Quantitative Profiling Identifies Potential Regulatory Proteins Involved in Development from Dauer Stage to L4 Stage in <i>Caenorhabditis elegans</i>

When <i>Caenorhabditis elegans</i> encounters unfavorable growth conditions, it enters the dauer stage, an alternative L3 developmental period. A dauer larva resumes larval development to the normal L4 stage by uncharacterized postdauer reprogramming (PDR) when growth conditions become more favorable. During this transition period, certain heterochronic genes involved in controlling the proper sequence of developmental events are known to act, with their mutations suppressing the Muv (multivulva) phenotype in <i>C. elegans.</i> To identify the specific proteins in which the Muv phenotype is highly suppressed, quantitative proteomic analysis with iTRAQ labeling of samples obtained from worms at L1 + 30 h (for continuous development [CD]) and dauer recovery +3 h (for postdauer development [PD]) was carried out to detect changes in protein abundance in the CD and PD states of both N2 and <i>lin-28­(n719)</i>. Of the 1661 unique proteins identified with <i>a</i> < 1% false discovery rate at the peptide level, we selected 58 proteins exhibiting ≥2-fold up-regulation or ≥2-fold down-regulation in the PD state and analyzed the Gene Ontology terms. RNAi assays against 15 selected up-regulated genes showed that seven genes were predicted to be involved in higher Muv phenotype (<i>p</i> < 0.05) in <i>lin-28­(n791)</i>, which is not seen in N2. Specifically, two genes, K08H10.1 and W05H9.1, displayed not only the highest rate (%) of Muv phenotype in the RNAi assay but also the dauer-specific mRNA expression, indicating that these genes may be required for PDR, leading to the very early onset of dauer recovery. Thus, our proteomic approach identifies and quantitates the regulatory proteins potentially involved in PDR in <i>C. elegans</i>, which safeguards the overall lifecycle in response to environmental changes

Quantitative Profiling Identifies Potential Regulatory Proteins Involved in Development from Dauer Stage to L4 Stage in <i>Caenorhabditis elegans</i>

When <i>Caenorhabditis elegans</i> encounters unfavorable growth conditions, it enters the dauer stage, an alternative L3 developmental period. A dauer larva resumes larval development to the normal L4 stage by uncharacterized postdauer reprogramming (PDR) when growth conditions become more favorable. During this transition period, certain heterochronic genes involved in controlling the proper sequence of developmental events are known to act, with their mutations suppressing the Muv (multivulva) phenotype in <i>C. elegans.</i> To identify the specific proteins in which the Muv phenotype is highly suppressed, quantitative proteomic analysis with iTRAQ labeling of samples obtained from worms at L1 + 30 h (for continuous development [CD]) and dauer recovery +3 h (for postdauer development [PD]) was carried out to detect changes in protein abundance in the CD and PD states of both N2 and <i>lin-28­(n719)</i>. Of the 1661 unique proteins identified with <i>a</i> < 1% false discovery rate at the peptide level, we selected 58 proteins exhibiting ≥2-fold up-regulation or ≥2-fold down-regulation in the PD state and analyzed the Gene Ontology terms. RNAi assays against 15 selected up-regulated genes showed that seven genes were predicted to be involved in higher Muv phenotype (<i>p</i> < 0.05) in <i>lin-28­(n791)</i>, which is not seen in N2. Specifically, two genes, K08H10.1 and W05H9.1, displayed not only the highest rate (%) of Muv phenotype in the RNAi assay but also the dauer-specific mRNA expression, indicating that these genes may be required for PDR, leading to the very early onset of dauer recovery. Thus, our proteomic approach identifies and quantitates the regulatory proteins potentially involved in PDR in <i>C. elegans</i>, which safeguards the overall lifecycle in response to environmental changes

Data_Sheet_1_Cerebral artery signal intensity gradient from Time-of-Flight Magnetic Resonance Angiography and clinical outcome in lenticulostriate infarction: a retrospective cohort study.PDF

PurposeLenticulostriate infarction requires further research of arterial hemodynamic factors, as the disease is diagnosed in the absence of major arterial stenosis or cardioembolism.MethodsIn this multicenter retrospective cohort study, we included patients who were hospitalized for lenticulostriate infarction from January 2015 to March 2021 at three stroke centers in South Korea. We obtained hemodynamic information on cerebral arteries using signal intensity gradient (SIG), an in-vivo approximated wall shear stress (WSS) derived from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA). A favorable outcome was defined as a modified Rankin Scale of 0 to 2 at hospital discharge.ResultsA total of 294 patients were included, of whom 146 (49.7%) had an unfavorable outcome. The unfavorable outcome group showed significantly lower SIG in both middle cerebral arteries (MCAs) than the favorable group (5.2 ± 1.2 SI/mm vs. 5.9 ± 1.2, p ConclusionCerebral artery SIG from TOF-MRA was significantly associated with short-term functional outcomes in patients with lenticulostriate infarction. Further studies are needed to investigate the temporal relationships of SIG in patients with cerebral infarction.</p

gFinder: A Web-Based Bioinformatics Tool for the Analysis of <i>N</i>‑Glycopeptides

Glycoproteins influence numerous indispensable biological functions, and changes in protein glycosylation have been observed in various diseases. The identification and characterization of glycoprotein and glycosylation sites by mass spectrometry (MS) remain challenging tasks, and great efforts have been devoted to the development of proteome informatics tools that facilitate the MS analysis of glycans and glycopeptides. Here we report on the development of gFinder, a web-based bioinformatics tool that analyzes mixtures of native <i>N</i>-glycopeptides that have been profiled by tandem MS. gFinder not only enables the simultaneous integration of collision-induced dissociation (CID) and high-energy collisional dissociation (HCD) fragmentation but also merges the spectra for high-throughput analysis. These merged spectra expedite the identification of both glycans and <i>N</i>-glycopeptide backbones in tandem MS data using the glycan database and a proteomic search tool (e.g., Mascot). These data can be used to simultaneously characterize peptide backbone sequences and possible <i>N</i>-glycan structures using assigned scores. gFinder also provides many convenient functions that make it easy to perform manual calculations while viewing the spectrum on-screen. We used gFinder to detect an additional protein (Q8N9B8) that was missed from the previously published data set containing N-linked glycosylation. For <i>N</i>-glycan analysis, we used the GlycomeDB glycan structure database, which integrates the structural and taxonomic data from all of the major carbohydrate databases available in the public domain. Thus, gFinder is a convenient, high-throughput analytical tool for interpreting the tandem mass spectra of <i>N</i>-glycopeptides, which can then be used for identification of potential missing proteins having glycans. gFinder is available publicly at http://gFinder.proteomix.org/

The functional analysis of 6 k-mean clusters.

<p>This list of proteins was employed to identify significantly activated pathways by comparing their functional annotations according to the PANTHER classification systems. Proteins involved in nucleic acid binding, protein synthesis, and signaling (particularly, proteins involved in integrin signaling) were enriched in the downregulated protein clusters (clusters 1, 2, and 3), whereas the upregulated proteins in clusters 4, 5, and 6 were enriched in proteins involved in cytoskeleton structure.</p

Experimental design of proteome analysis of hESCs using iTRAQ labeling.

<p>Samples from undifferentiated hESCs and EBs at days 6, 12, and 20 were collected in three biological replicates. Similar amounts of proteins were digested into peptides using trypsin. Peptides were subsequently desalted and labeled with 8-plex iTRAQ reagents 113–121. Labeled peptides were pooled, fractionated into 20 SCX fractions, and then analyzed by reverse-phase LC-MS/MS.</p

Correlation between the expression patterns of differentially expressed proteins identified in this study and their corresponding mRNA at three different stages.

<p>Correlation between the expression patterns of differentially expressed proteins identified in this study and their corresponding mRNA at three different stages.</p

Proteogenomic Analysis of Human Chromosome 9‑Encoded Genes from Human Samples and Lung Cancer Tissues

The Chromosome-centric Human Proteome Project (C-HPP) was recently initiated as an international collaborative effort. Our team adopted chromosome 9 (Chr 9) and performed a bioinformatics and proteogenomic analysis to catalog Chr 9-encoded proteins from normal tissues, lung cancer cell lines, and lung cancer tissues. Approximately 74.7% of the Chr 9 genes of the human genome were identified, which included approximately 28% of missing proteins (46 of 162) on Chr 9 compared with the list of missing proteins from the neXtProt Master Table (2013-09). In addition, we performed a comparative proteomics analysis between normal lung and lung cancer tissues. On the basis of the data analysis, 15 proteins from Chr 9 were detected only in lung cancer tissues. Finally, we conducted a proteogenomic analysis to discover Chr 9-residing single nucleotide polymorphisms (SNP) and mutations described in the COSMIC cancer mutation database. We identified 21 SNPs and four mutations containing peptides on Chr 9 from normal human cells/tissues and lung cancer cell lines, respectively. In summary, this study provides valuable information of the human proteome for the scientific community as part of C-HPP. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000603

Proteogenomic Analysis of Human Chromosome 9‑Encoded Genes from Human Samples and Lung Cancer Tissues

The Chromosome-centric Human Proteome Project (C-HPP) was recently initiated as an international collaborative effort. Our team adopted chromosome 9 (Chr 9) and performed a bioinformatics and proteogenomic analysis to catalog Chr 9-encoded proteins from normal tissues, lung cancer cell lines, and lung cancer tissues. Approximately 74.7% of the Chr 9 genes of the human genome were identified, which included approximately 28% of missing proteins (46 of 162) on Chr 9 compared with the list of missing proteins from the neXtProt Master Table (2013-09). In addition, we performed a comparative proteomics analysis between normal lung and lung cancer tissues. On the basis of the data analysis, 15 proteins from Chr 9 were detected only in lung cancer tissues. Finally, we conducted a proteogenomic analysis to discover Chr 9-residing single nucleotide polymorphisms (SNP) and mutations described in the COSMIC cancer mutation database. We identified 21 SNPs and four mutations containing peptides on Chr 9 from normal human cells/tissues and lung cancer cell lines, respectively. In summary, this study provides valuable information of the human proteome for the scientific community as part of C-HPP. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000603

Proteogenomic Analysis of Human Chromosome 9‑Encoded Genes from Human Samples and Lung Cancer Tissues

The Chromosome-centric Human Proteome Project (C-HPP) was recently initiated as an international collaborative effort. Our team adopted chromosome 9 (Chr 9) and performed a bioinformatics and proteogenomic analysis to catalog Chr 9-encoded proteins from normal tissues, lung cancer cell lines, and lung cancer tissues. Approximately 74.7% of the Chr 9 genes of the human genome were identified, which included approximately 28% of missing proteins (46 of 162) on Chr 9 compared with the list of missing proteins from the neXtProt Master Table (2013-09). In addition, we performed a comparative proteomics analysis between normal lung and lung cancer tissues. On the basis of the data analysis, 15 proteins from Chr 9 were detected only in lung cancer tissues. Finally, we conducted a proteogenomic analysis to discover Chr 9-residing single nucleotide polymorphisms (SNP) and mutations described in the COSMIC cancer mutation database. We identified 21 SNPs and four mutations containing peptides on Chr 9 from normal human cells/tissues and lung cancer cell lines, respectively. In summary, this study provides valuable information of the human proteome for the scientific community as part of C-HPP. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000603