Search

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are post-transcriptional regulatory RNAs that can modulate cell signaling and play key roles in cell state transitions. Epstein-Barr virus (EBV) expresses >40 viral miRNAs that manipulate both viral and cellular gene expression patterns and contribute to reprogramming of the host environment during infection. Here, we identified a subset of EBV miRNAs that desensitize cells to B cell receptor (BCR) stimuli, and attenuate the downstream activation of NF-kappaB or AP1-dependent transcription. Bioinformatics and pathway analysis of Ago PAR-CLIP datasets identified multiple EBV miRNA targets related to BCR signal transduction, including GRB2, SOS1, MALT1, RAC1, and INPP5D, which we validated in reporter assays. BCR signaling is critical for B cell activation, proliferation, and differentiation, and for EBV, is linked to reactivation. In functional assays, we demonstrate that EBV miR-BHRF1-2-5p contributes to the growth of latently infected B cells through GRB2 regulation. We further determined that activities of EBV miR-BHRF1-2-5p, EBV miR-BART2-5p, and a cellular miRNA, miR-17-5p, directly regulate virus reactivation triggered by BCR engagement. Our findings provide mechanistic insight into some of the key miRNA interactions impacting the proliferation of latently infected B cells and importantly, governing the latent to lytic switch. [ABSTRACT FROM AUTHOR]

A feature point based method is proposed for tracking multiple fish in 3D space. First, a simplified representation of the object is realized through construction of two feature point models based on its appearance characteristics. After feature points are classified into occluded and non-occluded types, matching and association are performed, respectively. Finally, the object's motion trajectory in 3D space is obtained through integrating multi-view tracking results. Experimental results show that the proposed method can simultaneously track 3D motion trajectories for up to 10 fish accurately and robustly. [ABSTRACT FROM AUTHOR]

Preharvest sprouting reduces the maize quality and causes a significant yield loss in maize production. vp-wl2 is a Mutator (Mu)-induced viviparous mutant in maize, causing white or pale yellow kernels, dramatically reduced carotenoid and ABA content, and a high level of zeta-carotene accumulation. Here, we reported the cloning of the vp-wl2 gene using a modified digestion-ligation-amplification method (DLA). The results showed that an insertion of Mu9 in the first intron of the zeta-carotene desaturase (ZDS) gene results in the vp-wl2 mutation. Previous studies have suggested that ZDS is likely the structural gene of the viviparous9 (vp9) locus. Therefore, we performed an allelic test using vp-wl2 and three vp9 mutants. The results showed that vp-wl2 is a novel allele of the vp9 locus. In addition, the sequences of ZDS gene were identified in these three vp9 alleles. The vp-wl2 mutant gene was subsequently introgressed into four maize inbred lines, and a viviparous phenotype was observed with yield losses from 7.69% to 13.33%. [ABSTRACT FROM AUTHOR]

Antibody therapy against antibiotics resistant Klebsiella pneumoniae infections represents a promising strategy, the success of which depends critically on the ability to identify appropriate antibody targets. Using a target-agnostic strategy, we recently discovered MrkA as a potential antibody target and vaccine antigen. Interestingly, the anti-MrkA monoclonal antibodies isolated through phage display and hybridoma platforms all recognize an overlapping epitope, which opens up important questions including whether monoclonal antibodies targeting different MrkA epitopes can be generated and if they possess different protective profiles. In this study we generated four anti-MrkA antibodies targeting different epitopes through phage library panning against recombinant MrkA protein. These anti-MrkA antibodies elicited strong in vitro and in vivo protections against a multi-drug resistant Klebsiella pneumoniae strain. Furthermore, mutational and epitope analysis suggest that the two cysteine residues may play essential roles in maintaining a MrkA structure that is highly compacted and exposes limited antibody binding/neutralizing epitopes. These results suggest the need for further in-depth understandings of the structure of MrkA, the role of MrkA in the pathogenesis of Klebsiella pneumoniae and the protective mechanism adopted by anti-MrkA antibodies to fully explore the potential of MrkA as an efficient therapeutic target and vaccine antigen. [ABSTRACT FROM AUTHOR]

Biofilm formed by Staphylococcus aureus significantly enhances antibiotic resistance by inhibiting the penetration of antibiotics, resulting in an increasingly serious situation. This study aimed to assess whether baicalein can prevent Staphylococcus aureus biofilm formation and whether it may have synergistic bactericidal effects with antibiotics in vitro. To do this, we used a clinically isolated strain of Staphylococcus aureus 17546 (t037) for biofilm formation. Virulence factors were detected following treatment with baicalein, and the molecular mechanism of its antibiofilm activity was studied. Plate counting, crystal violet staining, and fluorescence microscopy revealed that 32 μg/mL and 64 μg/mL baicalein clearly inhibited 3- and 7-day biofilm formation in vitro. Moreover, colony forming unit count, confocal laser scanning microscopy, and scanning electron microscopy showed that vancomycin (VCM) and baicalein generally enhanced destruction of biofilms, while VCM alone did not. Western blotting and real-time quantitative polymerase chain reaction analyses (RTQ-PCR) confirmed that baicalein treatment reduced staphylococcal enterotoxin A (SEA) and α-hemolysin (hla) levels. Most strikingly, real-time qualitative polymerase chain reaction data demonstrated that 32 μg/mL and 64 μg/mL baicalein downregulated the quorum-sensing system regulators agrA, RNAIII, and sarA, and gene expression of ica, but 16 μg/mL baicalein had no effect. In summary, baicalein inhibited Staphylococcus aureus biofilm formation, destroyed biofilms, increased the permeability of vancomycin, reduced the production of staphylococcal enterotoxin A and α-hemolysin, and inhibited the quorum sensing system. These results support baicalein as a novel drug candidate and an effective treatment strategy for Staphylococcus aureus biofilm-associated infections. [ABSTRACT FROM AUTHOR]

To clarify the mechanisms of Nosema ceranae parasitism, we deep-sequenced both honey bee host and parasite mRNAs throughout a complete 6-day infection cycle. By time-series analysis, 1122 parasite genes were significantly differently expressed during the reproduction cycle, clustering into 4 expression patterns. We found reactive mitochondrial oxygen species modulator 1 of the host to be significantly down regulated during the entire infection period. Our data support the hypothesis that apoptosis of honey bee cells was suppressed during infection. We further analyzed genome-wide genetic diversity of this parasite by comparing samples collected from the same site in 2007 and 2013. The number of SNP positions per gene and the proportion of non-synonymous substitutions per gene were significantly reduced over this time period, suggesting purifying selection on the parasite genome and supporting the hypothesis that a subset of N. ceranae strains might be dominating infection. [ABSTRACT FROM AUTHOR]

Genomic selection has been widely used for complex quantitative trait in farm animals. Estimations of breeding values for slaughter traits are most important to beef cattle industry, and it is worthwhile to investigate prediction accuracies of genomic selection for these traits. In this study, we assessed genomic predictive abilities for average daily gain weight (ADG), live weight (LW), carcass weight (CW), dressing percentage (DP), lean meat percentage (LMP) and retail meat weight (RMW) using Illumina Bovine 770K SNP Beadchip in Chinese Simmental cattle. To evaluate the abilities of prediction, marker effects were estimated using genomic BLUP (GBLUP) and three parallel Bayesian models, including multiple chains parallel BayesA, BayesB and BayesCπ (PBayesA, PBayesB and PBayesCπ). Training set and validation set were divided by random allocation, and the predictive accuracies were evaluated using 5-fold cross validations. We found the accuracies of genomic predictions ranged from 0.195±0.084 (GBLUP for LMP) to 0.424±0.147 (PBayesB for CW). The average accuracies across traits were 0.327±0.085 (GBLUP), 0.335±0.063 (PBayesA), 0.347±0.093 (PBayesB) and 0.334±0.077 (PBayesCπ), respectively. Notably, parallel Bayesian models were more accurate than GBLUP across six traits. Our study suggested that genomic selections with multiple chains parallel Bayesian models are feasible for slaughter traits in Chinese Simmental cattle. The estimations of direct genomic breeding values using parallel Bayesian methods can offer important insights into improving prediction accuracy at young ages and may also help to identify superior candidates in breeding programs. [ABSTRACT FROM AUTHOR]

Drought is the one of the most important environment stresses that restricts crop yield worldwide. Cassava (Manihot esculenta Crantz) is an important food and energy crop that has many desirable traits such as drought, heat and low nutrients tolerance. However, the mechanisms underlying drought tolerance in cassava are unclear. Ethylene signaling pathway, from the upstream receptors to the downstream transcription factors, plays important roles in environmental stress responses during plant growth and development. In this study, we used bioinformatics approaches to identify and characterize candidate Manihot esculenta ethylene receptor genes and transcription factor genes. Using computational methods, we localized these genes on cassava chromosomes, constructed phylogenetic trees and identified stress-responsive cis-elements within their 5’ upstream regions. Additionally, we measured the trehalose and proline contents in cassava fresh leaves after drought, osmotic, and salt stress treatments, and then it was found that the regulation patterns of contents of proline and trehalose in response to various dehydration stresses were differential, or even the opposite, which shows that plant may take different coping strategies to deal with different stresses, when stresses come. Furthermore, expression profiles of these genes in different organs and tissues under non-stress and abiotic stress were investigated through quantitative real-time PCR (qRT-PCR) analyses in cassava. Expression profiles exhibited clear differences among different tissues under non-stress and various dehydration stress conditions. We found that the leaf and tuberous root tissues had the greatest and least responses, respectively, to drought stress through the ethylene signaling pathway in cassava. Moreover, tuber and root tissues had the greatest and least reponses to osmotic and salt stresses through ethylene signaling in cassava, respectively. These results show that these plant tissues had differential expression levels of genes involved in ethylene signaling in response to the stresses tested. Moreover, after several gene duplication events, the spatiotemporally differential expression pattern of homologous genes in response to abiotic and biotic stresses may imply their functional diversity as a mechanism for adapting to the environment. Our data provide a framework for further research on the molecular mechanisms of cassava resistance to drought stress and provide a foundation for breeding drought-resistant new cultivars. [ABSTRACT FROM AUTHOR]

Three conventional Bayesian approaches (BayesA, BayesB and BayesCπ) have been demonstrated to be powerful in predicting genomic merit for complex traits in livestock. A priori, these Bayesian models assume that the non-zero SNP effects (marginally) follow a t-distribution depending on two fixed hyperparameters, degrees of freedom and scale parameters. In this study, we performed genomic prediction in Chinese Simmental beef cattle and treated degrees of freedom and scale parameters as unknown with inappropriate priors. Furthermore, we compared the modified methods (BayesFA, BayesFB and BayesFCπ) with their corresponding counterparts using simulation datasets. We found that the modified methods with distribution assumed to the two hyperparameters were beneficial for improving the predictive accuracy. Our results showed that the predictive accuracies of the modified methods were slightly higher than those of their counterparts especially for traits with low heritability and a small number of QTLs. Moreover, cross-validation analysis for three traits, namely carcass weight, live weight and tenderloin weight, in 1136 Simmental beef cattle suggested that predictive accuracy of BayesFCπ noticeably outperformed BayesCπ with the highest increase (3.8%) for live weight using the cohort masking cross-validation. [ABSTRACT FROM AUTHOR]

Zebrafish (Danio rerio) is one of the most widely used model organisms in collective behavior research. Multi-object tracking with high speed camera is currently the most feasible way to accurately measure their motion states for quantitative study of their collective behavior. However, due to difficulties such as their similar appearance, complex body deformation and frequent occlusions, it is a big challenge for an automated system to be able to reliably track the body geometry of each individual fish. To accomplish this task, we propose a novel fish body model that uses a chain of rectangles to represent fish body. Then in detection stage, the point of maximum curvature along fish boundary is detected and set as fish nose point. Afterwards, in tracking stage, we firstly apply Kalman filter to track fish head, then use rectangle chain fitting to fit fish body, which at the same time further judge the head tracking results and remove the incorrect ones. At last, a tracklets relinking stage further solves trajectory fragmentation due to occlusion. Experiment results show that the proposed tracking system can track a group of zebrafish with their body geometry accurately even when occlusion occurs from time to time. [ABSTRACT FROM AUTHOR]