Protein Modification Process Research Articles

Detecting the differential genomic variants using cross-population phenotype-associated variant (XP-PAV) of the Landrace and Yorkshire pigs in Korea

ABSTRACT Although there have been many genome-wide association studies (GWAS) and selective sweep analyses to understand pig genomic regions related to growth performance, these methods considered only the gene effect and selection signal, respectively. In this study, we suggest the cross-population phenotype associated variant (XP-PAV) analysis as a novel method to determine the genomic variants with different effects between the two populations. XP-PAV analysis could reveal the differential genetic variants between the two populations by considering the gene effect and selection signal simultaneously. In this study, we used daily weight gain (DWG) and back fat thickness (BF) as phenotypes and the Landrace and Yorkshire populations were used for XP-PAV analysis. The main aim was to reveal the differential selection by considering the gene effect between Landrace and Yorkshire pigs. In the gene ontology analysis of XP-PAV results, differential selective genes in DWG analysis were involved in the regulation of interleukin-2 production and cell cycle G2/M transition. The protein modification and glycerophospholipid biosynthetic processes were the most enriched terms in the BF analysis. Therefore, we could identify genetic differences for immune and several metabolic pathways between Landrace and Yorkshire breeds using the XP-PAV analysis. In this study, we expect that XP-PAV analysis will play a role in determining useful selective variants with gene effects and provide a new interpretation of the genetic differences between the two populations.

A longitudinal study of gene expression in first-episode schizophrenia; exploring relapse mechanisms by co-expression analysis in peripheral blood

Little is known about the pathophysiological mechanisms of relapse in first-episode schizophrenia, which limits the study of potential biomarkers. To explore relapse mechanisms and identify potential biomarkers for relapse prediction, we analyzed gene expression in peripheral blood in a cohort of first-episode schizophrenia patients with less than 5 years of evolution who had been evaluated over a 3-year follow-up period. A total of 91 participants of the 2EPs project formed the sample for baseline gene expression analysis. Of these, 67 provided biological samples at follow-up (36 after 3 years and 31 at relapse). Gene expression was assessed using the Clariom S Human Array. Weighted gene co-expression network analysis was applied to identify modules of co-expressed genes and to analyze their preservation after 3 years of follow-up or at relapse. Among the 25 modules identified, one module was semi-conserved at relapse (DarkTurquoise) and was enriched with risk genes for schizophrenia, showing a dysregulation of the TCF4 gene network in the module. Two modules were semi-conserved both at relapse and after 3 years of follow-up (DarkRed and DarkGrey) and were found to be biologically associated with protein modification and protein location processes. Higher expression of DarkRed genes was associated with higher risk of suffering a relapse and early appearance of relapse (p = 0.045). Our findings suggest that a dysregulation of the TCF4 network could be an important step in the biological process that leads to relapse and suggest that genes related to the ubiquitin proteosome system could be potential biomarkers of relapse.

Physiological responses and transcriptomic changes reveal the mechanisms underlying adaptation of Stylosanthes guianensis to phosphorus deficiency

BackgroundPhosphorus (P) is an essential macronutrient for plant growth that participates in a series of biological processes. Thus, P deficiency limits crop growth and yield. Although Stylosanthes guianensis (stylo) is an important tropical legume that displays adaptation to low phosphate (Pi) availability, its adaptive mechanisms remain largely unknown.ResultsIn this study, differences in low-P stress tolerance were investigated using two stylo cultivars (‘RY2’ and ‘RY5’) that were grown in hydroponics. Results showed that cultivar RY2 was better adapted to Pi starvation than RY5, as reflected by lower values of relative decrease rates of growth parameters than RY5 at low-P stress, especially for the reduction of shoot and root dry weight. Furthermore, RY2 exhibited higher P acquisition efficiency than RY5 under the same P treatment, although P utilization efficiency was similar between the two cultivars. In addition, better root growth performance and higher leaf and root APase activities were observed with RY2 compared to RY5. Subsequent RNA-seq analysis revealed 8,348 genes that were differentially expressed under P deficient and sufficient conditions in RY2 roots, with many Pi starvation regulated genes associated with P metabolic process, protein modification process, transport and other metabolic processes. A group of differentially expressed genes (DEGs) involved in Pi uptake and Pi homeostasis were identified, such as genes encoding Pi transporter (PT), purple acid phosphatase (PAP), and multidrug and toxin extrusion (MATE). Furthermore, a variety of genes related to transcription factors and regulators involved in Pi signaling, including genes belonging to the PHOSPHATE STARVATION RESPONSE 1-like (PHR1), WRKY and the SYG1/PHO81/XPR1 (SPX) domain, were also regulated by P deficiency in stylo roots.ConclusionsThis study reveals the possible mechanisms underlying the adaptation of stylo to P deficiency. The low-P tolerance in stylo is probably manifested through regulation of root growth, Pi acquisition and cellular Pi homeostasis as well as Pi signaling pathway. The identified genes involved in low-P tolerance can be potentially used to design the breeding strategy for developing P-efficient stylo cultivars to grow on acid soils in the tropics.

Genome-Wide Identification and Characterization of Calcium Metabolism Related Gene Families in Arabidopsis thaliana and Their Regulation by Bacillus amyloliquefaciens Under High Calcium Stress.

Several gene families involved in calcium signaling have been detected in plants, including calmodulin (CaM), calcium dependent protein kinases (CDPK), calcineurin B-like (CBL) and cyclic nucleotide-gated channels (CNGCs). In our previous study, we demonstrated that Bacillus amyloliquefaciens LZ04 (B. amyloliquefaciens LZ04) regulate genes involved in calcium stress in Arabidopsis thaliana (A. thaliana). Here, we aimed to explore the potential involvement of calcium-related gene families in the response of A. thaliana to calcium stress and the potential regulatory effects of B. amyloliquefaciens LZ04 on these genes. The structure, duplication, synteny, and expression profiles of 102 genes in calcium-related gene families in A. thaliana were investigated. Hidden Markov Models (HMMs) and BLASTP were used to predict candidate genes and conserved domains of the candidate genes were confirmed in SMART and NCBI CDD databases. Gene duplications and synteny were uncovered by BLASTP and phylogenetic analysis. The transcriptome expression profiles of candidate genes were investigated by strand-specific sequencing. Cluster analysis was used to find the expression profiles of calcium-related genes families under different treatment conditions. A total of 102 genes in calcium-related gene families were detected in A. thaliana genome, including 34 CDPK genes, 20 CNGC genes, 18 CIPK genes, 22 IQD genes, and 10 CBP genes. Additionally, of the 102 genes, 33 duplications (32.35%) and 26 gene pairs including 48 genes (47.06%) were detected. Treatment with B. amyloliquefaciens LZ04 enhanced the resistance of A. thaliana under high calcium stress by regulating some of the genes in the calcium-related gene families. Functional enrichment analysis revealed that the genes clustered in the 42nd expression profile which may be B. amyloliquefaciens-responsive genes under calcium stress were enriched in protein phosphorylation and protein modification process. Transcriptome data was validated by RT-PCR and the results generally corroborated the transcriptome sequencing results. These results may be useful for agricultural improvement in high calcium stress regions.

Deep learning survival model on transcriptomes level in patients with non-small cell lung cancer.

e20518 Background: Non-small cell lung cancer (NSCLC) is associated with poor prognosis. Global gene expression profiling with overall survival (OS) may help improving individualize survival. In this study, we identify biological important gene clusters and studied their prognostic abilities for OS by deep learning method. Methods: Using GEO genomics data repository, we identified 196 NSCLC patients (trainset: GSE37745) and 181 NSCLC patients (testset: GSE50081) with clinical information and long-term follow-up. In both cohorts, expression profiling was performed on RNA from tumor tissues using Affymetrix microarrays HG-U133-Plus2; and normalized using the Robust Multiarray Averaging (RMA). We established deep learning survival models through neural network extension of the Cox regression model for predicting OS, which were developed by 5-folds cross-validation in GSE37745 and independently validated in GSE50081. Significant RNA-seq and clinical variables were multiple inputs. Concordance index (CI) was evaluated and compared with multivariable Cox regression. Then we conducted Uniform Manifold Approximation and Projection (UMAP) using weights in hidden layer of the model for clustering the important RNA-seq and then performed enrichment analysis though GO/KEGG for revealing biological progresses. Results: Total 1039 RNA-seq levels were found significant with OS ( P < 0.05) by Cox proportional hazard model adjusted by clinical variables (age, gender, cancer stage, histology) in trainset. The deep learning survival model with 20 most significant RNA-seq and clinical variables had best average performances as CI = 0.74±0.04 in trainset (GSE37745) and CI = 0.68±0.06 in testset (GSE50081) in 10 iterations, better than multivariable Cox regression ( P < 0.05). The deep learning survival model with all significant RNA-seq were also established and the weights in the hidden layer were clustered by UMAP into 5 positive and 5 negative clusters. The clusters were enriched, such as in positive clusters, negative regulation of RNA metabolic process, negative regulation of RNA biosynthetic process and positive regulation of protein modification process were top three significant biological processes for shorten survival; while in negative clusters, DNA metabolic process, positive regulation of phosphate metabolic process and positive regulation of RNA metabolic process were the top three for prolonged survival. Conclusions: In this study, the deep learning survival algorithm was established for survival prediction based on a transcriptome level in patients with NSCLC. Given the models’ robustness and better performances, our study would be useful at predicting and applying more biological information for survival.

82 Methyl Donor Supplementation Alters Cytosine Methylation and Biological Processes of Cells Cultured in Divergent Glucose Media Reflecting Improvements in Mitochondrial Respiration and Cell Growth Rate

Abstract We hypothesized that supplementation of one-carbon metabolites (OCM: methionine, folate, choline, and vitamin B12) to bovine embryonic tracheal fibroblasts in divergent glucose media would alter cytosine methylation, and alterations in cytosine methylation will reflect biological processes matching previously improved mitochondrial respiration, cell proliferation, and cell growth rate data. Cells were cultured with 1g/L glucose (Low) or 4.5g/L glucose (High). Control medium (CON) contained basal concentrations of folate (0.001g/L), choline (0.001g/L), vitamin B12 (4µg/L), and methionine (0.015g/L). The OCM were supplemented at 2.5 and 5 times (2.5X and 5X, respectively) the CON media, except methionine was limited to 2X across all supplemented treatments. Cells were passaged three times in their treatment media before DNA extraction. Reduced representation bisulfite sequencing was adopted to analyze and compare the genomic methylation patterns within and across treatments using edgeR. Biological processes (BP) were retrieved based on the nearest genes of differentially methylated cytosines (P < 0.01) for each comparison between treatments. In both Low and High treatments, greater OCM increased the proportion of hypomethylated vs. hypermethylated cytosines. Functional analyses pointed out positive regulation of BP related to energy metabolism, except for the contrasts within the High group. Among the BP, we can highlight positive regulation of: GTPase activity, catalytic activity, molecular function, protein modification processes, phosphorylation, protein phosphorylation, cellular protein metabolic processes, MAPK cascade, and metabolic processes. These data support previously reported results from this experiment that showed increased mitochondrial respiration, cell proliferation, and growth rates with increasing OCM levels. We interpret these data to imply that when energy and OCM requirements are met for growth and basal methylation levels, DNA methylation levels decrease which may allow for greater transcription. Thus, OCM can be utilized for other functions such as polyamine synthesis, nucleotide synthesis, energetic metabolites, and phosphatidylcholine synthesis. USDA is an equal opportunity provider and employer.

DNA methylation-mediated modulation of rapid desiccation tolerance acquisition and dehydration stress memory in the resurrection plant Boea hygrometrica.

Pre-exposure of plants to various abiotic conditions confers improved tolerance to subsequent stress. Mild drought acclimation induces acquired rapid desiccation tolerance (RDT) in the resurrection plant Boea hygrometrica, but the mechanisms underlying the priming and memory processes remain unclear. In this study, we demonstrated that drought acclimation-induced RDT can be maintained for at least four weeks but was completely erased after 18 weeks based on a combination of the phenotypic and physiological parameters. Global transcriptome analysis identified several RDT-specific rapid dehydration-responsive genes related to cytokinin and phospholipid biosynthesis, nitrogen and carbon metabolism, and epidermal morphogenesis, most of which were pre-induced by drought acclimation. Comparison of whole-genome DNA methylation revealed dehydration stress-responsive hypomethylation in the CG, CHG, and CHH contexts and acclimation-induced hypermethylation in the CHH context of the B. hygrometrica genome, consistent with the transcriptional changes in methylation pathway genes. As expected, the global promoter and gene body methylation levels were negatively correlated with gene expression levels in both acclimated and dehydrated plants but showed no association with transcriptional divergence during the procedure. Nevertheless, the promoter methylation variations in the CG and CHG contexts were significantly associated with the differential expression of genes required for fundamental genetic processes of DNA conformation, RNA splicing, translation, and post-translational protein modification during acclimation, growth, and rapid dehydration stress response. It was also associated with the dehydration stress-induced upregulation of memory genes, including pre-mRNA-splicing factor 38A, vacuolar amino acid transporter 1-like, and UDP-sugar pyrophosphorylase, which may contribute directly or indirectly to the improvement of dehydration tolerance in B. hygrometrica plants. Altogether, our findings demonstrate the potential implications of DNA methylation in dehydration stress memory and, therefore, provide a molecular basis for enhanced dehydration tolerance in plants induced by drought acclimation.

Transcriptome Profile Reveals Drought-Induced Genes Preferentially Expressed in Response to Water Deficit in Cultivated Peanut (Arachis hypogaea L.).

Cultivated peanut (Arachis hypogaea) is one of the most widely grown food legumes in the world, being valued for its high protein and unsaturated oil contents. Drought stress is one of the major constraints that limit peanut production. This study’s objective was to identify the drought-responsive genes preferentially expressed under drought stress in different peanut genotypes. To accomplish this, four genotypes (drought tolerant: C76-16 and 587; drought susceptible: Tifrunner and 506) subjected to drought stress in a rainout shelter experiment were examined. Transcriptome sequencing analysis identified that all four genotypes shared a total of 2,457 differentially expressed genes (DEGs). A total of 139 enriched gene ontology terms consisting of 86 biological processes and 53 molecular functions, with defense response, reproductive process, and signaling pathways, were significantly enriched in the common DEGs. In addition, 3,576 DEGs were identified only in drought-tolerant lines in which a total of 74 gene ontology terms were identified, including 55 biological processes and 19 molecular functions, mainly related to protein modification process, pollination, and metabolic process. These terms were also found in shared genes in four genotypes, indicating that tolerant lines adjusted more related genes to respond to drought. Forty-three significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways were also identified, and the most enriched pathways were those processes involved in metabolic pathways, biosynthesis of secondary metabolites, plant circadian rhythm, phenylpropanoid biosynthesis, and starch and sucrose metabolism. This research expands our current understanding of the mechanisms that facilitate peanut drought tolerance and shed light on breeding advanced peanut lines to combat drought stress.

Identification of a MicroRNA Signature Associated With Lymph Node Metastasis in Endometrial Endometrioid Cancer.

BackgroundLymph node metastasis (LNM) is an important prognostic factor in endometrial cancer. Anomalous microRNAs (miRNAs) are associated with cell functions and are becoming a powerful tool to characterize malignant transformation and metastasis. The aim of this study was to construct a miRNA signature to predict LNM in endometrial endometrioid carcinoma (EEC).MethodCandidate target miRNAs related to LNM in EEC were screened by three methods including differentially expressed miRNAs (DEmiRs), weighted gene co-expression network analysis (WGCNA), and decision tree algorithms. Samples were randomly divided into the training and validation cohorts. A miRNA signature was built using a logistic regression model and was evaluated by the area under the curve (AUC) of receiver operating characteristic curve (ROC) and decision curve analysis (DCA). We also conducted pathway enrichment analysis and miRNA–gene regulatory network to look for potential genes and pathways engaged in LNM progression. Survival analysis was performed, and the miRNAs were tested whether they expressed differently in another independent GEO database.ResultThirty-one candidate miRNAs were screened and a final 15-miRNA signature was constructed by logistic regression. The model showed good calibration in the training and validation cohorts, with AUC of 0.824 (95% CI, 0.739–0.912) and 0.821 (95% CI, 0.691–0.925), respectively. The DCA demonstrated the miRNA signature was clinically useful. Hub miRNAs in signature seemed to contribute to EEC progression via mitotic cell cycle, cellular protein modification process, and molecular function. MiR-34c was statistically significant in survival that a higher expression of miR-34c indicated a higher survival time. MiR-34c-3p, miR-34c-5p, and miR-34b-5p were expressed differentially in GSE75968.ConclusionThe miRNA signature could work as a noninvasive method to detect LNM in EEC with a high prediction accuracy. In addition, miR-34c cluster may be a key biomarker referring LNM in endometrial cancer.

Transcriptome Analysis of lncRNA-mRNA Interactions in Chronic Atrophic Gastritis.

The aim of this study was to identify prognosis-related differentially expressed lncRNAs and mRNAs in chronic atrophic gastritis (CAG). By analysis of high-throughput whole-transcriptome sequencing data, the levels of lncRNAs and mRNAs between CAG and chronic non-atrophic gastritis were compared pairwisely. In total, 97,282 lncRNA transcripts and 20,307 mRNA transcripts were acquired, including 50 upregulated and 66 downregulated lncRNAs and 377 upregulated and 763 downregulated mRNAs in CAG (p < 0.05, fold change ≥ 2). Moreover, the interactions of the differentially expressed genes in CAG were investigated by gene ontology enrichment analysis, showing that the enriched genes are involved in many biological processes, such as MAP kinase activity, heat generation, and protein modification processes. Through the construction of co-expression networks of the differentially expressed genes in CAG, three critical lncRNAs nodes were identified as potential key factors in CAG. Eight mRNAs common in both the co-expression network and the protein–protein interaction network were selected via Venn analysis, including DGKA, EIF6, HKDC1, DHRS11, 1, KRT15, TESPA1, and CDHR2. Finally, the expression levels of five differentially expressed lncRNAs in CAG were confirmed by quantitative real-time polymerase chain reaction. In conclusion, this study presents novel promising biomarkers for the diagnosis of CAG.

Large-Scale Phosphoproteomic Study of Arabidopsis Membrane Proteins Reveals Early Signaling Events in Response to Cold.

Cold stress is one of the major factors limiting global crop production. For survival at low temperatures, plants need to sense temperature changes in the surrounding environment. How plants sense and respond to the earliest drop in temperature is still not clearly understood. The plasma membrane and its adjacent extracellular and cytoplasmic sites are the first checkpoints for sensing temperature changes and the subsequent events, such as signal generation and solute transport. To understand how plants respond to early cold exposure, we used a mass spectrometry-based phosphoproteomic method to study the temporal changes in protein phosphorylation events in Arabidopsis membranes during 5 to 60 min of cold exposure. The results revealed that brief cold exposures led to rapid phosphorylation changes in the proteins involved in cellular ion homeostasis, solute and protein transport, cytoskeleton organization, vesical trafficking, protein modification, and signal transduction processes. The phosphorylation motif and kinase–substrate network analysis also revealed that multiple protein kinases, including RLKs, MAPKs, CDPKs, and their substrates, could be involved in early cold signaling. Taken together, our results provide a first look at the cold-responsive phosphoproteome changes of Arabidopsis membrane proteins that can be a significant resource to understand how plants respond to an early temperature drop.

Co‑expression network analysis identified specific miRNAs and genes in association with slow‑transit constipation.

The pathogenesis of slow-transit constipation (STC) remains largely unclear, with the roles of microRNAs (miRs/miRNAs) yet to be determined. Co-expression network analysis of miRNAs in STC is crucial to elucidating potential underlying mechanisms. Weighted gene correlation network analysis was performed in the miRNA expression profile of STC (GSE57969). The key miRNA target genes were further functionally enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). A Protein-Protein Interaction (PPI) network was constructed, with a total of 12 color-clustered modules determined. Seven key miRNAs were established, including five miRNAs from the turquoise module (hsa-miR-20b, hsa-miR-128, hsa-miR-129-3p, hsa-miR-30b and hsa-miR-340), one miRNA from the blue module (hsa-miR-619) and one from the black module (hsa-miR-486-3p). A total of 2,077 key miRNA target genes were predicted. GO analysis revealed that the ‘protein modification process’ and ‘cellular protein modification process’ were the most significantly enriched processes in the ‘Biological Processes’ category, whereas the ‘nucleoplasm’ in ‘Cellular Components’ and ‘enzyme binding’ in ‘Molecular Functions’ were the most significantly enriched processes. The ‘cAMP signalling pathway’ was the top KEGG pathway. The hub genes identified from the PPI network included calmodulin (CALM)2, CALM1, histone deacetylase (HDAC)3, glycogen synthase kinase 3 β, HDAC9, heat-shock protein family A member 8, G-protein subunit γ (GNG)13, HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1, GNG10 and GNG7. This bioinformatics analysis demonstrated co-expressed miRNA networks with insightful genes and pathways associated with STC.

Zinc enhances carnosine inhibitory effect against structural and functional age-related protein alterations in an albumin glycoxidation model

Age-related complications including protein alterations seen in diabetes and Alzheimer's disease are a major issue due to their accumulation and deleterious effects. This report aims to investigate the effect of zinc supplementation on the anti-glycoxidation activity of carnosine on the in vitro model of albumin-based protein modification. Besides, the therapeutic effect of this combination was tested through the addition of the molecules in tandem (co-treatment) or post initiation (post-treatment) of the protein modification process. Glycation was induced via the addition of glucose to which carnosine (5mM) alone or with various zinc concentrations (125, 250, and 500μM) were added either at 0h or 24h post-glycation induction. On the other hand, protein oxidation was induced using chloramine T (20mM) and treated in the same way with carnosine and zinc. The different markers of glycation (advanced glycation end products (AGEs), dityrosine, and beta-sheet formation (aggregation)) and oxidation (AOPP, advanced oxidation protein products) were estimated via fluorescence and colorimetric assays. Zinc addition induced a significant enhancement of carnosine activity by reducing albumin modification that outperformed aminoguanidine both in the co- and post-treatment protocols. Zinc demonstrated a supplementary effect in combination with carnosine highlighting its potential in the protection against age-related protein modifications processes such as the ones found in diabetes.

Significant upregulation of signaling and pro-inflammatory markers indicate adaptation for tolerance in bovine trypanosomosis

Abstract The initial immune response on exposure to trypanosomosis is a significant factor mitigating disease tolerance or susceptibility in cattle. CD14 is a signaling receptor involved in the activation of the TLR signaling pathway, contributing to the production of cytokines, including tumor necrosis factor-α (TNF-α). We had shown that CD14 expression in trypanotolerant cattle is an adaptation footprint, not found in susceptible animals. To further our analysis in delineating the role of TLR-4 and TNF-α genes in disease tolerance or susceptibility, we examined whole transcriptome and interactome of the two genes by elucidating their expression profiles in bovine tissues (liver, lungs, heart and kidney). Our analyses demonstrate a significant (p&amp;lt; 0.05) upregulation of TLR-4 and TNF-α in trypanotolerant cattle but not others. The upregulation of these genes in tolerant animals reflects a complete activation of the innate immune pathway, thereby hampering disease establishment, which is absent in the susceptible animals. This is contrary to reports in human studies, where the expression of these genes lead to disease chronicity, rather than tolerance. This indicates an evolutionary differentiation between cattle and human during speciation. Furthermore, we catalogued microRNA expression between disease groups via network analysis and identified 13 candidate microRNAs targeting CD14, TLR-4 and TNF-α, amongst others, which GO analysis reveal are involved in gene silencing, cellular protein modification process, etc. We conclude that the upregulation of these markers and the significant co-regulatory interactome is indicative of adaptation footprint in tolerant animal, helpful for bovine immune response against trypanosomiasis.

Comparative analysis of excretory–secretory products of muscle larvae of three isolates of Trichinella pseudospiralis by the iTRAQ method

Trichinella pseudospiralis is a non-encapsulated intracellular parasitic nematode that can possess a strong ability to modulate the host immune response. Here, we compared the differentially expressed proteins of excretory-secretory (ES) products in three isolates of T. pseudospiralis muscle larvae (ML) [from Russia (RUS), United States of America (USA) and Australia (AUS)] using isobaric tags for relative and absolute quantification (iTRAQ)-based technology. A total of 2591 nonredundant proteins were identified, of which 65 (146), 72 (98) and 43 (103) significantly upregulated (downregulated) differentially expressed proteins were detected among pairwise comparisons (T4RUS vs T4USA, T4AUS vs T4USA and T4RUS vs T4AUS). In addition, GO annotation, KEGG and STRING analyses were carried out on the screened differentially altered proteins. The main biological processes involved included carbohydrate metabolic processes, DNA metabolic processes, cellular protein modification processes and homeostatic processes. The majority of KEGG pathways were found to be related to the metabolic pathways, lysosome pathway and protein processing in endoplasmic reticulum. Moreover, all ES protein expression levels involved in the lysosome pathway were significantly higher in the T4USA isolate than in the other two isolates. We also found differences in the expression of some important immunoregulatory proteins, such as protein disulfide-isomerase, thioredoxin protein and deoxyribonuclease-2-alpha, between different isolates of T. pseudospiralis ML. Flow cytometry was used to detect the increase in the CD4+/CD8 + T-cell ratio in pig peripheral blood and to verify the effect of T. pseudospiralis on the Th1/Th2 polarization of the host. Quantitative real-time PCR analysis also confirmed that the changes in the transcriptional level of genes were consistent with those at the proteomic level. These findings reveal the possible role of significantly differentially expressed proteins in ES products of the different isolates of T. pseudospiralis in antagonizing and participating in the regulation of the host immune response and maintaining a stable growth environment.

Advances in the role of HECT-type E3 ubiquitin ligases in tumors

The occurrence and development of tumors is a complex process with multiple factors and multiple steps. Ubiquitination refers to a multi-step cascade of protein modification processes including ubiquitin, ubiquitin-activating enzyme, ubiquitin-binding enzyme, ubiquitin ligase and proteasome, which is important for maintaining eukaryotic homeostasis. mechanism. The E3 ubiquitin ligases family is an important component of the ubiquitin-proteasome system. This family includes many proteins that catalyze the ubiquitination of various protein substrates and promote their degradation by the proteasome system. Up to date, E3 ubiquitin ligases has played an important role in a variety of tumor cell biology processes, including cell proliferation, apoptosis and cycle regulation. HECT-type E3 ubiquitin ligases, one of the earliest studies of E3 ubiquitin ligases, is involved in the ubiquitination of transcriptional regulation of protein translation. This article reviews the recent research progress of HECT-type E3 ubiquitin ligases and its role in tumors. Key words: Ubiquitin-protein ligases; Neoplasms; Therapeutic uses; HECT-type E3 ubiquitin ligases

Comparative genomics of the aconidial Aspergillus niger strain LDM3 predicts genes associated with its high protein secretion capacity

Aspergillus niger is widely used as a cell factory for homologous and heterologous protein production. As previous studies reported that reduced sporulation favors protein secretion in A. niger, in this study, we conducted a comparative genomic analysis of the non-sporulating industrially exploited A. niger strain LDM3 in China and the referenceprotein secretion strain CBS 513.88 to predict the key genes that might define the genetic basis of LDM3's high protein-producing potential in silico. After sequencing using a hybrid approach combining Illumina and PacBio sequencing platforms, a high-quality genome sequence of LDM3 was obtained which harbors 11,209 open reading frames (ORFs). LDM3 exhibits large chromosomal rearrangements in comparison to CBS 513.88. An alignment of the two genome sequences revealed that the majority of the 457 ORFs uniquely present in LDM3 possessed predicted functions in redox pathways, protein transport, and protein modification processes. In addition, bioinformatic analyses revealed the presence of 656 ORFs in LDM3 with non-synonymous mutations encoding for proteins related to protein translation, protein modification, protein secretion, metabolism, and energy production. We studied the impact of two of these on protein production in the established lab strain N402. Both tupA and prpA genes were selected because available literature suggested their involvement in asexual sporulation of A. niger. Our co-expression network analysis supportively predicted the role of tupA in protein secretion and the role of prpA in energy generation, respectively. By knockout experiments, we showed that the ΔtupA mutant displayed reduced sporulation (35%) accompanied by higher total protein secretion (65%) compared to its parental strain. Such an effect was, however, not observed in the ΔprpA mutant.

Genome-wide discovery of DNA variants in cucumber somaclonal lines

The emergence of somaclonal variability in in vitro cultures is undesirable during micropropagation, but this phenomenon may be a source of genetic variability sought by breeders. The main factors that affect the appearance of variability are known, but the exact mechanism has not yet been determined. In this paper, we used next-generation sequencing and comparative genomics to study changes in the genomes of cucumber lines resulting from in vitro regeneration and somaclonal mutation in comparison to a reference, the highly inbred B10 line. The total number of obtained polymorphisms differed between the three somaclonal lines S1, S2 and S3, with 8369, 7591 and 44510, respectively. Polymorphisms occurred most frequently in non-coding regions and were mainly SNPs. High-impact changes accounted for 1%–3% of all polymorphisms and most often caused an open reading frame shift. Functional analysis of genes affected by high impact variants showed that they were related to transport, biosynthetic processes, nucleotide-containing compounds and cellular protein modification processes. The obtained results indicated significant factors affecting somaclonal variability and the appearance of changes in the genome, and demonstrated a lack of dependence between phenotype and the number of genomic polymorphisms.

Systematic prediction of the biological functions of TAS2R10 using positive co-expression analysis.

Type 2 taste receptor 10 (TAS2R10), belonging to the TAS2R family of bitter receptors, is widely expressed in extra-oral tissues. However, its biological roles beyond bitterness sensing in the tongue have remained largely elusive. The present study aimed to perform a positive co-expression analysis using 60,000 Affymetrix expression arrays and 5,000 The Cancer Genome Atlas datasets to uncover such roles. Based on the functional enrichment analysis, it was indicated that in the Gene Ontology (GO) category biological process, TAS2R10 was mostly involved in ‘cellular protein metabolic process’, ‘protein modification process’, ‘cellular protein modification process’ and ‘cellular component assembly’. In the GO category cellular component, the co-expressed genes were accumulated in ‘Spt-Ada-Gcn5 acetyltransferase (SAGA)-type complex’ and ‘SAGA complex’, and in the category molecular function, they were concentrated in ‘hexosaminidase activity’, ‘cytoskeletal adaptor activity’, ‘cyclin binding’ and ‘β-N-acetylhexosaminidase activity’. Of note, it was indicated that TAS2R10 may be involved in ‘ubiquitin-mediated proteolysis’, which may provide a starting point to fully investigate the detailed functions of TAS2R10 in the future. TAS2R10 was also indicated to be associated with human diseases, i.e. ‘Salmonella infection’. Overall, the present study was the first to perform a comprehensive bioinformatics analysis of the functions of TAS2R10 and provide insight regarding the notion that this gene may have crucial roles beyond bitterness sensing.

A Proteomic Network Approach across the Kidney Stone Disease Reveals Endoplasmic Reticulum Stress and Crystal-Cell Interaction in the Kidney.

Crystal-cell interactions are a vital step toward kidney stone formation. However, its mechanisms remained unclear. Here, a protein-protein interaction (PPI) network analysis of a kidney stone revealed that the proteins were enriched in a posttranslational protein modification process in the endoplasmic reticulum (ER). The in vitro study showed that the markers of ER stress, including Bip and CHOP, were upregulated, PERK and ATF6 were activated, and XBP-1 mRNA was spliced. An ER stress-specific protein, caspase-12, was activated in the apoptotic cells induced by calcium oxalate monohydrate (COM) crystals. The treatment with tunicamycin, an ER stress inducer, promoted the crystal-cell adhesion assayed by atomic absorption, reduced cell viability assayed by MTT, and downregulated the expression of proteins involved in the crystal formations. The treatment with salubrinal, an ER stress inhibitor, reversed the above effects for both tunicamycin and COM crystals. The aforementioned main observations were supported by in vivo study. These data demonstrated that ER stress was an essentially biological process of crystal-cell interactions. Our findings suggest that blocking ER stress may become a potential approach to preventing a kidney stone.