The regulation of prolactin secretion and its targeting function of teleost.

Prolactin is involved in regulating various physiological activities of vertebrates and is one of the most momentous pituitary hormones. However, not enough attention is currently paid to prolactin, especially in teleost. This paper aims to gather, organize, and analyze recent studies on the regulation and functions of prolactin. By comparing with other animal groups, it highlights the significant role of prolactin in fish reproduction, immunity, growth, and osmotic pressure regulation, as well as the upstream and downstream factors that may be involved in the regulation of prolactin functions were introduced to provide a theoretical basis for the in-depth study and potential practical application of prolactin.

Proteomic-based stratification of intermediate-risk prostate cancer patients.

Gleason grading is an important prognostic indicator for prostate adenocarcinoma and is crucial for patient treatment decisions. However, intermediate-risk patients diagnosed in the Gleason grade group (GG) 2 and GG3 can harbour either aggressive or non-aggressive disease, resulting in under- or overtreatment of a significant number of patients. Here, we performed proteomic, differential expression, machine learning, and survival analyses for 1,348 matched tumour and benign sample runs from 278 patients. Three proteins (F5, TMEM126B, and EARS2) were identified as candidate biomarkers in patients with biochemical recurrence. Multivariate Cox regression yielded 18 proteins, from which a risk score was constructed to dichotomize prostate cancer patients into low- and high-risk groups. This 18-protein signature is prognostic for the risk of biochemical recurrence and completely independent of the intermediate GG. Our results suggest that markers generated by computational proteomic profiling have the potential for clinical applications including integration into prostate cancer management.

DPHL v.2: An updated and comprehensive DIA pan-human assay library for quantifying more than 14,000 proteins.

A comprehensive pan-human spectral library is critical for biomarker discovery using mass spectrometry (MS)-based proteomics. DPHL v.1, a previous pan-human library built from 1,096 data-dependent acquisition (DDA) MS data of 16 human tissue types, allows quantifying of 10,943 proteins. Here, we generated DPHL v.2 from 1,608 DDA-MS data. The data included 586 DDA-MS data acquired from 18 tissue types, while 1,022 files were derived from DPHL v.1. DPHL v.2 thus comprises data from 24 sample types, including several cancer types (lung, breast, kidney, and prostate cancer, among others). We generated four variants of DPHL v.2 to include semi-tryptic peptides and protein isoforms. DPHL v.2 was then applied to two colorectal cancer cohorts. The numbers of identified and significantly dysregulated proteins increased by at least 21.7% and 14.2%, respectively, compared with DPHL v.1. Our findings show that the increased human proteome coverage of DPHL v.2 provides larger pools of potential protein biomarkers.

Draft Genome Sequence Resource of Sweet Cherry Virescence Phytoplasma Strain SCV-TA2020 Associated with Sweet Cherry Virescence Disease in China.

Sweet cherry virescence phytoplasma strain SCV-TA2020, a related strain of 'Candidatus Phytoplasma ziziphi', is a pathogen associated with sweet cherry virescence disease in China. Here, we provide the first-draft genome sequence of SCV-TA2020, which consists of 775,344 bases, with a GC content of 23.21%. This will provide a reference for understanding the host selection and diversity of host-specific symptoms of 16SrV-B subgroup phytoplasmas.

Alternaria alternata Causing Brown Spot Disease on Walnut in Xinjiang, China.

Walnut is one of the Xinjiang's characteristic dried fruits and the main source of income for farmers in walnut growing areas. In September 2019, Juglans regia leaves with brown spots were observed in a 10 hm2 orchard in Hotan area, the diseased leaf rate reached more than 25%. The leaf lesions were suborbicular to irregular, black-brown, 3 to 8 mm in diameter, with distinct dark borders. Colonies were isolated from 10 diseased leaves collected from two trees in the orchard. Leaf sections (4 × 4 mm) from diseased leaves were surface disinfested with 75% ethyl alcohol for 30 s and 2% NaClO for 3 min, washed with sterile water three times and then plated on potato dextrose agar (PDA) and incubated at 27℃ with a 12h/12h light/dark photoperiod for 4 days. A total of 7 fungal isolates were obtained by single-spore isolation. All the colonies were dark olivaceous on the PDA plates, with loose, cottony mycelium. On potato carrot agar (PCA), all fungal isolates produced conidial chains with numerous secondary chains. The conidia were ellipsoid or obpyriform with 0-3 longitudinal septa and 2-4 transverse septa, measuring 20.6 to 35.8 × 6.8 to 11.2 µm (25.5 ± 0.4 × 8.7 ± 0.2 µm, n=50). The morphological characteristics of the seven fungal isolates were consistent with the A. alternata descriptions of Simmons (2007). DNA was extracted from 50 mg of mycelia for the representative isolate HLP17-7. The internal transcribed spacer (ITS) region was PCR amplified using the universal primers ITS1 / ITS4 (White et al.1990), the partial coding sequence of endopolygalacturonase (endoPG) and the partial region of the histone 3 (H3) were amplified using primers PG2b / PG3 (Andrew et al. 2009) and H3-1a / H3-1b (Glass and Donaldson 1995) respectively. The products were sequenced and deposited in GenBank database under the accession numbers MW514319 [ITS], ON806938 endoPG, MW489301 [H3]. ITS, endoPG and H3 sequences had 99.81% (1/535 nt difference), 99.78% (1/448 nt difference) and 100% (0/417 nt difference) homology with homologous sequences of A. alternata strains (KP124306 [ITS], KP124006 [endoPG], MK085979 [H3]), respectively. During the early autumn, pathogenicity tests were carried out on the healthy mature leaves of seven-year-old Juglans regia plants in the field. Thirty leaves (five leaves per plant) were wounded with a sterile needle and then sprayed with a spore suspension prepared from 10-day-old PDA culture. Five wounded leaves per plant were sprayed with sterile water as control. All the treated leaves were covered with clear plastic bags for 3 days, and the experiment was replicated three times. On the 8th day after inoculation, brown spots appeared on the inoculated leaves, but no spots were observed in the control. Morphological observation and gene sequencing confirmed that the original fungal pathogen was re-isolated from the inoculated leaves. No colony was isolated from the control leaves. The pathogen causing the brown spot was identified as A. alternata based on morphological features and sequence analysis. A. alternata has been reported previously in Sichuan (Yang et al., 2017) causing brown spot in walnut. Xinjiang is dry with little rain and abundant sunshine, so there are few diseases on walnuts. However, the occurrence of brown spot disease has alarmed fruit farmers, walnuts are still at the risk of A. alternata infections even in dry environment with little rain. To our knowledge, this is the first report of A. alternata causing brown spot in walnut in Xinjiang, China. References: Andrew, M., et al. 2009. Mycologia. 101:95 Glass, M. L., and Donaldson, G. C. 1995. Appl. Environ. Microbiol. 61:1323. Simmons, E. G. 2007. Alternaria: An Identification Manual. CBS Fungal Biodiversity Centre, Utrecht, The Netherlands. White, T. J., et al. 1990. Page 315 in: PCR Protocols: A Guide to Methods and Applications. Academic Press, San Diego, CA. Yang, L., et al. 2017. Forest Research. 30(6):1004-1008.

Artificial intelligence defines protein-based classification of thyroid nodules.

Determination of malignancy in thyroid nodules remains a major diagnostic challenge. Here we report the feasibility and clinical utility of developing an AI-defined protein-based biomarker panel for diagnostic classification of thyroid nodules: based initially on formalin-fixed paraffin-embedded (FFPE), and further refined for fine-needle aspiration (FNA) tissue specimens of minute amounts which pose technical challenges for other methods. We first developed a neural network model of 19 protein biomarkers based on the proteomes of 1724 FFPE thyroid tissue samples from a retrospective cohort. This classifier achieved over 91% accuracy in the discovery set for classifying malignant thyroid nodules. The classifier was externally validated by blinded analyses in a retrospective cohort of 288 nodules (89% accuracy; FFPE) and a prospective cohort of 294 FNA biopsies (85% accuracy) from twelve independent clinical centers. This study shows that integrating high-throughput proteomics and AI technology in multi-center retrospective and prospective clinical cohorts facilitates precise disease diagnosis which is otherwise difficult to achieve by other methods.

Identification of 16SrXXX-A Phytoplasma Associated with Salt cedar (Tamarix chinensis Lour.) witches'-broom (SCWB) in Southern Xinjiang of China.

Salt cedar is an ornamental shrub/moderate tree species native to Asia and East Europe, and grows in salt-alkali soil, desert and other dry areas, which plays an important role in wind prevention and sand fixation as well as maintaining ecological balance. Salt cedar witches'-broom (SCWB), which was extremely pernicious to Salt cedar. It was first observed and reported in Xi'an, China in 2005 (Zhao et al.2005). Witches' broom symptoms were observed on 20 out of 150 (13.3%) salt plants surveyed from the Alar region and 10 out of 86 (11.6%) plants from the Akesu region in southern of Xinjiang in May 2020. The damaged plants compared with asymptomatic plants (Fig.1A), the major symptoms included branches clustered, intersegment shorten and coarsen, giving rise to the formation of clusters (Fig.1B). Total plant DNA was extracted from phloem tissues with asymptomatic symptoms and phloem tissues with witches'-broom symptoms by a CTAB-based DNA extraction method (Green et al.1999). The 16S rRNA gene and the phytoplasma universal primers P1/P7 and rpF1/rpR1 of the rp (ribosomal protein) gene were used for Polymerase chain reaction (PCR) amplification by using the extracted plant total DNA as the template. The PCR product was used as the template and the R16F2n/R16R2 prmer was used for nested PCR amplification of the 16S rRNA gene after the amplification was completed. The results show that no product was obtained in asymptomatic plants. When DNA samples from witches'-broom symptomatic plants were used as templates, fragments with lengths 1219 bp and 1174 bp, corresponding to 16S rRNA gene and rp gene, were obtained. 16S rRNA gene was sequenced and deposited in GenBank under accession number MW447513. BLAST analysis revealed that the partial 16S rRNA sequence of the phytoplasma associated with P. aphylla witches' broom showed highest sequence identity (99.67%) to salt cedar witches' broom phytoplasma, 'Candidatus Phytoplasma tamaricis' (Accession Number: FJ432664). Phylogenetic and molecular evolutionary analyses were conducted using MEGA-X (Kumar et al., 2018). Results showed taht the SCWB and 16S rXXX group's'Candidatus Phytoplasma tamaricis', (GenBank accession: FJ432664) have the highest affinity (Fig.2A). A virtual restriction fragment length polymorphism(RFLP) was done to determinethe subgroup ( Zhao et al. 2009). The 16S rDNA sequence from the Tamarix chinensis plant showed 99.3% similarity with that of the "Candidatus Phytoplasma tamaricis" reference strain (GenBank accession: FJ432664), suggesting that the phytoplasma in this study belongs to "Candidatus Phytoplasma tamaricis"-related strain. Therefore, it can be stated that SCWB belongs to the 16S rXXX group. The partial rp sequences only shared 84.74% sequence similarity with that of 'Candidatus Phytoplasma prunorum' (MG383523) of Apple proliferation group, a known subgroup 16S rX. Blast analysis based on the partial rp sequences showed that it shares less than 90% similarity with that of any known phytoplasma (Fig 2B), we suspect that this is due to a lack of sequenced rp gene sequences for the 16S rXXX group. To our knowledge, this is the first report of Salt Cedar Witches' Broom phytoplasma in Xinjiang province, China. As a consequence, we guess the SCWB phytoplasma rp gene belongs to 16S rXXX-rp group, which is also the first report about the 16SrXXX-rp group. Because SCWB1 is the only strain in the 16S rXXX group, and it is the representative strain of the 16S rXXX-A subgroup (Zhao et al. 2009). So, the SCWB disease we found in southern Xinjiang belongs to the 16S rXXX-A subgroup.

ProteomeExpert: a Docker image-based web server for exploring, modeling, visualizing and mining quantitative proteomic datasets.

SUMMARY: The rapid progresses of high-throughput sequencing technology-based omics and mass spectrometry-based proteomics, such as data-independent acquisition and its penetration to clinical studies have generated increasing number of proteomic datasets containing hundreds to thousands of samples. To analyze these quantitative proteomic datasets and other omics (e.g. transcriptomics and metabolomics) datasets more efficiently and conveniently, we present a web server-based software tool ProteomeExpert implemented in Docker, which offers various analysis tools for experimental design, data mining, interpretation and visualization of quantitative proteomic datasets. ProteomeExpert can be deployed on an operating system with Docker installed or with R language environment. AVAILABILITY AND IMPLEMENTATION: The Docker image of ProteomeExpert is freely available from https://hub.docker.com/r/lifeinfo/proteomeexpert. The source code of ProteomeExpert is also openly accessible at http://www.github.com/guomics-lab/ProteomeExpert/. In addition, a demo server is provided at https://proteomic.shinyapps.io/peserver/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PulseDIA: Data-Independent Acquisition Mass Spectrometry Using Multi-Injection Pulsed Gas-Phase Fractionation.

The performance of data-independent acquisition (DIA) mass spectrometry (MS) depends on the separation efficiency of peptide precursors. In Orbitrap-based mass spectrometers, separation efficiency of peptide precursors is limited by the relatively slow scanning rate compared to time of flight (TOF)-based MS. Here, we present PulseDIA, a multi-injection gas-phase fractionation (GPF) strategy for enhanced DIA-MS. This is achieved by equally dividing the conventional DIA analysis covering the entire mass range into multiple injections for DIA analyses with complementary windows. Using mouse liver digests, the PulseDIA method identified up to 50% more peptides and 29% more protein groups than that by conventional DIA with the same length of effective gradient time. Compared to conventional multi-injection GPF, PusleDIA exhibited higher flexibility and identified up to 18% more peptides and 8% more protein groups using two injections. The gain of peptides per effective time unit was the highest in PulseDIA compared to conventional DIA and GPF. We further applied the PulseDIA method to profile the proteome of 18 human tissue samples (benign and malignant) from nine cholangiocarcinoma (CCA) patients. PulseDIA identified 7796 protein groups in these CCA samples, with a 14% increase of protein group identification compared to the conventional DIA method. The missing value for protein matrix dropped by 7% using PulseDIA compared to DIA. A total of 681 significantly altered proteins were detected in CCA samples using PulseDIA, including several dysregulated proteins, which were absent in the conventional DIA analysis. Taken together, we present PulseDIA as an enhanced DIA-MS method with improved sensitivity and reproducibility.

BatchServer: A Web Server for Batch Effect Evaluation, Visualization, and Correction.

Batch effects are unwanted data variations that may obscure biological signals, leading to bias or errors in subsequent data analyses. Effective evaluation and elimination of batch effects are necessary for omics data analysis. In order to facilitate the evaluation and correction of batch effects, here we present BatchSever, an open-source R/Shiny based user-friendly interactive graphical web platform for batch effects analysis. In BatchServer, we introduced autoComBat, a modified version of ComBat, which is the most widely adopted tool for batch effect correction. BatchServer uses PVCA (Principal Variance Component Analysis) and UMAP (Manifold Approximation and Projection) for evaluation and visualization of batch effects. We demonstrate its applications in multiple proteomics and transcriptomic data sets. BatchServer is provided at https://lifeinfor.shinyapps.io/batchserver/ as a web server. The source codes are freely available at https://github.com/guomics-lab/batch_server.

DPHL: A DIA Pan-human Protein Mass Spectrometry Library for Robust Biomarker Discovery.

To address the increasing need for detecting and validating protein biomarkers in clinical specimens, mass spectrometry (MS)-based targeted proteomic techniques, including the selected reaction monitoring (SRM), parallel reaction monitoring (PRM), and massively parallel data-independent acquisition (DIA), have been developed. For optimal performance, they require the fragment ion spectra of targeted peptides as prior knowledge. In this report, we describe a MS pipeline and spectral resource to support targeted proteomics studies for human tissue samples. To build the spectral resource, we integrated common open-source MS computational tools to assemble a freely accessible computational workflow based on Docker. We then applied the workflow to generate DPHL, a comprehensive DIA pan-human library, from 1096 data-dependent acquisition (DDA) MS raw files for 16 types of cancer samples. This extensive spectral resource was then applied to a proteomic study of 17 prostate cancer (PCa) patients. Thereafter, PRM validation was applied to a larger study of 57 PCa patients and the differential expression of three proteins in prostate tumor was validated. As a second application, the DPHL spectral resource was applied to a study consisting of plasma samples from 19 diffuse large B cell lymphoma (DLBCL) patients and 18 healthy control subjects. Differentially expressed proteins between DLBCL patients and healthy control subjects were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supports DIA and PRM MS pipelines for robust protein biomarker discovery. DPHL is freely accessible at https://www.iprox.org/page/project.html?id=IPX0001400000.

A circulating extracellular vesicles-based novel screening tool for colorectal cancer revealed by shotgun and data-independent acquisition mass spectrometry.

Background: Early screening for colorectal cancer (CRC) is essential to improve its prognosis. Liquid biopsies are increasingly being considered for diagnosing cancer due to low invasiveness and high reproducibility. In addition, circulating extracellular vesicles (crEVs, extracellular vesicles isolated from plasma) expressing tumour-specific proteins are potential biomarkers for various cancers. Here, we present a data-independent acquisition (DIA)-mass spectrometry (MS)-based diagnostic method for liquid biopsies. Methods: Extracellular vesicles (EVs) were isolated from culture supernatants of human CRC cell lines, and plasma of patients with CRC at different tumour stages, by overnight ultracentrifugation coupled with sucrose density gradient centrifugation. Tumour-specific EV proteins were prioritized using Tandem Mass Tag (TMT)-based shotgun proteomics and phosphoproteomics. The results were verified in a second independent cohort and a mouse tumour-bearing model using Western blotting (WB). The candidate biomarkers were further validated in a third cohort by DIA-MS. Finally, the DIA-MS methodology was accelerated to permit high-throughput detection of EV biomarkers in another independent cohort of patients with CRC and healthy controls. Results: High levels of total and phosphorylated fibronectin 1 (FN1) in crEVs, haptoglobin (HP), S100A9 and fibrinogen α chain (FGA) were significantly associated with cancer progression. FGA was the most dominant biomarker candidate. Analysis of the human CRC cell lines and the mouse model indicated that FGA+ crEVs were likely released by CRC cells. Furthermore, fast DIA-MS and parallel reaction monitoring (PRM)-MS both confirmed that FGA+ crEVs could distinguish colon adenoma with an area of curve (AUC) in the receiver operating characteristic (ROC) curve of 0.949 and patients with CRC (AUC of ROC is 1.000) from healthy individuals. The performance outperformed conventional tumour biomarkers. The DIA-MS quantification of FGA+ crEVs among three groups agreed with that from PRM-MS. Conclusion: DIA-MS detection of FGA+ crEVs is a potential rapid and non-invasive screening tool to identify early stage CRC. Abbreviations: FGA: fibrinogen α chain; CRC: colorectal cancer; crEVs: circulating extracellular vesicles; EV: extracellular vesicles;MS: mass spectrometry; WB: Western blotting; ROC: receiver operating characteristic; PRM: Parallel Reaction Monitoring; GPC1: Glypican-1; GO: Gene ontology; TEM: transmission electron microscopy; FN1: Fibronectin 1; HP: haptoglobin; TMT: Tandem Mass Tag; LC-MS/MS: liquid chromatography coupled to tandem mass spectrometry; DIA: data-independent acquisition; DDA: data-dependent acquisition; CiRT: Common internal Retention Time standards;AGC: Automatic gain control; AUC: area under curve.

Accelerated Protein Biomarker Discovery from FFPE Tissue Samples Using Single-Shot, Short Gradient Microflow SWATH MS.

We reported and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in preclassified clinical specimens. The method uses a 15 min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration, and OpenSWATH software for data analysis. We applied the method to a cohort containing 204 FFPE tissue samples from 58 prostate cancer patients and 10 benign prostatic hyperplasia patients. Altogether we identified 27,975 proteotypic peptides and 4037 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with a 2 h gradient, we found 3800 proteins were quantified by the two methods on two different instruments with relatively high consistency (r = 0.77). The accelerated method consumed only 17% instrument time, while quantifying 80% of proteins compared to the 2 h gradient SWATH. Although the missing value rate increased by 20%, batch effects reduced by 21%. 75 deregulated proteins measured by the accelerated method were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, and the results exhibited high quantitative consistency with the 15 min SWATH method (r = 0.89) in the same sample set. We further verified the applicability of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n = 154). Altogether, the results showed that the 15 min gradient microflow SWATH accelerated large-scale data acquisition by 6 times, reduced batch effect by 21%, introduced 20% more missing values, and exhibited comparable ability to separate disease groups.

High-throughput proteomic analysis of FFPE tissue samples facilitates tumor stratification.

Formalin-fixed, paraffin-embedded (FFPE), biobanked tissue samples offer an invaluable resource for clinical and biomarker research. Here, we developed a pressure cycling technology (PCT)-SWATH mass spectrometry workflow to analyze FFPE tissue proteomes and applied it to the stratification of prostate cancer (PCa) and diffuse large B-cell lymphoma (DLBCL) samples. We show that the proteome patterns of FFPE PCa tissue samples and their analogous fresh-frozen (FF) counterparts have a high degree of similarity and we confirmed multiple proteins consistently regulated in PCa tissues in an independent sample cohort. We further demonstrate temporal stability of proteome patterns from FFPE samples that were stored between 1 and 15 years in a biobank and show a high degree of the proteome pattern similarity between two types of histological regions in small FFPE samples, that is, punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of a certain degree of biological variations. Applying the method to two independent DLBCL cohorts, we identified myeloperoxidase, a peroxidase enzyme, as a novel prognostic marker. In summary, this study presents a robust proteomic method to analyze bulk and biopsy FFPE tissues and reports the first systematic comparison of proteome maps generated from FFPE and FF samples. Our data demonstrate the practicality and superiority of FFPE over FF samples for proteome in biomarker discovery. Promising biomarker candidates for PCa and DLBCL have been discovered.

In-depth serum proteomics reveals biomarkers of psoriasis severity and response to traditional Chinese medicine.

Serum and plasma contain abundant biological information that reflect the body's physiological and pathological conditions and are therefore a valuable sample type for disease biomarkers. However, comprehensive profiling of the serological proteome is challenging due to the wide range of protein concentrations in serum. Methods: To address this challenge, we developed a novel in-depth serum proteomics platform capable of analyzing the serum proteome across ~10 orders or magnitude by combining data obtained from Data Independent Acquisition Mass Spectrometry (DIA-MS) and customizable antibody microarrays. Results: Using psoriasis as a proof-of-concept disease model, we screened 50 serum proteomes from healthy controls and psoriasis patients before and after treatment with traditional Chinese medicine (YinXieLing) on our in-depth serum proteomics platform. We identified 106 differentially-expressed proteins in psoriasis patients involved in psoriasis-relevant biological processes, such as blood coagulation, inflammation, apoptosis and angiogenesis signaling pathways. In addition, unbiased clustering and principle component analysis revealed 58 proteins discriminating healthy volunteers from psoriasis patients and 12 proteins distinguishing responders from non-responders to YinXieLing. To further demonstrate the clinical utility of our platform, we performed correlation analyses between serum proteomes and psoriasis activity and found a positive association between the psoriasis area and severity index (PASI) score with three serum proteins (PI3, CCL22, IL-12B). Conclusion: Taken together, these results demonstrate the clinical utility of our in-depth serum proteomics platform to identify specific diagnostic and predictive biomarkers of psoriasis and other immune-mediated diseases.

Identification of Protein Abundance Changes in Hepatocellular Carcinoma Tissues Using PCT-SWATH.

PURPOSE: To rapidly identify protein abundance changes in biopsy-level fresh-frozen hepatocellular carcinoma (HCC). EXPERIMENTAL DESIGN: The pressure-cycling technology (PCT) is applied and sequential window acquisition of all theoretical mass spectra (SWATH-MS) workflow is optimized to analyze 38 biopsy-level tissue samples from 19 HCC patients. Each proteome is analyzed with 45 min LC gradient. MCM7 is validated using immunohistochemistry (IHC). RESULTS: A total of 11 787 proteotypic peptides from 2579 SwissProt proteins are quantified with high confidence. The coefficient of variation (CV) of peptide yield using PCT is 32.9%, and the R2 of peptide quantification is 0.9729. Five hundred forty-one proteins showed significant abundance change between the tumor area and its adjacent benign area. From 24 upregulated pathways and 13 suppressed ones, enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues are observed. Protein changes based on α-fetoprotein expression and hepatitis B virus infection are further analyzed. The data altogether highlight 16 promising tumor marker candidates. The upregulation of minichromosome maintenance complex component 7 (MCM7) is further observed in multiple HCC tumor tissues by IHC. CONCLUSIONS AND CLINICAL RELEVANCE: The practicality of rapid proteomic analysis of biopsy-level fresh-frozen HCC tissue samples with PCT-SWATH has been demonstrated and promising tumor marker candidates including MCM7 are identified.

The genetic structure of Turnip mosaic virus population reveals the rapid expansion of a new emergent lineage in China.

BACKGROUND: Turnip mosaic virus (TuMV) is one of the most widespread and economically important virus infecting both crop and ornamental species of the family Brassicaceae. TuMV isolates can be classified to five phylogenetic lineages, basal-B, basal-BR, Asian-BR, world-B and Orchis. RESULTS: To understand the genetic structure of TuMV from radish in China, the 3'-terminal genome of 90 TuMV isolates were determined and analyzed with other available Chinese isolates. The results showed that the Chinese TuMV isolates from radish formed three groups: Asian-BR, basal-BR and world-B. More than half of these isolates (52.54%) were clustered to basal-BR group, and could be further divided into three sub-groups. The TuMV basal-BR isolates in the sub-groups I and II were genetically homologous with Japanese ones, while those in sub-group III formed a distinct lineage. Sub-populations of TuMV basal-BR II and III were new emergent and in a state of expansion. The Chinese TuMV radish populations were under negative selection. Gene flow between TuMV populations from Tai'an, Weifang and Changchun was frequent. CONCLUSIONS: The genetic structure of Turnip mosaic virus population reveals the rapid expansion of a new emergent lineage in China.

Announcing the Genome Atlas of Bamboo and Rattan (GABR) project: promoting research in evolution and in economically and ecologically beneficial plants.

Bamboo and rattan are widely grown for manufacturing, horticulture, and agroforestry. Bamboo and rattan production might help reduce poverty, boost economic growth, mitigate climate change, and protect the natural environment. Despite progress in research, sufficient molecular and genomic resources to study these species are lacking. We launched the Genome Atlas of Bamboo and Rattan (GABR) project, a comprehensive, coordinated international effort to accelerate understanding of bamboo and rattan genetics through genome analysis. GABR includes 2 core subprojects: Bamboo-T1K (Transcriptomes of 1000 Bamboos) and Rattan-G5 (Genomes of 5 Rattans), and several other subprojects. Here we describe the organization, directions, and status of GABR.