Proteome evaluation of homolog abundance patterns in Arachis hypogaea cv. Tifrunner

Background Cultivated peanut (Arachis hypogaea, AABB genome), an allotetraploid from a cross between A. duranensis (AA genome) and A. ipaensis (BB genome), is an important oil and protein crop with released genome and RNA-seq sequence datasets. These datasets provide the molecular foundation for studying gene expression and evolutionary patterns. However, there are no reports on the proteomic data of A. hypogaea cv. Tifrunner, which limits understanding of its gene function and protein level evolution. Results This study sequenced the A. hypogaea cv. Tifrunner leaf and root proteome using the tandem mass tag technology. A total of 4803 abundant proteins were identified. The 364 differentially abundant proteins were estimated by comparing protein abundances between leaf and root proteomes. The differentially abundant proteins enriched the photosystem process. The number of biased abundant homeologs between the two sub-genomes A (87 homeologs in leaf and root) and B (69 and 68 homeologs in leaf and root, respectively) was not significantly different. However, homeologous proteins with biased abundances in different sub-genomes enriched different biological processes. In the leaf, homeologs biased to sub-genome A enriched biosynthetic and metabolic process, while homeologs biased to sub-genome B enriched iron ion homeostasis process. In the root, homeologs with biased abundance in sub-genome A enriched inorganic biosynthesis and metabolism process, while homeologs with biased abundance in sub-genome B enriched organic biosynthesis and metabolism process. Purifying selection mainly acted on paralogs and homeologs. The selective pressure values were negatively correlated with paralogous protein abundance. About 77.42% (24/31) homeologous and 80% (48/60) paralogous protein pairs had asymmetric abundance, and several protein pairs had conserved abundances in the leaf and root tissues. Conclusions This study sequenced the proteome of A. hypogaea cv. Tifrunner using the leaf and root tissues. Differentially abundant proteins were identified, and revealed functions. Paralog abundance divergence and homeolog bias abundance was elucidated. These results indicate that divergent abundance caused retention of homologs in A. hypogaea cv. Tifrunner.

Proteomic Changes in Sarcoplasmic and Myofibrillar Proteins Associated with Color Stability of Ovine Muscle during Post-Mortem Storage

The objective of this study was to investigate the proteomic characteristics for the sarcoplasmic and myofibrillar proteomes of M. longissimus lumborum (LL) and M. psoasmajor (PM) from Small-tailed Han Sheep. During post-mortem storage periods (1, 3, and 5 days), proteome analysis was applied to elucidate sarcoplasmic and myofibrillar protein changes in skeletal muscles with different color stability. Proteomic results revealed that the identified differentially abundant proteins were glycolytic enzymes, energy metabolism enzymes, chaperone proteins, and structural proteins. Through Pearson’s correlation analysis, a few of those identified proteins (Pyruvate kinase, Adenylate kinase isoenzyme 1, Creatine kinase M-type, and Carbonic anhydrase 3) were closely correlated to representative meat color parameters. Besides, bioinformatics analysis of differentially abundant proteins revealed that the proteins mainly participated in glycolysis and energy metabolism pathways. Some of these proteins may have the potential probability to be predictors of meat discoloration during post-mortem storage. Within the insight of proteomics, these results accumulated some basic theoretical understanding of the molecular mechanisms of meat discoloration.

Comparative proteomics analysis provides new insights into the haustorium development of Taxillus chinensis (DC.) Danser

Background Loranthus (Taxillus chinensis) is an important medicinal and parasitic plant that attacks other plants for living. To reveal the mechanisms of haustorium development, we employed an iTRAQ proteomics-based approach to identify differentially abundant proteins (DAPs) of fresh seeds (CK), baby (FB), and adult haustoria (FD). Results A total of 563 and 785 DAPs were successfully quantified in the early/later developmental stage, respectively. Pathway enrichment analysis indicated that the DAPs mainly associated with metabolic pathways, ribosome, phenylpropanoid biosynthesis and photosynthesis. In the meantime, DAPs associated with phytohormone signaling pathway changed markedly. Furthermore, we evaluated the contents change of phytohormone during the haustoria development. These results indicated that phytohormone is very important for haustorium development. qRT-PCR validation showed that the mRNA expression levels were consistent with the protein variation, suggesting that our result were reliable. Conclusions To the best of our knowledge, this is the first haustoria proteomes of loranthus, and our findings will improve our understanding of the molecular mechanism of haustoria development.

Comparative proteomics reveals Cryptosporidium parvum manipulation of the host cell molecular expression and immune response

Cryptosporidium is a life-threating protozoan parasite belonging to the phylum Apicomplexa, which mainly causes gastroenteritis in a variety of vertebrate hosts. Currently, there is a re-emergence of Cryptosporidium infection; however, no fully effective drug or vaccine is available to treat Cryptosporidiosis. In the present study, to better understand the detailed interaction between the host and Cryptosporidium parvum, a large-scale label-free proteomics study was conducted to characterize the changes to the proteome induced by C. parvum infection. Among 4406 proteins identified, 121 proteins were identified as differentially abundant (> 1.5-fold cutoff, P < 0.05) in C. parvum infected HCT-8 cells compared with uninfected cells. Among them, 67 proteins were upregulated, and 54 proteins were downregulated at 36 h post infection. Analysis of the differentially abundant proteins revealed an interferon-centered immune response of the host cells against C. parvum infection and extensive inhibition of metabolism-related enzymes in the host cells caused by infection. Several proteins were further verified using quantitative real-time reverse transcription polymerase chain reaction and western blotting. This systematic analysis of the proteomics of C. parvum-infected HCT-8 cells identified a wide range of functional proteins that participate in host anti-parasite immunity or act as potential targets during infection, providing new insights into the molecular mechanism of C. parvum infection.

Identification of Candidate Genes That Specifically Regulate Subcutaneous and Intramuscular Fat Deposition Using Transcriptomic and Proteomic Profiles in Dingyuan Pigs

Subcutaneous fat and intramuscular fat (IMF) deposition are closely related to meat production and pork quality. Dingyuan pig, as a native pig breed in China, low selection leads to obvious genetic and phenotypic differences in the population. Individuals with extreme fat content in the population are ideal models for studying the mechanism of fat deposition. In this study, we used RNA-Seq and tandem mass tags-based (TMT) proteomics to analyze the key pathways and genes that specifically regulate subcutaneous fat and IMF deposition in Dingyuan pigs. We identified 191 differentially expressed genes (DEGs) and 61 differentially abundant proteins (DAPs) in the high and low back fat thickness (HBF, LBF) groups, 85 DEGs and 12 DAPs were obtained in the high and low intramuscular fat (HIMF, LIMF) groups. The functional analysis showed that the DEGs and DAPs in the backfat groups were mainly involved in carbohydrates, amino acids, and fatty acids, whereas the IMF groups were involved in the insulin pathway, longevity, and some disease-related pathways. we found 33 candidate genes that might tissue-specifically lipids deposition for subcutaneous and intramuscular fat. Our research provides theoretical reference materials for the improvement of fat deposition traits of local pig breeds in my country.

Changes in Porcine Corpus Luteum Proteome Associated with Development, Maintenance, Regression, and Rescue during Estrous Cycle and Early Pregnancy

Corpus luteum (CL), a transitory gland, undergoes rapid growth in a limited time to produce progesterone (P4) followed by its regression. A complex molecular signaling is involved in controlling luteal P4 production. In the present study, 2D gel electrophoresis-based proteomics and in silico functional analysis were used to identify changes in key proteins and pathways in CL along the different stages of the estrous cycle as its development progresses from early (Day 3) to mid-luteal phase (Day 9), effective functioning (Day 12) followed by regression (Day 15) or, in the case of pregnancy, rescue of function (Day 15). A total of 273 proteins were identified by MALDI-MS/MS analysis that showed significant changes in abundances at different stages of CL development or regression and rescue. Functional annotation of differentially abundant proteins suggested enrichment of several important pathways and functions during CL development and function maintenance including cell survival, endocytosis, oxidative stress response, estradiol metabolism, and angiogenesis. On the other hand, differentially abundant proteins during CL regression were associated with decreased steroid synthesis and metabolism and increased apoptosis, necrosis, and infiltration of immune cells. Establishment of pregnancy rescues CL from regression by maintaining the expression of proteins that support steroidogenesis as pathways such as the super-pathway of cholesterol biosynthesis, RhoA signaling, and functions such as fatty acid metabolism and sterol transport were enriched in CL of pregnancy. In this study, some novel proteins were identified along CL development that advances our understanding of CL survival and steroidogenesis.

Biomarker Candidates for Tumors Identified from Deep-Profiled Plasma Stem Predominantly from the Low Abundant Area

The plasma proteome has the potential to enable a holistic analysis of the health state of an individual. However, plasma biomarker discovery is difficult due to its high dynamic range and variability. Here, we present a novel automated analytical approach for deep plasma profiling and applied it to a 180-sample cohort of human plasma from lung, breast, colorectal, pancreatic, and prostate cancer. Using a controlled quantitative experiment, we demonstrate a 257% increase in protein identification and a 263% increase in significantly differentially abundant proteins over neat plasma. In the cohort, we identified 2,732 proteins. Using machine learning, we discovered biomarker candidates such as STAT3 in colorectal cancer and developed models that classify the disease state. For pancreatic cancer, a separation by stage was achieved. Importantly, biomarker candidates came predominantly from the low abundance region, demonstrating the necessity to deeply profile because they would have been missed by shallow profiling.

In-Depth Benchmarking of DIA-type Proteomics Data Analysis Strategies Using a Large-Scale Benchmark Dataset Comprising Inter-Patient Heterogeneity

An overwhelming number of proteomics software tools and algorithms have been published for different steps of Data Independent Acquisition analysis of clinical samples. Nonetheless, there is still a lack of comprehensive benchmark studies evaluating which combinations of those isolated components perform best. Here, we used 92 lymph nodes from distinct patients to create a unique benchmark dataset representing real-world inter-individual heterogeneity. The publicly available dataset comprises 118 LC-MS/MS runs with > 12 million MS2 spectra and allowed us to objectively evaluate how well different combinations of spectral libraries, DIA software, sparsity reduction, normalization and statistical tests can detect differentially abundant proteins, while also taking sample size into account. Evaluation of 2 million data analysis workflows showed that a gas phase fractionation refined spectral library in combination with DIA-NN and Significance Analysis of Microarrays reliably detected differentially abundant proteins. Furthermore, DIA-NN and Spectronaut robustly avoided the false detection of truly absent proteins.

TMT-Based Quantitative Proteomic Analysis Identified Proteins and Signaling Pathways Involved in the Response to Xanthatin Treatment in Human HT-29 Colon Cancer Cells

Background: Xanthatin is a plant-derived bioactive sesquiterpene lactone from the Xanthium strumarium L., and it has been used as a traditional Chinese medicine. Recently, many studies have reported that xanthatin has anticancer activity. However, a comprehensive understanding of the mechanism underlying the antitumor effects of xanthatin is still lacking. Objective: To systematically and comprehensively identify the underlying mechanisms of xanthatin on cancer cells, quantitative proteomic techniques were performed. Methods: Xanthatin induced HT-29 colon cancer cells death was detected by lactate dehydrogenase (LDH) release cell death assay. Differentially abundant proteins in two groups (control groups and xanthatin treatment groups) of human HT-29 colon cancer cells were identified using tandem mass tag (TMT) quantitative proteomic techniques. All the significant differentially abundant proteins were generally characterized by performing hierarchical clustering, Gene Ontology (GO) enrichment analyses and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. We chose Western blot analysis to validate the candidate proteins in the proteomics results. Results: A total of 5637 proteins were identified, of which 397 significantly differentially abundant proteins in the groups were quantified. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, we found that p53-related signaling played an important role in xanthatin-treated HT-29 colon cancer cells. p53-upregulated modulator of apoptosis (Puma), Sestrin-2 and p14ARF, which were selected from among p53-related signaling proteins, were further validated, and the results were consistent with the tandem mass tag quantitative proteomic results. Conclusion: We first investigated the molecular mechanism underlying the effects of xanthatin treatment on HT-29 colon cancer cells using tandem mass tag quantitative proteomic methods and provided a global comprehensive understanding of the antitumor effects of xanthatin. However, it is necessary to further confirm the function of the differentially abundant proteins and the potentially associated signaling pathways.

Evaluation of Total Female and Male Aedes aegypti Proteomes Reveals Significant Predictive Protein–Protein Interactions, Functional Ontologies, and Differentially Abundant Proteins

Aedes aegypti is a significant vector for many tropical and subtropical flavivirus diseases. Only the female mosquito transmits pathogens, while the male plays a vital role in mating and species continuity. This study explored the total proteomes of females and males based on the physiological and genetic differences of female and male mosquitoes. Protein extracts from mosquitoes were analysed using LC–ESI–MS/MS for protein identification, protein interaction network analysis, functional ontology enrichment, and differential protein abundance analyses. Protein identification revealed 422 and 682 proteins exclusive to males and females, respectively, with 608 common proteins found in both sexes. The most significant PPIs (<1.0 × 10−16) were for common proteins, followed by proteins exclusive to females (<1.0 × 10−16) and males (1.58 × 10−12). Significant functional enrichments were observed in the biological process, molecular function, and cellular component for the male and female proteins. The abundance of the proteins differed, with one protein showing an increase (elongation factor 1 α, EF1α) and two showing reductions (actin family) in females versus males. Overall, the study verified the total proteomes differences between male and female Ae. aegypti based on protein identification and interactions, functional ontologies, and differentially abundant proteins. Some of the identified proteins merit further investigation to elucidate their roles in blocking viral transmission.