Proteomic analysis reveals LRPAP1 as a key player in the micropapillary pattern metastasis of lung adenocarcinoma.

Objectives: Lung adenocarcinomas have different prognoses depending on their histological growth patterns. Micropapillary growth within lung adenocarcinoma, particularly metastasis, is related to dismal prognostic outcome. Metastasis accounts for a major factor leading to mortality among lung cancer patients. Understanding the mechanisms underlying early stage metastasis can help develop novel treatments for improving patient survival. Methods: Here, quantitative mass spectrometry was conducted for comparing protein expression profiles among various histological subtypes, including adenocarcinoma in situ, minimally invasive adenocarcinoma, and invasive adenocarcinoma (including acinar and micropapillary [MIP] types). To determine the mechanism of MIP-associated metastasis, we identified a protein that was highly expressed in MIP. The expression of the selected highly expressed MIP protein was verified via immunohistochemical (IHC) analysis and its function was validated by an in vitro migration assay. Results: Proteomic data revealed that low-density lipoprotein receptor-related protein-associated protein 1 (LRPAP1) was highly expressed in MIP group, which was confirmed by IHC. The co-expressed proteins in this study, PSMD1 and HSP90AB1, have been reported to be highly expressed in different cancers and play an essential role in metastasis. We observed that LRPAP1 promoted lung cancer progression, including metastasis, invasion and proliferation in vitro and in vivo. Conclusion: LRPAP1 is necessary for MIP-associated metastasis and is the candidate novel anti-metastasis therapeutic target.

Combined Proteomic and Phosphoproteomic Characterization of the Molecular Regulators and Functional Modules During Pancreatic Progenitor Cell Development.

Differentiated multipotent pancreatic progenitors have major advantages for both modeling pancreas development and preventing or treating diabetes. Despite significant advancements in inducing the differentiation of human pluripotent stem cells into insulin-producing cells, the complete mechanism governing proliferation and differentiation remains poorly understood. This study used large-scale mass spectrometry to characterize molecular processes at various stages of human embryonic stem cell (hESC) differentiation toward pancreatic progenitors. hESCs were induced into pancreatic progenitor cells in a five-stage differentiation protocol. A high-performance liquid chromatography-mass spectrometry platform was used to undertake comprehensive proteome and phosphoproteome profiling of cells at different stages. A series of bioinformatic explorations, including coregulated modules, gene regulatory networks, and phosphosite enrichment analysis, were then conducted. A total of 27,077 unique phosphorylated sites and 8122 proteins were detected, including several cyclin-dependent kinases at the initial stage of cell differentiation. Furthermore, we discovered that ERK1, a member of the MAPK cascade, contributed to proliferation at an early stage. Finally, Western blotting confirmed that the phosphosites from SIRT1 and CHEK1 could inhibit the corresponding substrate abundance in the late stage. Thus, this study extends our understanding of the molecular mechanism during pancreatic cell development.

A large-scale proteogenomic atlas of pear.

Pear is an important fruit tree that is widely distributed around the world. The first pear genome map was reported from our laboratory approximately 10 years ago. To further study global protein expression patterns in pear, we generated pear proteome data based on 24 major tissues. The tissue-resolved profiles provided evidence of the expression of 17 953 proteins. We identified 4294 new coding events and improved the pear genome annotation via the proteogenomic strategy based on 18 090 peptide spectra with peptide spectrum matches >1. Among the eight randomly selected new short coding open reading frames that were expressed in the style, four promoted and one inhibited the growth of pear pollen tubes. Based on gene coexpression module analysis, we explored the key genes associated with important agronomic traits, such as stone cell formation in fruits. The network regulating the synthesis of lignin, a major component of stone cells, was reconstructed, and receptor-like kinases were implicated as core factors in this regulatory network. Moreover, we constructed the online database PearEXP (http://www.peardb.org.cn) to enable access to the pear proteogenomic resources. This study provides a paradigm for in-depth proteogenomic studies of woody plants.

Dynamic Plasma Lipidomic Analysis Revealed Cholesterol Ester and Amides Associated with Sepsis Development in Critically Ill Patients after Cardiovascular Surgery with Cardiopulmonary Bypass.

Background: Sepsis in patients after cardiovascular surgery with cardiopulmonary bypass (CPB) has a high rate of mortality. We sought to determine whether changes in lipidomics can predict sepsis after cardiac surgery. Methods: We used high-performance liquid chromatography coupled to tandem mass spectrometry to explore global lipidome changes in samples from a prospective case-control cohort (30 sepsis vs. 30 nonsepsis) hospitalized with cardiovascular surgery. All patients were sampled before and within 48−72 h after surgery. A bioinformatic pipeline was applied to acquire reliable features and MS/MS-driven identifications. Furthermore, a multiple-step machine learning framework was performed for signature discovery and performance evaluation. Results: Compared with preoperative samples, 94 features were upregulated and 282 features were downregulated in the postoperative samples of the sepsis group, and 73 features were upregulated and 265 features were downregulated in the postoperative samples of the nonsepsis group. "Autophagy", "pathogenic Escherichia coli infection" and "glycosylphosphatidylinositol-anchor biosynthesis" pathways were significantly enriched in the pathway enrichment analysis. A multistep machine learning framework further confirmed that two cholesterol esters, CE (18:0) and CE (16:0), were significantly decreased in the sepsis group (p < 0.05). In addition, oleamide and stearamide were increased significantly in the postoperative sepsis group (p < 0.001). Conclusions: This study revealed characteristic lipidomic changes in the plasma of septic patients before and after cardiac surgery with CPB. We discovered two cholesterol esters and two amides from peripheral blood that could be promising signatures for sepsis within a dynamic detection between the preoperative and postoperative groups.

Light shift suppression with pulsed light detection in magnetic-state-selected cesium beam clocks.

Light detection is widely used in atomic clocks. The simple detecting structure induces the light shift which influences the clock's long-term stability. We introduce a new method to suppress light shift by using pulsed light instead of continuous light to detect atomic states. Under a suitable pulsed sequence, the part of the atoms which do not simultaneously interact with light and microwave field are detected. We demonstrate the validity of our approach in a magnetic-state-selected cesium beam clock. Using a well-tuned sequence, the light shift coefficient is reduced by a factor of about 10, in comparison with the continuous light detection scheme. In a clock stability test with extra light power noise, the result shows good immunity of the method to laser power fluctuations. We also analyze the sources of the clock short-term stability degradation, including the Dick effect and the fact that a reduced number of atoms is detected in the pulsed detection case.

Overview of the MEMS Pirani Sensors.

Vacuum equipment has a wide range of applications, and vacuum monitoring in such equipment is necessary in order to meet practical applications. Pirani sensors work by using the effect of air density on the heat conduction of the gas to cause temperature changes in sensitive structures, thus detecting the pressure in the surrounding environment and thus vacuum monitoring. In past decades, MEMS Pirani sensors have received considerable attention and practical applications because of their advances in simple structures, long service life, wide measurement range and high sensitivity. This review systematically summarizes and compares different types of MEMS Pirani sensors. The configuration, material, mechanism, and performance of different types of MEMS Pirani sensors are discussed, including the ones based on thermistors, thermocouples, diodes and surface acoustic wave. Further, the development status of novel Pirani sensors based on functional materials such as nanoporous materials, carbon nanotubes and graphene are investigated, and the possible future development directions for MEMS Pirani sensors are discussed. This review is with the purpose to focus on a generalized knowledge of MEMS Pirani sensors, thus inspiring the investigations on their practical applications.

Lysophosphatidylcholines and phosphatidylcholines as biomarkers for stroke recovery.

Stroke is a serious global public health issue, associated with severe disability and high mortality rates. Its early detection is challenging, and no effective biomarkers are available. To obtain a better understanding of stroke prevention, management, and recovery, we conducted lipidomic analyses to characterize plasma metabolic features. Lipid species were measured using an untargeted lipidomic analysis with liquid chromatography-tandem mass spectrometry. Sixty participants were recruited in this cohort study, including 20 healthy individuals and 40 patients with stroke. To investigate the association between lipids related to long-term functional recovery in stroke patients. The primary independent variable was activities of daily living (ADL) dependency upon admission to the stroke unit and at the 3-month follow-up appointment. ADL dependency was assessed using the Barthel Index. Eleven significantly altered lipid species between the stroke and healthy groups were detected and displayed in a hierarchically clustered heatmap. Acyl carnitine, triacylglycerol, and ceramides were detected as potential lipid markers. Regarding the association between lipid profiles and functional status of patients with stroke the results indicated, lysophosphatidylcholines (LPC) and phosphatidylcholines were closely associated with stroke recovery. LPC may contribute positively role in patient's rehabilitation process via an anti-inflammatory mechanism. Appropriate management or intervention for lipid levels is expected to lead to better clinical outcomes.

Improving the short-term frequency stability of a magnetic-state-selected cesium beam clock with optical detection.

The microwave spectrum line shape and the signal-to-noise ratio of a compact optically detected magnetic-state-selection cesium beam clock are analyzed in this paper. As the noise analysis shows, the performance is related to the atomic utilization ratio and locking parameters when the laser frequency noise is the dominant noise source. Methods are adopted for realizing better short-term frequency stability of the clock, including using a highly efficient state-selection cesium beam tube, optimizing the locking parameters, and stabilizing the microwave power to maximize the error signal. After optimization, the signal-to-noise ratio of the clock reaches 7.0 × 103 in a bandwidth of 1 Hz and the clock demonstrates a short-term stability of 4.1 × 10-12 τ-1/2. The five-day Allan standard deviation reaches 7.7 × 10-15.

Comparison of applied torque and energy conversion efficiency between rotational triboelectric nanogenerator and electromagnetic generator.

Triboelectric nanogenerator (TENG) is regarded as an equally important mechanical energy harvesting technology as electromagnetic generator (EMG). Here, the input mechanical torques and energy conversion efficiencies of the rotating EMG and TENG are systematically measured, respectively. At constant rotation rates, the input mechanical torque of EMG is balanced by the friction resisting torque and electromagnetic resisting torque, which increases with the increasing rotation rate due to Ampere force. While the input mechanical torque of TENG is balanced by the friction resisting torque and electrostatic resisting torque, which is nearly constant at different rotation rates. The energy conversion efficiency of EMG increases with the increasing input mechanical power, while that of the TENG remains nearly constant. Compared with the EMG, the TENG has a higher conversion efficiency at a low input mechanical power, which demonstrates a remarkable merit of the TENG for efficiently harvesting weak ambient mechanical energy.

Network Topology Optimization of Triboelectric Nanogenerators for Effectively Harvesting Ocean Wave Energy.

The emerging triboelectric nanogenerator (TENG) network shows great potential in harvesting the ocean wave energy, which can help to achieve large-scale clean wave power generation. However, due to the lack of an effective networking strategy and theoretical guidance, the practicability of the TENG network is heavily restricted. In this paper, based on the typical spherical TENG, we investigated the networking design of TENGs. Four fundamental forms of electrical networking topology are proposed for large-scale TENG networks, and the influences of cable resistance and output phase asynchrony of each unit to the network output were systematically investigated. The research results show that the forms of electrical networking topology can produce an important influence on the output power of large-scale TENG networks. This is the first strategy analysis for the TENG network, which provides a theoretical basis and a universal method for the optimization design of large-scale power networks.

Improving Gene Annotation of the Peanut Genome by Integrated Proteogenomics Workflow.

Peanut (Arachis hypogaea L.) is a staple crop in semiarid tropical and subtropical regions. Although the genome of peanut has been fully sequenced, the current gene annotations are still incomplete. New technologies in genomics and proteomics have resulted in the emergence of proteogenomics, which can integrate genomic, transcriptomic, and proteomic data for improving gene annotation. In the present study, we collected RNA-seq and proteomic data from multiple tissues such as seed, shell, and gynophore of peanut and utilized a proteogenomic approach to improve the gene annotation of peanut based on these data. A total of 1 935 655 904 RNA-seq reads and 7 490 280 MS/MS spectra were collected. Ultimately, 13 767 annotated genes were found with evidence at the protein level, and seven novel protein-coding genes were found with both RNA-seq and proteomics evidence. In addition, 35 gene models were updated based on proteomics data. Proteogenomic approaches improved the gene annotation in certain aspects by integrating both RNA-seq and proteomic data. We expect that these approaches could help improve existing genome annotations of other species.

Comparative proteomics analysis of Tibetan hull-less barley under osmotic stress via data-independent acquisition mass spectrometry.

BACKGROUND: Tibetan hull-less barley (Hordeum vulgare L. var. nudum) is one of the primary crops cultivated in the mountains of Tibet and encounters low temperature, high salinity, and drought. Specifically, drought is one of the major abiotic stresses that affect and limit Tibetan barley growth. Osmotic stress is often simultaneously accompanied by drought conditions. Thus, to improve crop yield, it is critical to explore the molecular mechanism governing the responses of hull-less barley to osmotic/drought stress conditions. FINDINGS: In this study, we used quantitative proteomics by data-independent acquisition mass spectrometry to investigate protein abundance changes in tolerant (XL) and sensitive (DQ) cultivars. A total of 6,921 proteins were identified and quantified in all samples. Two distinct strategies based on pairwise and time-course comparisons were utilized in the comprehensive analysis of differentially abundant proteins. Further functional analysis of differentially abundant proteins revealed that some hormone metabolism-associated and phytohormone abscisic acid-induced genes are primarily affected by osmotic stress. Enhanced regulation of reactive oxygen species (may promote the tolerance of hull-less barley under osmotic stress. Moreover, we found that some regulators, such as GRF, PR10, MAPK, and AMPK, were centrally positioned in the gene regulatory network, suggesting that they may have a dominant role in the osmotic stress response of Tibetan barley. CONCLUSIONS: Our findings highlight a subset of proteins and processes that are involved in the alleviation of osmotic stress. In addition, this study provides a large-scale and multidimensional proteomic data resource for the further investigation and improvement of osmotic/drought stress tolerance in hull-less barley or other plant species.

PPIP: Automated Software for Identification of Bioactive Endogenous Peptides.

Endogenous peptides play an important role in multiple biological processes in many species. Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is an important technique for detecting these peptides on a large scale. We present PPIP, which is a dedicated peptidogenomics software for identifying endogenous peptides based on peptidomics and RNA-Seq data. This software automates the de novo transcript assembly based on RNA-Seq data, construction of a protein reference database based on the de novo assembled transcripts, peptide identification, function analysis, and HTML-based report generation. Different function components are integrated using Docker technology. The Docker image of PPIP is available at https://hub.docker.com/r/shawndp/ppip , and the source code under GPL-3 license is available at https://github.com/Shawn-Xu/PPIP . A user manual of PPIP is available at https://shawn-xu.github.io/PPIP .

Improvements to the Rice Genome Annotation Through Large-Scale Analysis of RNA-Seq and Proteomics Data Sets.

Rice (Oryza sativa) is one of the most important worldwide crops. The genome has been available for over 10 years and has undergone several rounds of annotation. We created a comprehensive database of transcripts from 29 public RNA sequencing data sets, officially predicted genes from Ensembl plants, and common contaminants in which to search for protein-level evidence. We re-analyzed nine publicly accessible rice proteomics data sets. In total, we identified 420K peptide spectrum matches from 47K peptides and 8,187 protein groups. 4168 peptides were initially classed as putative novel peptides (not matching official genes). Following a strict filtration scheme to rule out other possible explanations, we discovered 1,584 high confidence novel peptides. The novel peptides were clustered into 692 genomic loci where our results suggest annotation improvements. 80% of the novel peptides had an ortholog match in the curated protein sequence set from at least one other plant species. For the peptides clustering in intergenic regions (and thus potentially new genes), 101 loci were identified, for which 43 had a high-confidence hit for a protein domain. Our results can be displayed as tracks on the Ensembl genome or other browsers supporting Track Hubs, to support re-annotation of the rice genome.

Digging More Missing Proteins Using an Enrichment Approach with ProteoMiner.

Human Proteome Project (HPP) aims at mapping entire human proteins with a systematic effort upon all the emerging techniques, which would enhance understanding of human biology and lay a foundation for development of medical applications. Until now, 2563 missing proteins (MPs, PE2-4) are still undetected even using the most sensitive approach of protein detection. Herein, we propose that enrichment of low-abundance proteins benefits MPs finding. ProteoMiner is an equalizing technique by reducing high-abundance proteins and enriching low-abundance proteins in biological liquids. With triton X-100/TBS buffer extraction, ProteoMiner enrichment, and peptide fractionation, 20 MPs (at least two non-nested unique peptides with more than eight a.a. length) with 60 unique peptides were identified from four human tissues including eight membrane/secreted proteins and five nucleus proteins. Then 15 of them were confirmed with two non-nested unique peptides (≥9 a.a.) identified by matching well with their chemically synthetic peptides in PRM assay. Hence, these results demonstrated ProteoMiner as a powerful means in discovery of MPs.

Improvement of peptide identification with considering the abundance of mRNA and peptide.

BACKGROUND: Tandem mass spectrometry (MS/MS) followed by database search is a main approach to identify peptides/proteins in proteomic studies. A lot of effort has been devoted to improve the identification accuracy and sensitivity for peptides/proteins, such as developing advanced algorithms and expanding protein databases. RESULTS: Herein, we described a new strategy for enhancing the sensitivity of protein/peptide identification through combination of mRNA and peptide abundance in Percolator. In our strategy, a new workflow for peptide identification is established on the basis of the abundance of transcripts and potential novel transcripts derived from RNA-Seq and abundance of peptides towards the same life species. We demonstrate the utility of this strategy by two MS/MS datasets and the results indicate that about 5% ~ 8% improvement of peptide identification can be achieved with 1% FDR in peptide level by integrating the peptide abundance, the transcript abundance and potential novel transcripts from RNA-Seq data. Meanwhile, 181 and 154 novel peptides were identified in the two datasets, respectively. CONCLUSIONS: We have demonstrated that this strategy could enable improvement of peptide/protein identification and discovery of novel peptides, as compared with the traditional search methods.

Drug Resistance in Colorectal Cancer Cell Lines is Partially Associated with Aneuploidy Status in Light of Profiling Gene Expression.

A priority in solving the problem of drug resistance is to understand the molecular mechanism of how a drug induces the resistance response within cells. Because many cancer cells exhibit chromosome aneuploidy, we explored whether changes of aneuploidy status result in drug resistance. Two typical colorectal cancer cells, HCT116 and LoVo, were cultured with the chemotherapeutic drugs irinotecan (SN38) or oxaliplatin (QxPt), and the non- and drug-resistant cell lines were selected. Whole exome sequencing (WES) was employed to evaluate the aneuploidy status of these cells, and RNAseq and LC-MS/MS were implemented to examine gene expression at both mRNA and protein level. The data of gene expression was well-matched with the genomic conclusion that HCT116 was a near diploid cell, whereas LoVo was an aneuploid cell with the increased abundance of mRNA and protein for these genes located at chromosomes 5, 7, 12, and 15. By comparing the genomic, transcriptomic, and proteomic data, the LoVo cells with SN38 tolerance showed an increased genome copy in chromosome 14, and the expression levels of the genes on this chromosome were also significantly increased. Thus, we first observed that SN38 could impact the aneuploidy status in cancer cells, which was partially associated with the acquired drug resistance.

PGA: an R/Bioconductor package for identification of novel peptides using a customized database derived from RNA-Seq.

BACKGROUND: Peptide identification based upon mass spectrometry (MS) is generally achieved by comparison of the experimental mass spectra with the theoretically digested peptides derived from a reference protein database. Obviously, this strategy could not identify peptide and protein sequences that are absent from a reference database. A customized protein database on the basis of RNA-Seq data is thus proposed to assist with and improve the identification of novel peptides. Correspondingly, development of a comprehensive pipeline, which provides an end-to-end solution for novel peptide detection with the customized protein database, is necessary. RESULTS: A pipeline with an R package, assigned as a PGA utility, was developed that enables automated treatment to the tandem mass spectrometry (MS/MS) data acquired from different MS platforms and construction of customized protein databases based on RNA-Seq data with or without a reference genome guide. Hence, PGA can identify novel peptides and generate an HTML-based report with a visualized interface. On the basis of a published dataset, PGA was employed to identify peptides, resulting in 636 novel peptides, including 510 single amino acid polymorphism (SAP) peptides, 2 INDEL peptides, 49 splice junction peptides, and 75 novel transcript-derived peptides. The software is freely available from http://bioconductor.org/packages/PGA/ , and the example reports are available at http://wenbostar.github.io/PGA/ . CONCLUSIONS: The pipeline of PGA, aimed at being platform-independent and easy-to-use, was successfully developed and shown to be capable of identifying novel peptides by searching the customized protein database derived from RNA-Seq data.

Appraisal of the Missing Proteins Based on the mRNAs Bound to Ribosomes.

Considering the technical limitations of mass spectrometry in protein identification, the mRNAs bound to ribosomes (RNC-mRNA) are assumed to reflect the mRNAs participating in the translational process. The RNC-mRNA data are reasoned to be useful for appraising the missing proteins. A set of the multiomics data including free-mRNAs, RNC-mRNAs, and proteomes was acquired from three liver cancer cell lines. On the basis of the missing proteins in neXtProt (release 2014-09-19), the bioinformatics analysis was carried out in three phases: (1) finding how many neXtProt missing proteins have or do not have RNA-seq and/or MS/MS evidence, (2) analyzing specific physicochemical and biological properties of the missing proteins that lack both RNA-seq and MS/MS evidence, and (3) analyzing the combined properties of these missing proteins. Total of 1501 missing proteins were found by neither RNC-mRNA nor MS/MS in the three liver cancer cell lines. For these missing proteins, some are expected higher hydrophobicity, unsuitable detection, or sensory functions as properties at the protein level, while some are predicted to have nonexpressing chromatin structures on the corresponding gene level. With further integrated analysis, we could attribute 93% of them (1391/1501) to these causal factors, which result in the expression products scarcely detected by RNA-seq or MS/MS.