preferred, and that signal processing and statistical analysis steps are interdependent. While variance-stabilizing transformation is preferred in conjunction with principal component analysis, constant normalization is more appropriate for use with a t-test. Empirical Bayes t-test provides more reliable conclusions when the number of samples in each group is relatively small. Performance of these methods is illustrated using a clinical metabolomics experiment on patients with type 1 diabetes to evaluate the effect of insulin deprivation.

Background

Finite element analysis results will show significant differences if the model used is performed under various material properties, geometries, loading modes or other conditions. This study adopted an FE model, taking into account the possible asymmetry inherently existing in the spine with respect to the sagittal plane, with a more geometrically realistic outline to analyze and compare the biomechanical behaviour of the lumbar spine with regard to the facet force and intradiscal pressure, which are associated with low back pain symptoms and other spinal disorders. Dealing carefully with the contact surfaces of the facet joints at various levels of the lumbar spine can potentially help us further ascertain physiological behaviour concerning the frictional effects of facet joints under separate loadings or the responses to the compressive loads in the discs.

Methods

A lumbar spine model was constructed from processes including smoothing the bony outline of each scan image, stacking the boundary lines into a smooth surface model, and subsequent further processing in order to conform with the purpose of effective finite element analysis performance. For simplicity, most spinal components were modelled as isotropic and linear materials with the exception of spinal ligaments (bilinear). The contact behaviour of the facet joints and changes of the intradiscal pressure with different postures were analyzed.

Results

The results revealed that asymmetric responses of the facet joint forces exist in various postures and that such effect is amplified with larger loadings. In axial rotation, the facet joint forces were relatively larger in the contralateral facet joints than in the ipsilateral ones at the same level. Although the effect of the preloads on facet joint forces was not apparent, intradiscal pressure did increase with preload, and its magnitude increased more markedly in flexion than in extension and axial rotation.

Conclusions

Disc pressures showed a significant increase with preload and changed more noticeably in flexion than in extension or in axial rotation. Compared with the applied preloads, the postures played a more important role, especially in axial rotation; the facet joint forces were increased in the contralateral facet joints as compared to the ipsilateral ones at the same level of the lumbar spine.

SYNOPSIS

Objectives

This study utilized the electronic medical records of six veterinary hospitals (operated by Banfield, The Pet Hospital®) in the vicinity of Fairburn, Georgia, to assess the health of dogs and cats following the unintentional release of propyl mercaptan from a waste-processing facility.

Methods

Standardized electronic medical records were used to define clinical syndromes (eye inflammation, gastrointestinal, respiratory, fever, general weakness/change in mental state) in dogs and cats. The frequency and geographic distribution of each syndrome was evaluated before, during, and after the chemical release, using control charts, density maps, change in average mean distance from a suspected point source of chemical release, space-time statistics, and autoregressive integrated moving averages.

Results

No consistent pattern of change in syndromic events was observed following the suspected release of propyl mercaptan. Some syndromes, including respiratory syndrome in cats, gastrointestinal syndrome in dogs, and eye inflammation syndrome in both cats and dogs, showed a change in time and spatial patterns following the release of propyl mercaptan into the community. These changes were consistent with clinical signs observed in people during a previous propyl mercaptan release in California as well as the release in Fairburn.

Conclusion

A systematic review of electronic medical records of dogs and cats exposed to release of propyl mercaptan showed no conclusive and consistent evidence of adverse health effects. Methods for the use of medical records of pets for detecting environmental hazards require further development and evaluation.

Recent studies demonstrated that PNZIP and its homologs encode a special cyclase and play an important role in chlorophyll biosynthesis in higher plants. To investigate the molecular mechanism governing the PNZIP gene, the PNZIP promoter was isolated and analyzed. Deletion analysis indicated that G-box is an important element in the regulation of the reporter gene expression. Further mutation assay demonstrated that G-box and GATACT elements are necessary and sufficient for the high and tissue-specific expression of the GUS gene. Using yeast one-hybrid screening, we have isolated a novel tobacco bZIP protein, NtbZIP, which can specifically recognize the G-box of the PNZIP promoter. The NtbZIP protein shares a limited amino acid homology to Arabidopsis ABI5 and AtAREB1 and very low homology to other bZIP proteins. Northern blot analysis showed that the NtbZIP gene is not induced by exogenous ABA and is expressed in different tobacco organs. Cotransformation assays showed that the NtbZIP protein could activate the transcription of the GUS gene driven by the PNZIP promoter. Transgenic tobaccos analysis demonstrated that constitutively expressing antisense NtbZIP gene resulted in a lower NTZIP synthesis and reduced chlorophyll levels. We suggest that NTZIP is a target gene of NtbZIP, which is involved in the regulation of chlorophyll biosynthesis.

It is well known that the topological phenomena with fractional excitations, the fractional quantum Hall effect, will emerge when electrons move in Landau levels. Here we show the theoretical discovery of the fractional quantum Hall effect in the absence of Landau levels in an interacting fermion model. The non-interacting part of our Hamiltonian is the recently proposed topologically non-trivial flat-band model on a checkerboard lattice. In the presence of nearest-neighbouring repulsion, we find that at 1/3 filling, the Fermi-liquid state is unstable towards the fractional quantum Hall effect. At 1/5 filling, however, a next-nearest-neighbouring repulsion is needed for the occurrence of the 1/5 fractional quantum Hall effect when nearest-neighbouring repulsion is not too strong. We demonstrate the characteristic features of these novel states and determine the corresponding phase diagram.

The fractional quantum Hall effect occurs when electrons move in Landau levels. In this study, using a theoretical flat-band lattice model, the fractional quantum Hall effect is observed in the presence of repulsive interactions when the band is one third full and in the absence of Landau levels.