Phytopathogen type III effector weaponry and their plant targets

Phytopathogenic bacteria suppress plant innate immunity and promote pathogenesis by injecting proteins called type III effectors into plant cells using a type III protein secretion system. These type III effectors use at least three major strategies to alter host responses. One strategy is to alter host protein turnover, either by direct cleavage or by modulating ubiquitination and targeting to the 26S proteasome. Another strategy involves alteration of RNA metabolism by transcriptional activation or ADP-ribosylation of RNA-binding proteins. A third major strategy is to inhibit the kinases involved in plant defence signalling, either by removing phosphates or by direct inhibition. The wide array of strategies bacterial pathogens employ to suppress innate immunity suggest that circumvention of innate immunity is critical for bacterial pathogenicity of plants

Phytopathogen type III effector weaponry and their plant targets

Phytopathogenic bacteria suppress plant innate immunity and promote pathogenesis by injecting proteins called type III effectors into plant cells using a type III protein secretion system. These type III effectors use at least three major strategies to alter host responses. One strategy is to alter host protein turnover, either by direct cleavage or by modulating ubiquitination and targeting to the 26S proteasome. Another strategy involves alteration of RNA metabolism by transcriptional activation or ADP-ribosylation of RNA-binding proteins. A third major strategy is to inhibit the kinases involved in plant defence signalling, either by removing phosphates or by direct inhibition. The wide array of strategies bacterial pathogens employ to suppress innate immunity suggest that circumvention of innate immunity is critical for bacterial pathogenicity of plants

The combination approach of SVM and ECOC for powerful identification and classification of transcription factor

<p>Abstract</p> <p>Background</p> <p>Transcription factors (TFs) are core functional proteins which play important roles in gene expression control, and they are key factors for gene regulation network construction. Traditionally, they were identified and classified through experimental approaches. In order to save time and reduce costs, many computational methods have been developed to identify TFs from new proteins and to classify the resulted TFs. Though these methods have facilitated screening of TFs to some extent, low accuracy is still a common problem. With the fast growing number of new proteins, more precise algorithms for identifying TFs from new proteins and classifying the consequent TFs are in a high demand.</p> <p>Results</p> <p>The support vector machine (SVM) algorithm was utilized to construct an automatic detector for TF identification, where protein domains and functional sites were employed as feature vectors. Error-correcting output coding (ECOC) algorithm, which was originated from information and communication engineering fields, was introduced to combine with support vector machine (SVM) methodology for TF classification. The overall success rates of identification and classification achieved 88.22% and 97.83% respectively. Finally, a web site was constructed to let users access our tools (see Availability and requirements section for URL).</p> <p>Conclusion</p> <p>The SVM method was a valid and stable means for TFs identification with protein domains and functional sites as feature vectors. Error-correcting output coding (ECOC) algorithm is a powerful method for multi-class classification problem. When combined with SVM method, it can remarkably increase the accuracy of TF classification using protein domains and functional sites as feature vectors. In addition, our work implied that ECOC algorithm may succeed in a broad range of applications in biological data mining.</p

Uncovering neuroinflammation-related modules and potential repurposing drugs for Alzheimer's disease through multi-omics data integrative analysis

BackgroundNeuroinflammation is one of the key factors leading to neuron death and synapse dysfunction in Alzheimer's disease (AD). Amyloid-β (Aβ) is thought to have an association with microglia activation and trigger neuroinflammation in AD. However, inflammation response in brain disorders is heterogenous, and thus, it is necessary to unveil the specific gene module of neuroinflammation caused by Aβ in AD, which might provide novel biomarkers for AD diagnosis and help understand the mechanism of the disease.MethodsTranscriptomic datasets of brain region tissues from AD patients and the corresponding normal tissues were first used to identify gene modules through the weighted gene co-expression network analysis (WGCNA) method. Then, key modules highly associated with Aβ accumulation and neuroinflammatory response were pinpointed by combining module expression score and functional information. Meanwhile, the relationship of the Aβ-associated module to the neuron and microglia was explored based on snRNA-seq data. Afterward, transcription factor (TF) enrichment and the SCENIC analysis were performed on the Aβ-associated module to discover the related upstream regulators, and then a PPI network proximity method was employed to repurpose the potential approved drugs for AD.ResultsA total of 16 co-expression modules were primarily obtained by the WGCNA method. Among them, the green module was significantly correlated with Aβ accumulation, and its function was mainly involved in neuroinflammation response and neuron death. Thus, the module was termed the amyloid-β induced neuroinflammation module (AIM). Moreover, the module was negatively correlated with neuron percentage and showed a close association with inflammatory microglia. Finally, based on the module, several important TFs were recognized as potential diagnostic biomarkers for AD, and then 20 possible drugs including ibrutinib and ponatinib were picked out for the disease.ConclusionIn this study, a specific gene module, termed AIM, was identified as a key sub-network of Aβ accumulation and neuroinflammation in AD. Moreover, the module was verified as having an association with neuron degeneration and inflammatory microglia transformation. Moreover, some promising TFs and potential repurposing drugs were presented for AD based on the module. The findings of the study shed new light on the mechanistic investigation of AD and might make benefits the treatment of the disease

Supplementing Vitamin E to the Ration of Beef Cattle Increased the Utilization Efficiency of Dietary Nitrogen

The objectives of the trial were to investigate the effects of supplementing vitamin E (VE) on nutrient digestion, nitrogen (N) retention and plasma parameters of beef cattle in feedlot. Four growing Simmental bulls, fed with a total mixed ration composed of corn silage and concentrate mixture as basal ration, were used as the experimental animals. Four levels of VE product, i.e. 0, 150, 300, 600 mg/head/d (equivalent to 0, 75, 150, 300 IU VE/head/d), were supplemented to the basal ration (VE content 38 IU/kg dry matter) in a 4×4 Latin square design as experimental treatments I, II, III and IV, respectively. Each experimental period lasted 15 days, of which the first 12 days were for pretreatment and the last 3 days for sampling. The results showed that supplementing VE did not affect the nutrient digestibility (p>0.05) whereas decreased the urinary N excretion (p0.05). It was concluded that supplementing VE up to 300 IU/head/d did not affect the nutrient digestibility whereas supplementing VE at 150 or 300 IU/head/d increased the N retention and the plasma concentrations of VE and TG (p<0.05) of beef cattle

iGepros: an integrated gene and protein annotation server for biological nature exploration

<p>Abstract</p> <p>Background</p> <p>In the post-genomic era, transcriptomics and proteomics provide important information to understand the genomes. With fast development of high-throughput technology, more and more transcriptomics and proteomics data are generated at an unprecedented rate. Therefore, requirement of software to annotate those omics data and explore their biological nature arises. In the past decade, some pioneer works were presented to address this issue, but limitations still exist. Fox example, some of these tools offer command line only, which is not suitable for those users with little or no experience in programming. Besides, some tools don’t support large scale gene and protein analysis.</p> <p>Results</p> <p>To overcome these limitations, an integrated gene and protein annotation server named iGepros has been developed. The server provides user-friendly interfaces and detailed on-line examples, so most researchers even those with little or no programming experience can use it smoothly. Moreover, the server provides many functionalities to compare transcriptomics and proteomics data. Especially, the server is constructed under a model-view-control framework, which makes it easy to incorporate more functions to the server in the future.</p> <p>Conclusions</p> <p>In this paper, we present a server with powerful capability not only for gene and protein functional annotation, but also for transcriptomics and proteomics data comparison. Researchers can survey biological characters behind gene and protein datasets and accelerate their investigation of transcriptome and proteome by applying the server. The server is publicly available at <url>http://www.biosino.org/iGepros/</url>.</p

Revealing missing human protein isoforms based on Ab initio prediction, RNA-seq and proteomics

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing. In this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.publishedVersio

Shifts of Hydrogen Metabolism From Methanogenesis to Propionate Production in Response to Replacement of Forage Fiber With Non-forage Fiber Sources in Diets in vitro

The rumen microbial complex adaptive mechanism invalidates various methane (CH4) mitigation strategies. Shifting the hydrogen flow toward alternative electron acceptors, such as propionate, was considered to be a meaningful mitigation strategy. A completely randomized design was applied in in vitro incubation to investigate the effects of replacing forage fiber with non-forage fiber sources (NFFS) in diets on methanogenesis, hydrogen metabolism, propionate production and the methanogenic and bacterial community. There are two treatments in the current study, CON (a basic total mixed ration) and TRT (a modified total mixed ration). The dietary treatments were achieved by partly replacing forage fiber with NFFS (wheat bran and soybean hull) to decrease forage neutral detergent fiber (fNDF) content from 24.0 to 15.8%, with the composition and inclusion rate of other dietary ingredients remaining the same in total mixed rations. The concentrations of CH4, hydrogen (H2) and volatile fatty acids were determined using a gas chromatograph. The archaeal and bacterial 16S rRNA genes were sequenced by Miseq high-throughput sequencing and used to reveal the relative abundance of methanogenic and bacterial communities. The results revealed that the concentration of propionate was significantly increased, while the concentration of acetate and the acetate to propionate ratio were not affected by treatments. Compared with CON, the production of H2 increased by 8.45% and the production of CH4 decreased by 14.06%. The relative abundance of Methanomassiliicoccus was significantly increased, but the relative abundance of Methanobrevibacter tended to decrease in TRT group. At the bacterial phylum level, the TRT group significantly decreased the relative abundance of Firmicutes and tended to increase the relative abundance of Bacteroidetes. The replacement of forage fiber with NFFS in diets can affect methanogenesis by shifting the hydrogen flow toward propionate, and part is directed to H2in vitro. The shift was achieved by a substitution of Firmicutes by Bacteroidetes, another substitution of Methanobrevibacter by Methanomassiliicoccus. Theoretical predictions of displacements of H2 metabolism from methanogenesis to propionate production was supported by the dietary intervention in vitro