scholarly journals Large Scale Profiling of Protein Isoforms Using Label-Free Quantitative Proteomics Revealed the Regulation of Nonsense-Mediated Decay in Moso Bamboo (Phyllostachys edulis)

Cells ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 744 ◽  
Author(s):  
Xiaolan Yu ◽  
Yongsheng Wang ◽  
Markus V. Kohnen ◽  
Mingxin Piao ◽  
Min Tu ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Gene Annotation ◽  
Function Analysis ◽  
Moso Bamboo ◽  
Protein Isoforms ◽  
Label Free ◽  
Total Proteins ◽  
Protein Coding

Moso bamboo is an important forest species with a variety of ecological, economic, and cultural values. However, the gene annotation information of moso bamboo is only based on the transcriptome sequencing, lacking the evidence of proteome. The lignification and fiber in moso bamboo leads to a difficulty in the extraction of protein using conventional methods, which seriously hinders research on the proteomics of moso bamboo. The purpose of this study is to establish efficient methods for extracting the total proteins from moso bamboo for following mass spectrometry-based quantitative proteome identification. Here, we have successfully established a set of efficient methods for extracting total proteins of moso bamboo followed by mass spectrometry-based label-free quantitative proteome identification, which further improved the protein annotation of moso bamboo genes. In this study, 10,376 predicted coding genes were confirmed by quantitative proteomics, accounting for 35.8% of all annotated protein-coding genes. Proteome analysis also revealed the protein-coding potential of 1015 predicted long noncoding RNA (lncRNA), accounting for 51.03% of annotated lncRNAs. Thus, mass spectrometry-based proteomics provides a reliable method for gene annotation. Especially, quantitative proteomics revealed the translation patterns of proteins in moso bamboo. In addition, the 3284 transcript isoforms from 2663 genes identified by Pacific BioSciences (PacBio) single-molecule real-time long-read isoform sequencing (Iso-Seq) was confirmed on the protein level by mass spectrometry. Furthermore, domain analysis of mass spectrometry-identified proteins encoded in the same genomic locus revealed variations in domain composition pointing towards a functional diversification of protein isoform. Finally, we found that part transcripts targeted by nonsense-mediated mRNA decay (NMD) could also be translated into proteins. In summary, proteomic analysis in this study improves the proteomics-assisted genome annotation of moso bamboo and is valuable to the large-scale research of functional genomics in moso bamboo. In summary, this study provided a theoretical basis and technical support for directional gene function analysis at the proteomics level in moso bamboo.

Development of Algorithms for Mass Spectrometry-based Label-free Quantitative Proteomics*

2011 ◽  
Vol 38 (6) ◽  
pp. 506-518 ◽  
Author(s):  
Wei ZHANG ◽  
Ji-Yang ZHANG ◽  
Hui LIU ◽  
Han-Chang SUN ◽  
Chang-Ming XU ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Label Free

scholarly journals Loss of critical developmental and human disease-causing genes in 58 mammals

2019 ◽  
Author(s):  
Yatish Turakhia ◽  
Heidi I. Chen ◽  
Amir Marcovitz ◽  
Gill Bejerano
Keyword(s):  
Evolutionary Biology ◽  
Large Scale ◽  
Gene Annotation ◽  
Synonymous Substitution ◽  
Specific Gene ◽  
High Confidence ◽  
Protein Coding ◽  
Congenital Diseases ◽  
Manual Curation ◽  
Human Genes

Gene losses provide an insightful route for studying the morphological and physiological adaptations of species, but their discovery is challenging. Existing genome annotation tools and protein databases focus on annotating intact genes and do not attempt to distinguish nonfunctional genes from genes missing annotation due to sequencing and assembly artifacts. Previous attempts to annotate gene losses have required significant manual curation, which hampers their scalability for the ever-increasing deluge of newly sequenced genomes. Using extreme sequence erosion (deletion and non-synonymous substitution) as an unambiguous signature of loss, we developed an automated approach for detecting high-confidence protein-coding gene loss events across a species tree. Our approach relies solely on gene annotation in a single reference genome, raw assemblies for the remaining species to analyze, and the associated phylogenetic tree for all organisms involved. Using the hg38 human assembly as a reference, we discovered over 500 unique human genes affected by such high-confidence erosion events in different clades across 58 mammals. While most of these events likely have benign consequences, we also found dozens of clade-specific gene losses that result in early lethality in outgroup mammals or are associated with severe congenital diseases in humans. Our discoveries yield intriguing potential for translational medical genetics and for evolutionary biology, and our approach is readily applicable to large-scale genome sequencing efforts across the tree of life.

scholarly journals NAguideR: performing and prioritizing missing value imputations for consistent bottom-up proteomic analyses

2020 ◽  
Vol 48 (14) ◽  
pp. e83-e83 ◽  
Author(s):  
Shisheng Wang ◽  
Wenxue Li ◽  
Liqiang Hu ◽  
Jingqiu Cheng ◽  
Hao Yang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Missing Values ◽  
Protein Complexes ◽  
Label Free ◽  
Missing Value ◽  
Imputation Methods ◽  
Data Independent Acquisition ◽  
Low Performance ◽  
User Friendly

Abstract Mass spectrometry (MS)-based quantitative proteomics experiments frequently generate data with missing values, which may profoundly affect downstream analyses. A wide variety of imputation methods have been established to deal with the missing-value issue. To date, however, there is a scarcity of efficient, systematic, and easy-to-handle tools that are tailored for proteomics community. Herein, we developed a user-friendly and powerful stand-alone software, NAguideR, to enable implementation and evaluation of different missing value methods offered by 23 widely used missing-value imputation algorithms. NAguideR further evaluates data imputation results through classic computational criteria and, unprecedentedly, proteomic empirical criteria, such as quantitative consistency between different charge-states of the same peptide, different peptides belonging to the same proteins, and individual proteins participating protein complexes and functional interactions. We applied NAguideR into three label-free proteomic datasets featuring peptide-level, protein-level, and phosphoproteomic variables respectively, all generated by data independent acquisition mass spectrometry (DIA-MS) with substantial biological replicates. The results indicate that NAguideR is able to discriminate the optimal imputation methods that are facilitating DIA-MS experiments over those sub-optimal and low-performance algorithms. NAguideR further provides downloadable tables and figures supporting flexible data analysis and interpretation. NAguideR is freely available at http://www.omicsolution.org/wukong/NAguideR/ and the source code: https://github.com/wangshisheng/NAguideR/.

scholarly journals proDA: Probabilistic Dropout Analysis for Identifying Differentially Abundant Proteins in Label-Free Mass Spectrometry

2020 ◽  
Author(s):  
Constantin Ahlmann-Eltze ◽  
Simon Anders
Keyword(s):  
Mass Spectrometry ◽  
Quantitative Proteomics ◽  
Statistical Power ◽  
Missing Values ◽  
Ad Hoc ◽  
Linear Models ◽  
Statistical Tests ◽  
High Sensitivity ◽  
Small Sample ◽  
Label Free

Abstract Protein mass spectrometry with label-free quantification (LFQ) is widely used for quantitative proteomics studies. Nevertheless, well-principled statistical inference procedures are still lacking, and most practitioners adopt methods from transcriptomics. These, however, cannot properly treat the principal complication of label-free proteomics, namely many non-randomly missing values. We present proDA, a method to perform statistical tests for differential abundance of proteins. It models missing values in an intensity-dependent probabilistic manner. proDA is based on linear models and thus suitable for complex experimental designs, and boosts statistical power for small sample sizes by using variance moderation. We show that the currently widely used methods based on ad hoc imputation schemes can report excessive false positives, and that proDA not only overcomes this serious issue but also offers high sensitivity. Thus, proDA fills a crucial gap in the toolbox of quantitative proteomics.

scholarly journals Identification of an Arginase II Inhibitor via RapidFire Mass Spectrometry Combined with Hydrophilic Interaction Chromatography

2018 ◽  
Vol 24 (4) ◽  
pp. 457-465 ◽  
Author(s):  
Wataru Asano ◽  
Yu Takahashi ◽  
Motoaki Kawano ◽  
Yoshiji Hantani
Keyword(s):  
Mass Spectrometry ◽  
High Throughput ◽  
High Throughput Screening ◽  
Large Scale ◽  
Hydrophilic Interaction Chromatography ◽  
Label Free ◽  
Hydrophilic Interaction ◽  
High Concentration ◽  
Allosteric Site ◽  
Arginase Ii

Peripheral arterial disease (PAD) is an occlusive disease that can lead to atherosclerosis. The involvement of arginase II (Arg II) in PAD progression has been proposed. However, no promising drugs targeting Arg II have been developed to date for the treatment of PAD. In this study, we established a method for detecting the activity of Arg II via high-throughput label-free RapidFire mass spectrometry using hydrophilic interaction chromatography, which enables the direct measurement of l-ornithine produced by Arg II. This approach facilitated a robust high-concentration screening of fragment compounds and the identification of a fragment that inhibits the activity of Arg II. We further confirmed binding of the fragment to the potential allosteric site of Arg II using a surface plasmon resonance assay. We concluded that the identified fragment is a promising compound that may lead to novel drugs to treat PAD, and our method for detecting the activity of Arg II can be applied to large-scale high-throughput screening to identify other structural types of Arg II inhibitors.

scholarly journals Analysis of membrane fouling by proteins during nanofiltration of chitin alkali wastewater

2014 ◽  
Vol 4 (4) ◽  
pp. 253-262 ◽  
Author(s):  
Juan Li ◽  
Liming Zhao ◽  
Yaosong Wang ◽  
Chaoqin Chen ◽  
Jiachun Zhou ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Membrane Fouling ◽  
Protein Concentration ◽  
Large Scale ◽  
Permeate Flux ◽  
Total Proteins ◽  
Fouling Mechanism ◽  
Protein Fouling ◽  
Processing Plants ◽  
And Diffusion

The membrane fouling mechanism used during the nanofiltration (NF) of chitin alkali effluent was investigated. Tests were carried out in three large-scale chitin-processing plants with three kinds of wastewater. An alkali resistant NF membrane with molecular weight cut-off of 250 Da was employed. The reflection coefficient (σ) and diffusion coefficient (Ps) of total proteins were deduced, assuming that the proteins were single entities in the feed. Viscosity and osmosis pressure were measured to evaluate their influences on the permeate flux. Furthermore, the fraction of the protein fouling was extracted and qualitatively analyzed by mass spectrometry. Results showed that the NF permeate flux of alkali wastewater with the highest protein concentration (4.00%) was the lowest, and that σ and penetration Ps decreased with protein content growth. Over 60% of the peptides in the permeate were hydrophobic, whereas 70% of the peptides in the adsorption cake were hydrophilic. Irreversible resistance was the predominant resistance during NF processing, and the fouling behaviour of hydrophilic fractions was dominant.

scholarly journals Deciphering the major metabolic pathways associated with aluminum tolerance in popcorn roots using label-free quantitative proteomics

2021 ◽  
Author(s):  
Vitor B. Pinto ◽  
Vinícius C. Almeida ◽  
Italo A. P. Lima ◽  
Ellen M. Vale ◽  
Wagner L. Araújo ◽  
...  
Keyword(s):  
Inbred Line ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Citrate Synthase ◽  
Al Toxicity ◽  
Soluble Form ◽  
Starch Degradation ◽  
Label Free ◽  
Al Stress ◽  
Proteomic Data

Aluminum toxicity is one of the most important abiotic stresses that affect crop production worldwide. The soluble form (Al3+) inhibits root growth by altering water and nutrients uptake, which also reduces plant growth and development. Under a long term Al3+ exposure, plants can activate several tolerance mechanisms, and to date, there are no reports of large-scale proteomic data of maize in response to this ion. To investigate the post-transcriptional regulation in response to Al toxicity, we performed a label-free quantitative proteomics for comparative analysis of two Al-contrasting popcorn inbred lines and an Al-tolerant commercial hybrid during 72 h under Al-stress. A total of 489 differentially accumulated proteins (DAPs) were identified in the Al-sensitive inbred line, 491 in the Al-tolerant inbred line, and 277 in the commercial hybrid. Among them, 120 DAPs were co-expressed in both Al tolerant genotypes. Bioinformatics analysis indicated that starch and sucrose metabolism, glycolysis/gluconeogenesis, and carbohydrate metabolism were significant biochemical processes regulated in response to Al toxicity. The up accumulation of sucrose synthase and the increase of sucrose content and starch degradation suggest that these components may enhance popcorn tolerance to Al stress. The up-accumulation of citrate synthase suggests a key role of this enzyme in the detoxification process in the Al-tolerant inbred line. The integration of transcriptomic and proteomic data indicated that the Al tolerance response presents a complex regulatory network into the transcription and translation dynamics of popcorn roots development.

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