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Guo, T.

Publications and source records attributed to Guo, T..

107 records · Page 6Linked to original sources

Proteogenomic heterogeneity of localized human prostate cancer progression

BackgroundTumor-specific genomic aberrations are routinely determined by high throughput genomic measurements. It remains unclear though, how complex genome alterations affect molecular networks through changing protein levels, and consequently biochemical states of tumor tissues. ResultsHere, we investigated the propagation of genomic effects along the axis of gene expression during prostate cancer progression. For that, we quantified genomic, transcriptomic and proteomic alterations based on 105 prostate samples, consisting of benign prostatic hyperplasia regions and malignant tumors, from 39 prostate cancer patients. Our analysis revealed convergent effects of distinct copy number alterations impacting on common downstream proteins, which are important for establishing the tumor phenotype. We devised a network-based approach that integrates perturbations across different molecular layers, which identified a sub-network consisting of nine genes whose joint activity positively correlated with increasingly aggressive tumor phenotypes and was predictive of recurrence-free survival. Further, our data revealed a wide spectrum of intra-patient network effects, ranging from similar to very distinct alterations on different molecular layers. ConclusionsThis study uncovered molecular networks with remarkably convergent alterations across tumor sites and patients, but it also exposed a diversity of network effects: we could not identify a single sub-network that was perturbed in all high-grade tumor regions.

systems biology↗

JAK Inhibitors Suppress Colon Cancer Cachexia-Associated Anorexia and Adipose Wasting in Mice

BackgroundCachexia (CX), a syndrome of muscle atrophy, adipose loss, and anorexia, is associated with reduced survival in cancer patients. The colon adenocarcinoma C26c20 cell line secretes the cytokine leukemia inhibitor factor (LIF) which induces CX. We characterized how LIF promotes CX-associated weight loss and anorexia in mice through JAK-dependent changes in adipose and hypothalamic tissues. MethodsCX was induced in vivo with C26c20 colon adenocarcinoma cells or recombinant LIF administration in the absence or presence of JAK inhibitors. Blood, adipose, and hypothalamic tissues were collected and processed for cyto/adipokine ELISAs, immunoblot analysis, and quantitative RT-PCR. CX was induced in vitro by stimulating differentiated adipocytes with recombinant LIF or IL-6 in the absence or presence of lipase or JAK inhibitors. These activated adipocytes were processed for lipolysis, immunoblot analysis, and RT-PCR. ResultsTumor-secreted LIF induced changes in adipose tissue expression and serum levels of IL-6 and leptin in a JAK-dependent manner influencing CX-associated adipose wasting and anorexia. We identified two JAK inhibitors that block cytokine-mediated adipocyte lipolysis and IL-6 induction using an in vitro CX lipolysis assay. JAK inhibitors administered to in vivo colon cancer CX mouse models led to 1) a decrease in STAT3 phosphorylation in hypothalamic and adipose tissues, 2) a reverse in the CX serum cyto/adipokine signature, 3) a delay in colon cancer CX-associated anorexia and adipose loss, and 4) an improvement in overall survival. ConclusionsJAK inhibitors suppress cytokine-associated adipose loss and anorexia in multiple in vitro and in vivo models of cancer CX.

cancer biology↗

PulseDIA: in-depth data independent acquisition mass spectrometry using enhanced gas phase fractionation

An inherent bottleneck of data independent acquisition (DIA) analysis by Orbitrap-based mass spectrometers is the relatively large window width due to the relatively slow scanning rate compared to TOF. Here we present a novel gas phase separation and MS acquisition method called PulseDIA-MS, which improves the specificity and sensitivity of Orbitrap-based DIA analysis. This is achieved by dividing the ordinary DIA-MS analysis covering the entire mass range into multiple injections for DIA-MS analyses with complementary windows. Using standard HeLa digests, the PulseDIA method identified 69,530 peptide precursors from 9,337 protein groups with ten MS injections of 30 min LC gradient. The PulseDIA scheme containing two complementary windows led to the highest gain of peptide and protein identifications per time unit compared to the conventional 30 min DIA method. We further applied the method to profile the proteome of 18 cholangiocarcinoma (CCA) tissue samples (benign and malignant) from nine patients. PulseDIA identified 7,796 protein groups in these CCA samples, with 14% increase of protein identifications, compared to the conventional DIA method. The missing value for protein matrix dropped by 7% with PulseDIA acquisition. 681 proteins were significantly dysregulated in tumorous CCA samples. Together, we presented and benchmarked an alternative DIA method with higher sensitivity and lower missing rate.

cancer biology↗

A SAC phosphoinositide phosphatase controls rice development via hydrolyzing phosphatidylinositol 4-phosphate and phosphatidylinositol 4,5-bisphosphate

Phosphoinositides (PIs) as regulatory membrane lipids play essential roles in multiple cellular processes. Although the exact molecular targets of PIs-dependent modulation remain largely elusive, the effects of disturbed PIs metabolism could be employed to propose regulatory modules associated with particular downstream targets of PIs. Here, we identified the role of GRAIN NUMBER AND PLANT HEIGHT 1 (GH1), which encodes a suppressor of actin (SAC) domain-containing phosphatase with unknown function in rice. Endoplasmic reticulum-localized GH1 specifically dephosphorylated and hydrolyzed phosphatidylinositol 4-phosphate (PI4P) and phosphatidylinositol 4,5-bisphosphate [PI(4,5)P2]. Inactivation of GH1 resulted in massive accumulation of both PI4P and PI(4,5)P2, while excessive GH1 caused their depletion. Notably, superabundant PI4P and PI(4,5)P2 could both disrupt actin cytoskeleton organization and suppress cell elongation. Interestingly, both PI4P and PI(4,5)P2 inhibited actin-related proteins 2 and 3 (Arp2/3) complex-nucleated actin branching networks in vitro, whereas PI(4,5)P2 showed more dramatic effect in a dose-dependent manner. Overall, the overaccumulation of PI(4,5)P2 resulted from dysfunction of SAC phosphatase possibly perturbs Arp2/3 complex-mediated actin polymerization, thereby disordering the cell development. These findings imply that Arp2/3 complex might be the potential molecular target of PI(4,5)P2-dependent modulation in eukaryotes, thereby providing new insights into the relationship between PIs homeostasis and plants growth and development.

plant biology↗

The microstructure investigation of plant architecture with X-ray microscopy

BackgroundIn recent years, the plant morphology has been well studied by multiple approaches at cellular and subcellular levels. Two-dimensional (2D) microscopy techniques offer imaging of plant structures on a wide range of magnifications for researchers. However, subcellular imaging is still challenging in plant tissues like roots and seeds.\n\nResultsHere we use a three-dimensional (3D) imaging technology based on the ZEISS X-ray microscope (XRM) Versa and analyze several plant tissues from different plant species. The XRM provides new insights into plant structures using non-destructive imaging at high-resolution and high contrast. We also developed a workflow aiming to acquire accurate and high-quality images in the context of the whole specimen. Multiple plant samples including rice, tobacco, Arabidopsis and maize were used to display the differences of phenotypes, which indicates that the XRM is a powerful tool to investigate plant microstructure.\n\nConclusionsOur work provides a novel observation method to evaluate and quantify tissue specific differences for a range of plant species. This new tool is suitable for non-destructive seed observation and screening.

plant biology↗

Melanoblast transcriptome analysis reveals novel pathways promoting melanoma metastasis

Cutaneous malignant melanoma is an aggressive cancer of melanocytes with a strong propensity to metastasize. We posited that melanoma cells acquire metastatic capability by adopting an embryonic-like phenotype, and that a lineage approach would uncover novel metastatic melanoma biology. We used a genetically engineered mouse model to generate a rich melanoblast transcriptome dataset, identified melanoblast-specific genes whose expression contributed to metastatic competence, and derived a 43-gene signature that predicted patient survival. We identified a melanoblast gene, KDELR3, whose loss impaired experimental metastasis. In contrast, KDELR1 deficiency enhanced metastasis, providing the first example of different disease etiologies within the KDELR-family of retrograde transporters. We show that KDELR3 regulates the metastasis suppressor, KAI1, and report an interaction with the E3 ubiquitin-protein ligase gp78, a regulator of KAI1 degradation. Our work demonstrates that the melanoblast transcriptome can be mined to uncover novel targetable pathways for melanoma therapy.

cancer biology↗

Discovery and Multi-center Verification of Prostate Cancer Protein Biomarkers using Single-shot Short Gradient Microflow SWATH and MRMHR Mass Spectrometry

We report and evaluated a microflow, single-shot, short gradient SWATH MS method intended to accelerate the discovery and verification of protein biomarkers in clinical specimens. The method uses 15-min gradient microflow-LC peptide separation, an optimized SWATH MS window configuration and OpenSWATH software for data analysis.\n\nWe applied the method to a cohort 204 of FFPE prostate tissue samples from 58 prostate cancer patients and 10 prostatic hyperplasia patients. Altogether we identified 27,976 proteotypic peptides and 4,043 SwissProt proteins from these 204 samples. Compared to a reference SWATH method with 2-hour gradient the accelerated method consumed only 27% instrument time, quantified 80% proteins and showed reduced batch effects. 3,800 proteins were quantified by both methods in two different instruments with relatively high consistency (r = 0.77). 75 proteins detected by the accelerated method with differential abundance between clinical groups were selected for further validation. A shortlist of 134 selected peptide precursors from the 75 proteins were analyzed using MRM-HR, exhibiting high quantitative consistency with the 15-min SWATH method (r = 0.89) in the same sample set. We further verified the capacity of these 75 proteins in separating benign and malignant tissues (AUC = 0.99) in an independent prostate cancer cohort (n=154).\n\nOverall our data show that the single-shot short gradient microflow-LC SWATH MS method achieved about 4-fold acceleration of data acquisition with reduced batch effect and a moderate level of protein attrition compared to a standard SWATH acquisition method. Finally, the results showed comparable ability to separate clinical groups.

cancer biology↗

Arabidopsis Proteome and the Mass Spectral Assay Library

Arabidopsis is an important model organism and the first plant with its genome sequenced. Knowledge from studying this species has either direct or indirect applications to agriculture and human health. Quantitative proteomics by data-independent acquisition (SWATH/DIA-MS) was recently developed and considered as a high-throughput targetedlike approach for accurate proteome quantitation. In this approach, a high-quality and comprehensive library is a prerequisite. Here, we generated a protein expression atlas of 10 organs of Arabidopsis and created a library consisting of 15,514 protein groups, 187,265 unique peptide sequences, and 278,278 precursors. The identified protein groups correspond to ~56.5% of the predicted proteome. Further proteogenomics analysis identified 28 novel proteins. We subsequently applied DIA-mass spectrometry using this library to quantify the effect of abscisic acid on Arabidopsis. We were able to recover 8,793 protein groups with 1,787 of them being differentially expressed which includes 65 proteins known to respond to abscisic acid stress. Mass spectrometry data are available via ProteomeXchange with identifier PXD012710 for data-dependent acquisition and PXD014032 for DIA analyses.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1a3f799org.highwire.dtl.DTLVardef@1d4711dorg.highwire.dtl.DTLVardef@4e3f73org.highwire.dtl.DTLVardef@127a9a4org.highwire.dtl.DTLVardef@f254bb_HPS_FORMAT_FIGEXP M_TBL C_TBL

plant biology↗

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 one to 15 years in a biobank and show a high degree of the proteome pattern similarity between two types histological region of small FFPE samples, i.e. punched tissue biopsies and thin tissue sections of micrometer thickness, despite the existence of certain degree of biological variations. Applying the method to two independent DLBCL cohorts we identified myeloperoxidase (MPO), 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.

biochemistry↗

Managing congestion at visitor hotspots using park-level use level data: Case study of a Chinese World Heritage site

Tourist congestion at hot spots has been a major management concern for UNESCO World Heritage Sites and other iconic protected areas. A growing number of heritage sites employ technologies, such as cameras and electronic ticket-checking systems, to monitor user levels, but data collected by these monitoring technologies are often under-utilize. In this study, we illustrated how to integrate data from hot spots by camera-captured monitoring and entrance counts to manage use levels at a World Heritage Site in southeastern China. 6,930 photos of a congestion hotspot (scenic outlook on a trail) were collected within the park at a 10-minute interval over 105 days from January to November 2017. The entrance counts were used to predict daily average and maximum use level at the hotspot Average use level at the congestion hotspot did not exceed the use limit mandated by the Chinese park administration agency. However, from 9:20 am to 12:00 pm, the use level at hotspots exceeded visitor preferred use level. Visitor use level was significantly higher at the hotspot during a major Chinese \"golden week\" holiday. The daily entrance counts significantly predicted the average and maximum use level at the hotspot. Based on our findings, we recommend that the number of visitors entering the gate on each day should be less than 28,764 for the hotspots to meet use level mandates, while less than 6,245 to meet visitor preference. The gap manifested the complexity in visitor capacity management at high-use World Heritage Sites and other protected areas and calls for innovative monitoring and management strategies.

ecology↗

Identification of protein abundance changes in biopsy-level hepatocellular carcinoma tissues using PCT-SWATH

In this study, we optimized the pressure-cycling technology (PCT) and SWATH mass spectrometry workflow to analyze biopsy-level tissue samples (2 mg wet weight) from 19 hepatocellular carcinoma (HCC) patients. Using OpenSWATH and pan-human spectral library, we quantified 11,787 proteotypic peptides from 2,579 SwissProt proteins in 76 HCC tissue samples within about 9 working days (from receiving tissue to SWATH data). The coefficient of variation (CV) of peptide yield using PCT was 32.9%, and the R2 of peptide quantification was 0.9729. We identified protein changes in malignant tissues compared to matched control samples in HCC patients, and further stratified patient samples into groups with high -fetoprotein (AFP) expression or HBV infection. In aggregate, the data identified 23 upregulated pathways and 13 ones. We observed enhanced biomolecule synthesis and suppressed small molecular metabolism in liver tumor tissues. 16 proteins of high documented relevance to HCC are highlighted in our data. We also identified changes of virus-infection-related proteins including PKM, CTPS1 and ALDOB in the HBV+ HCC subcohort. In conclusion, we demonstrate the practicality of performing proteomic analysis of biopsy-level tissue samples with PCT-SWATH methodology with moderate effort and within a relatively short timeframe.

systems biology↗

Myricetin Attenuates LPS-induced Inflammation in RAW 264.7 Macrophages and Mouse Models

BackgroundMyricetin has been demonstrated to inhibit inflammation in a variety of diseases, but little is known about its characters in acute lung injury (ALI). In this study, we aimed to investigate the protective effects of myricetin on inflammation in lipopolysaccharide (LPS)-stimulated RAW 264.7 cells and a LPS-induced lung injury model.\n\nMethodsSpecifically, we investigated its effects on lung edema and histological damage by lung W/D weight ratio, HE staining and Evans Blue dye. Then macrophage activation was detected by evaluating the TNF-, IL-6 and IL-1{beta} mRNA and protein iNOS and COX-2. Myricetin was used to detect the impact on the inflammatory responses in LPS-induced RAW264.7 cells with the same manners in mouse model. Finally, NF-{kappa}B and MAPK signaling pathways were investigated with Western blot assay in LPS-induced RAW264.7 cells.\n\nResultsMyricetin significantly inhibited the production of the pro-inflammatory cytokines in vitro and in vivo. The in vivo experiments showed that pretreatment with Myricetin markedly attenuated the development of pulmonary edema, histological severities and macrophage activation in mice with ALI. The underlying mechanisms were further demonstrated in vitro that myricetin exerted an anti-inflammatory effect through suppressing the NF-{kappa}B p65 and AKT activation in NF-{kappa}B pathway and JNK, p-ERK and p38 in mitogen-activated protein kinases signaling pathway.\n\nConclusionMyricetin alleviated ALI by inhibiting macrophage activation, and inhibited inflammation in vitro and in vivo. It may be a potential therapeutic candidate for the prevention of inflammatory diseases.

cell biology↗

Colonization of phosphate-solubilizing Pseudomonas sp. strain P34-L in the wheat rhizosphere and its effects on wheat growth and the expression of phosphate transporter gene TaPT4 in wheat

The ability to colonize the rhizosphere is an important basics requirement for field application of plant growth-promoting rhizobacteria (PGPR) strains. There are complex signal exchanges and mutual recognition between microbes and plants. In this study, phosphate-solubilizing Pseudomonas sp. P34, a PGPR strain with affinity to wheat, was isolated from the wheat rhizosphere by wheat germ agglutinin (WGA). The plasmid pTR102 harboring the luciferase luxAB gene was transferred into P34 to create P34-L. The labeled strain was used to track the temporal and spatial characteristics of colonization in wheat rhizosphere and its effects on wheat development. The transcript level of phosphate transporter gene TaPT4, a phosphorus deficiency indicator gene, in wheat roots was monitored by quantitative reverse-transcription PCR. The experimental results indicated that there was a high density of stain P34-L within the top 8-cm depth of the wheat rhizosphere on day 36 of wheat growth. The strain could survive in the wheat rhizosphere for a long time, and colonize new spaces in wheat rhizosphere following the extension of wheat roots. Compared with uninoculated wheat plants, those inoculated with P34-L showed significantly increased phosphorus accumulation in leaves, seedling fresh and dry weight, root fresh and dry weight, total root length, and number of root tips, forks, crossings, which showed a great value of application of the strain on wheat production by promoting the root growth and dry matter accumulation. Strain P34-L down-regulated the transcript level of TaPT4 in wheat roots, which means a well phosphorus supplementation environment was established by P34-L.\n\nImportanceMany PGPR strains often failed to achieve the desired effects when applied in the field. One major reason for the failure is lack of a special affinity between a certain strain and the target host plant, so those strains have low competitive ability with the indigenous microorganism, and unable to survive constantly in rhizosphere. In this work, a new technique to isolate wheat-specific phosphate-solubilizing PGPR strain by WGA was established. The isolate P34 was confirmed can colonize the wheat rhizosphere, and have significantly ability in promoting phosphorus absorption and wheat growth by luminescence labeling techniques. Furthermore, the phosphate-solubilizing ability of this affinity PGPR strain was verified in gene level by quantitative reverse-transcription PCR. These results lay a firm foundation for further research on the relationships between PGPR and their host plants. Meanwhile, this work supplied a potential ideal biofertilizer producing strain for sustainable agriculture.

microbiology↗

Rapid proteotyping reveals cancer biology and drug response determinants in the NCI-60 cells

We describe the rapid and reproducible acquisition of quantitative proteome maps for the NCI-60 cancer cell lines and their use to reveal cancer biology and drug response determinants. Proteome datasets for the 60 cell lines were acquired in duplicate within 30 working days using pressure cycling technology and SWATH mass spectrometry. We consistently quantified 3,171 proteotypic proteins annotated in the SwissProt database across all cell lines, generating a data matrix with 0.1% missing values, allowing analyses of protein complexes and pathway activities across all the cancer cells. Systematic and integrative analysis of the genetic variation, mRNA expression and proteomic data of the NCI-60 cancer cell lines uncovered complementarity between different types of molecular data in the prediction of the response to 240 drugs. We additionally identified novel proteomic drug response determinants for clinically relevant chemotherapeutic and targeted therapies. We anticipate that this study represents a significant advance toward the translational application of proteotypes, which reveal biological insights that are easily missed in the absence of proteomic data.

systems biology↗

Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers

Many tumors are characterized by large genomic heterogeneity and it remains unclear to what extent this impacts on protein biomarker discovery. Here, we quantified proteome intra-tissue heterogeneity (ITH) based on a multi-region analysis of 30 biopsy-scale prostate tissues using pressure cycling technology and SWATH mass spectrometry. We quantified 8,248 proteins and analyzed the ITH of 3,700 proteins. The level of ITH varied significantly depending on proteins and tissue types. Benign tissues exhibited generally more complex ITH patterns than malignant tissues. Spatial variability of ten prostate biomarkers was further validated by immunohistochemistry in an independent cohort (n=83) using tissue microarrays. PSA was preferentially variable in benign prostatic hyperplasia, while GDF15 substantially varied in prostate adenocarcinomas. Further, we found that DNA repair pathways exhibited a high degree of variability in tumorous tissues, which may contribute to the genetic heterogeneity of tumors. This study conceptually adds a new perspective to protein biomarker discovery by quantifying spatial proteome variation and it demonstrates the feasibility by exploiting recent technological progress.

systems biology↗

Splice Expression Variation Analysis (SEVA) for Differential Gene Isoform Usage in Cancer

MotivationCurrent bioinformatics methods to detect changes in gene isoform usage in distinct phenotypes compare the relative expected isoform usage in phenotypes. These statistics model differences in isoform usage in normal tissues, which have stable regulation of gene splicing. Pathological conditions, such as cancer, can have broken regulation of splicing that increases the heterogeneity of the expression of splice variants. Inferring events with such differential heterogeneity in gene isoform usage requires new statistical approaches.\n\nResultsWe introduce Splice Expression Variability Analysis (SEVA) to model increased heterogeneity of splice variant usage between conditions (e.g., tumor and normal samples). SEVA uses a rank-based multivariate statistic that compares the variability of junction expression profiles within one condition to the variability within another. Simulated data show that SEVA is unique in modeling heterogeneity of gene isoform usage, and benchmark SEVAs performance against EBSeq, DiffSplice, and rMATS that model differential isoform usage instead of heterogeneity. We confirm the accuracy of SEVAin identifying known splice variants in head and neck cancer and perform cross-study validation of novel splice variants. A novel comparison of splice variant heterogeneity between subtypes of head and neck cancer demonstrated unanticipated similarity between the heterogeneity of gene isoform usage in HPV-positive and HPV-negative subtypes and anticipated increased heterogeneity among HPV-negative samples with mutations in genes that regulate the splice variant machinery.\n\nConclusionThese results show that SEVA accurately models differential heterogeneity of gene isoform usage from RNA-seq data.\n\nAvailabilitySEVA is implemented in the R/Bioconductor package GSReg.\n\nContactbahman@jhu.edu, favorov@sensi.org, ejfertig@jhmi.edu

genomics↗

PatternMarkers and Genome-Wide CoGAPS Analysis in Parallel Sets (GWCoGAPS) for data-driven detection of novel biomarkers via whole transcriptome Non-negative matrix factorization (NMF)

SummaryNon-negative Matrix Factorization (NMF) algorithms associate gene expression with biological processes (e.g., time-course dynamics or disease subtypes). Compared with univariate associations, the relative weights of NMF solutions can obscure biomarkers. Therefore, we developed a novel PatternMarkers statistic to extract genes for biological validation and enhanced visualization of NMF results. Finding novel and unbiased gene markers with PatternMarkers requires whole-genome data. However, NMF algorithms typically do not converge for the tens of thousands of genes in genome-wide profiling. Therefore, we also developed Genome-Wide CoGAPS Analysis in Parallel Sets (GWCoGAPS), the first robust whole genome Bayesian NMF using the sparse, MCMC algorithm, CoGAPS. This software contains analytic and visualization tools including a Shiny web application, patternMatcher, which are generalized for any NMF. Using these tools, we find granular brain-region and cell-type specific signatures with corresponding biomarkers in GTex data, illustrating GWCoGAPS and patternMarkers ascertainment of data-driven biomarkers from whole-genome data.\n\nAvailabilityPatternMarkers & GWCoGAPS are in the CoGAPS Bioconductor package (3.5) under the GPL license.\n\nContactgsteinobrien@jhmi.edu; ccolantu@jhmi.edu; ejfertig@jhmi.edu

bioinformatics↗