Systematic analyses of the transcriptome, translatome, and proteome provide a global view and potential strategy for the C-HPP

Targeting the Neuro-vascular Presynaptic Signalling in STROKE: Evidence and Therapeutic Implications

Background

Stroke is one of the leading causes of death and long-term adult disability worldwide. Stroke causes neurodegeneration and impairs synaptic function. Understanding the role of synaptic proteins and associated signalling pathways in stroke pathology could offer insights into therapeutic approaches as well as improving rehabilitation-related treatment regimes.

Purpose

The current study aims to analyse synaptic transcriptome changes in acute and long-term post-stroke (1 day, 7 day timepoints), especially focusing on pre- and postsynaptic genes.

Methods

We performed data mining of the recent mRNA sequence from isolated mouse brain micro-vessels (MBMVs) after transient middle cerebral artery occlusion (tMCAO) stroke model. Using the SynGO (Synaptic Gene Ontologies and annotations) bioinformatics platform we assessed synaptic protein expression and associated pathways, and compared synaptic protein changes at 1 day and 7 day post-stroke.

Results

Enrichment analysis of the MBMVs identified significant alterations in the expression of genes related to synaptic physiology, synaptic transmission, neuronal structure, and organisation. We identified that the synaptic changes observed at the 7 day timepoint were initiated by the regulation of specific presynaptic candidates 1 day (24h) post-stroke, highlighting the significance of presynaptic regulation in mediating organising of synaptic structures and physiology. Analysis of transcriptomic data from human postmortem stroke brains confirmed similar presynaptic signalling patterns.

Conclusion

Our findings identify the changes in presynaptic gene regulation in micro-vessels following ischaemic stroke. Targeting presynaptic active zone protein signalling could represent a promising therapeutic target in mitigating ischaemic stroke.

The Translatome Map: RNC-Seq vs. Ribo-Seq for Profiling of HBE, A549, and MCF-7 Cell Lines

Gene expression is a tightly regulated process that involves multiple layers of control, including transcriptional, post-transcriptional, and translational regulation. To gain a comprehensive understanding of gene expression dynamics and its functional implications, it is crucial to compare translatomic, transcriptomic, and proteomic data. The two most common analysis methods, Ribo-seq and RNC-Seq, were used to analyze the translatome of the same sample, whose datasets were downloaded from the TranslatomeDB database. The resulting translatome maps obtained for three cell lines (HBE, A549, and MCF-7) using these two methods were comparatively analyzed. The two methods of translatome analysis were shown to provide comparable results and can be used interchangeably. The obtained mRNA translation patterns were annotated in the transcriptome and proteome context for the same sample, which may become the basis for the reconstruction of the molecular mechanisms of pathological process development in the future.

Inhibition of DNMT1 methyltransferase activity via glucose-regulated O-GlcNAcylation alters the epigenome

The DNA methyltransferase activity of DNMT1 is vital for genomic maintenance of DNA methylation. We report here that DNMT1 function is regulated by O-GlcNAcylation, a protein modification that is sensitive to glucose levels, and that elevated O-GlcNAcylation of DNMT1 from high glucose environment leads to alterations to the epigenome. Using mass spectrometry and complementary alanine mutation experiments, we identified S878 as the major residue that is O-GlcNAcylated on human DNMT1. Functional studies in human and mouse cells further revealed that O-GlcNAcylation of DNMT1-S878 results in an inhibition of methyltransferase activity, resulting in a general loss of DNA methylation that preferentially occurs at partially methylated domains (PMDs). This loss of methylation corresponds with an increase in DNA damage and apoptosis. These results establish O-GlcNAcylation of DNMT1 as a mechanism through which the epigenome is regulated by glucose metabolism and implicates a role for glycosylation of DNMT1 in metabolic diseases characterized by hyperglycemia.

A multi-omics dataset of human transcriptome and proteome stable reference

The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the accuracy and reproducibility of omics workflows. The transcriptome and proteome of most cell lines shift during culturing, which limits their applicability as standard samples. In this study, we demonstrated that the human hepatocellular cell line MHCC97H has a very stable transcriptome (r = 0.983~0.997) and proteome (r = 0.966~0.988 for data-dependent acquisition, r = 0.970~0.994 for data-independent acquisition) after 9 subculturing generations, which allows this steady standard sample to be consistently produced on an industrial scale in long term. Moreover, this stability was maintained across labs and platforms. In sum, our study provides omics standard reference material and reference datasets for transcriptomic and proteomics research. This helps to further standardize the workflow and data quality of omics techniques and thus promotes the application of omics technology in precision medicine.

Functional Peptides Encoded by Long Non-Coding RNAs in Gastrointestinal Cancer

Gastrointestinal cancer is by far the most common malignancy and the most common cause of cancer-related deaths worldwide. Recent studies have shown that long non-coding RNAs (lncRNAs) play an important role in the epigenetic regulation of cancer cells and regulate tumor progression by affecting chromatin modifications, gene transcription, translation, and sponge to miRNAs. In particular, lncRNA has recently been found to possess open reading frame (ORF), which can encode functional small peptides or proteins. These peptides interact with its targets to regulate transcription or the signal axis, thus promoting or inhibiting the occurrence and development of tumors. In this review, we summarize the involvement of lncRNAs and the function of lncRNAs encoded small peptides in gastrointestinal cancer.

Extensive Translational Regulation through the Proliferative Transition of Trypanosoma cruzi Revealed by Multi-Omics

Trypanosoma cruzi is the etiological agent for Chagas disease, a neglected parasitic disease in Latin America. Gene transcription control governs the eukaryotic cell replication but is absent in trypanosomatids; thus, it must be replaced by posttranscriptional regulatory events. We investigated the entrance into the T. cruzi replicative cycle using ribosome profiling and proteomics on G₁/S epimastigote cultures synchronized with hydroxyurea. We identified 1,784 translationally regulated genes (change > 2, false-discovery rate [FDR] < 0.05) and 653 differentially expressed proteins (change > 1.5, FDR < 0.05), respectively. A major translational remodeling accompanied by an extensive proteome change is found, while the transcriptome remains largely unperturbed at the replicative entrance of the cell cycle. The differentially expressed genes comprise specific cell cycle processes, confirming previous findings while revealing candidate cell cycle regulators that undergo previously unnoticed translational regulation. Clusters of genes showing a coordinated regulation at translation and protein abundance share related biological functions such as cytoskeleton organization and mitochondrial metabolism; thus, they may represent posttranscriptional regulons. The translatome and proteome of the coregulated clusters change in both coupled and uncoupled directions, suggesting that complex cross talk between the two processes is required to achieve adequate protein levels of different regulons. This is the first simultaneous assessment of the transcriptome, translatome, and proteome of trypanosomatids, which represent a paradigm for the absence of transcriptional control. The findings suggest that gene expression chronology along the T. cruzi cell cycle is controlled mainly by translatome and proteome changes coordinated using different mechanisms for specific gene groups. IMPORTANCE Trypanosoma cruzi is an ancient eukaryotic unicellular parasite causing Chagas disease, a potentially life-threatening illness that affects 6 to 7 million people, mostly in Latin America. The antiparasitic treatments for the disease have incomplete efficacy and adverse reactions; thus, improved drugs are needed. We study the mechanisms governing the replication of the parasite, aiming to find differences with the human host, valuable for the development of parasite-specific antiproliferative drugs. Transcriptional regulation is essential for replication in most eukaryotes, but in trypanosomatids, it must be replaced by subsequent gene regulation steps since they lack transcription initiation control. We identified the genome-wide remodeling of mRNA translation and protein abundance during the entrance to the replicative phase of the cell cycle. We found that translation is strongly regulated, causing variation in protein levels of specific cell cycle processes, representing the first simultaneous study of the translatome and proteome in trypanosomatids.

Combinatorial peptides: A library that continuously probes low-abundance proteins

After a decade of experimental applications, it is the objective of this review to make a point on combinatorial peptide ligand libraries dedicated to low-abundance proteins from animals to plants and to microorganism proteomics. It is, thus, at the light of the recent technical developments and applications that we will examine the state of the art, its usage within the scientific community, and its openness to unexplored fields. The improvements of the methodology and its implementation in connection with analytical determinations of combinatorial peptide ligand library (CPLL)-treated samples are extensively reviewed and commented upon. Relevant examples covering few critical aspects describe the performance of the technology. Finally, a reflection on the technological future is attempted in particular by involving new concepts adapted to the limited availability of certain biological samples.

The Ultrafast and Accurate Mapping Algorithm FANSe3: Mapping a Human Whole-Genome Sequencing Dataset Within 30 Minutes

Aligning billions of reads generated by the next-generation sequencing (NGS) to reference sequences, termed "mapping", is the time-consuming and computationally-intensive process in most NGS applications. A Fast, accurate and robust mapping algorithm is highly needed. Therefore, we developed the FANSe3 mapping algorithm, which can map a 30 × human whole-genome sequencing (WGS) dataset within 30 min, a 50 × human whole exome sequencing (WES) dataset within 30 s, and a typical mRNA-seq dataset within seconds in a single-server node without the need for any hardware acceleration feature. Like its predecessor FANSe2, the error rate of FANSe3 can be kept as low as 10^-9 in most cases, this is more robust than the Burrows-Wheeler transform-based algorithms. Error allowance hardly affected the identification of a driver somatic mutation in clinically relevant WGS data and provided robust gene expression profiles regardless of the parameter settings and sequencer used. The novel algorithm, designed for high-performance cloud-computing after infrastructures, will break the bottleneck of speed and accuracy in NGS data analysis and promote NGS applications in various fields. The FANSe3 algorithm can be downloaded from the website: http://www.chi-biotech.com/fanse3/.

Mass-Spectrometry-Based Near-Complete Draft of the Saccharomyces cerevisiae Proteome

Proteomics approaches designed to catalogue all open reading frames (ORFs) under a defined set of growth conditions of an organism have flourished in recent years. However, no proteome has been sequenced completely so far. Here, we generate the largest yeast proteome data set, including 5610 identified proteins, using a strategy based on optimized sample preparation and high-resolution mass spectrometry. Among the 5610 identified proteins, 94.1% are core proteins, which achieves near-complete coverage of the yeast ORFs. Comprehensive analysis of missing proteins showed that proteins are missed mainly due to physical properties. A review of protein abundance shows that our proteome encompasses a uniquely broad dynamic range. Additionally, these values highly correlate with mRNA abundance, implying a high level of accuracy, sensitivity, and precision. We present examples of how the data could be used, including reannotating gene localization, providing expression evidence of pseudogenes. Our near-complete yeast proteome data set will be a useful and important resource for further systematic studies.

Trastuzumab-induced upregulation of a protein set in extracellular vesicles emitted by ErbB2-positive breast cancer cells correlates with their trastuzumab sensitivity

Background

ErbB2/HER2 oncoprotein often drives breast cancers (BCs) which are treated with the anti-ErbB2 antibody trastuzumab. The efficacy of trastuzumab-based metastatic BC therapies is routinely assessed by imaging studies. Trastuzumab typically becomes ineffective in the case of this disease and is then replaced by other drugs. Biomarkers of BC trastuzumab response could allow imaging studies and the switch to other drugs to occur earlier than is now possible. Moreover, bone-only BC metastases can be hard to measure, and biomarkers of their trastuzumab response could facilitate further treatment decisions. Such biomarkers are presently unavailable. In this study, we searched for proteins whose levels in BC cell-emitted extracellular vesicles (EVs) potentially correlate with BC trastuzumab sensitivity.

Methods

We isolated EVs from cultured trastuzumab-sensitive and trastuzumab-resistant human BC cells before and after trastuzumab treatment and characterized these EVs by nanoparticle tracking analysis and electron microscopy. We found previously that ErbB2 drives BC by downregulating a pro-apoptotic protein PERP. We now tested whether trastuzumab-induced PERP upregulation in EVs emitted by cultured human BC cells correlates with their trastuzumab sensitivity. We also used mass spectrometry to search for additional proteins whose levels in such EVs reflect BC cell trastuzumab sensitivity. Once we identified proteins whose EV levels correlate with this sensitivity in culture, we explored the feasibility of testing whether their levels in the blood EVs of trastuzumab-treated metastatic BC patients correlate with patients’ response to trastuzumab-based treatments.

Results

We found that neither trastuzumab nor acquisition of trastuzumab resistance by BC cells affects the size or morphology of EVs emitted by cultured BC cells. We established that EV levels of proteins PERP, GNAS2, GNA13, ITB1, and RAB10 correlate with BC cell trastuzumab response. Moreover, these proteins were upregulated during trastuzumab-based therapies in the blood EVs of a pilot cohort of metastatic BC patients that benefited from these therapies but not in those derived from patients that failed such treatments.

Conclusions

Upregulation of a protein set in EVs derived from cultured breast tumor cells correlates with tumor cell trastuzumab sensitivity. It is feasible to further evaluate these proteins as biomarkers of metastatic BC trastuzumab response.

Understanding the proteome encoded by "non-coding RNAs": new insights into human genome

A great number of non-coding RNAs (ncRNAs) account for the majority of the genome. The translation of these ncRNAs has been noted but seriously underestimated due to both technological and theoretical limitations. Based on the development of ribosome profiling (Ribo-seq), full length translating RNA analysis (RNC-seq) and mass spectrometry technology, more and more ncRNAs are being found to be translated in different organism, and some of them can produce functional peptides. While recently, not only individual new functional proteins, but also a new proteome have been experimentally discovered to be encoded by endogenous lncRNAs and circRNAs. These new proteins are of biological significance, suggesting the connection of the translation of ncRNAs to human physiology and diseases. Therefore, an in-depth and systematic understanding of the coding capabilities of ncRNAs is necessary for basic biology and medicine. In this review, we summarize the advances in the field of discovering this new proteome, i.e. "ncRNA-coded" proteins.

A hidden human proteome encoded by 'non-coding' genes

It has been a long debate whether the 98% ‘non-coding’ fraction of human genome can encode functional proteins besides short peptides. With full-length translating mRNA sequencing and ribosome profiling, we found that up to 3330 long non-coding RNAs (lncRNAs) were bound to ribosomes with active translation elongation. With shotgun proteomics, 308 lncRNA-encoded new proteins were detected. A total of 207 unique peptides of these new proteins were verified by multiple reaction monitoring (MRM) and/or parallel reaction monitoring (PRM); and 10 new proteins were verified by immunoblotting. We found that these new proteins deviated from the canonical proteins with various physical and chemical properties, and emerged mostly in primates during evolution. We further deduced the protein functions by the assays of translation efficiency, RNA folding and intracellular localizations. As the new protein UBAP1-AST6 is localized in the nucleoli and is preferentially expressed by lung cancer cell lines, we biologically verified that it has a function associated with cell proliferation. In sum, we experimentally evidenced a hidden human functional proteome encoded by purported lncRNAs, suggesting a resource for annotating new human proteins.

TranslatomeDB: a comprehensive database and cloud-based analysis platform for translatome sequencing data

Translation is a key regulatory step, linking transcriptome and proteome. Two major methods of translatome investigations are RNC-seq (sequencing of translating mRNA) and Ribo-seq (ribosome profiling). To facilitate the investigation of translation, we built a comprehensive database TranslatomeDB (http://www.translatomedb.net/) which provides collection and integrated analysis of published and user-generated translatome sequencing data. The current version includes 2453 Ribo-seq, 10 RNC-seq and their 1394 corresponding mRNA-seq datasets in 13 species. The database emphasizes the analysis functions in addition to the dataset collections. Differential gene expression (DGE) analysis can be performed between any two datasets of same species and type, both on transcriptome and translatome levels. The translation indices translation ratios, elongation velocity index and translational efficiency can be calculated to quantitatively evaluate translational initiation efficiency and elongation velocity, respectively. All datasets were analyzed using a unified, robust, accurate and experimentally-verifiable pipeline based on the FANSe3 mapping algorithm and edgeR for DGE analyzes. TranslatomeDB also allows users to upload their own datasets and utilize the identical unified pipeline to analyze their data. We believe that our TranslatomeDB is a comprehensive platform and knowledgebase on translatome and proteome research, releasing the biologists from complex searching, analyzing and comparing huge sequencing data without needing local computational power.

Translatomics: The Global View of Translation

In all kingdoms of life, proteins are synthesized by ribosomes in a process referred to as translation. The amplitude of translational regulation exceeds the sum of transcription, mRNA degradation and protein degradation. Therefore, it is essential to investigate translation in a global scale. Like the other “omics”-methods, translatomics investigates the totality of the components in the translation process, including but not limited to translating mRNAs, ribosomes, tRNAs, regulatory RNAs and nascent polypeptide chains. Technical advances in recent years have brought breakthroughs in the investigation of these components at global scale, both for their composition and dynamics. These methods have been applied in a rapidly increasing number of studies to reveal multifaceted aspects of translation control. The process of translation is not restricted to the conversion of mRNA coding sequences into polypeptide chains, it also controls the composition of the proteome in a delicate and responsive way. Therefore, translatomics has extended its unique and innovative power to many fields including proteomics, cancer research, bacterial stress response, biological rhythmicity and plant biology. Rational design in translation can enhance recombinant protein production for thousands of times. This brief review summarizes the main state-of-the-art methods of translatomics, highlights recent discoveries made in this field and introduces applications of translatomics on basic biological and biomedical research.

Metabolomics study of the therapeutic mechanism of a Chinese herbal formula on collagen-induced arthritis mice

Wenjinghuoluo (WJHL) prescription, the typical rheumatoid arthritis (RA) treatment compound in traditional Chinese medicine, shows favorable efficacy. The precise mechanism of WJHL on RA therapy is yet to be elucidated. This study aimed to determine the metabolic biomarkers in the early onset of RA and evaluate the regulation effect of WJHL on metabolite levels. Multivariate statistical analysis identified 93 biomarkers by precise MS/MS. These biomarkers played an important role in the regulation of key metabolic pathways associated with collagen-induced arthritis (CIA). A total of 68 biomarkers were related to the treatment of CIA by WJHL therapy. In addition, pathway analysis results showed six and three significant related pathways according to corresponding differential metabolites before and after WJHL therapy. Finally, disease and function prediction of ingenuity pathway analysis indicated that lipid metabolism, small molecule biochemistry, and carbohydrate metabolism were associated functions of WJHL therapy on CIA. Furthermore, top analysis-ready molecules of up-regulated thiamine and down-regulated arachidonic acid maybe the most related metabolites of WJHL therapy on CIA. The present work indicates that a metabolomics platform provides a new insight into understanding the mechanisms of action of natural medicines, such as WJHL.

Wenjinghuoluo (WJHL) prescription, the typical rheumatoid arthritis (RA) treatment compound in traditional Chinese medicine, shows favorable efficacy.

Multiproteases Combined with High-pH Reverse-Phase Separation Strategy Verified Fourteen Missing Proteins in Human Testis Tissue

Subsequent to conducting the Chromosome-Centric Human Proteome Project, we have focused on human testis-enriched missing proteins (MPs) since 2015. For protein coverage to be enhanced, a multiprotease strategy was used for separation of samples by 10% SDS-PAGE. For the separating efficiency to be improved, a high-pH reverse phase (RP) separation strategy was applied to fractionate complex samples in this study. A total of 11,558 proteins was identified, which is the largest proteome data set for single human tissue sample so far. On the basis of this large-scale data set, we verified 14 MPs (PE2) in neXtProt (2018-01) after spectrum quality analysis, isobaric post-translational modification, and single amino acid variant filtering, and synthesized peptide matching. Tissue expression analysis showed that 3 of 14 MPs were testis-specific proteins. Functional analysis showed that 10 of 14 MPs were closely related to liver tumor, liver carcinoma, and hepatocellular carcinoma. Another 100 MPs were listed as candidates but required additional verification information. All MS data sets have been deposited into the ProteomeXchange with the identifier PXD009737.

Cytoskeleton-centric protein transportation by exosomes transforms tumor-favorable macrophages

The exosome is a key initiator of pre-metastatic niche in numerous cancers, where macrophages serve as primary inducers of tumor microenvironment. However, the proteome that can be exosomally transported from cancer cells to macrophages has not been sufficiently characterized so far. Here, we used colorectal cancer (CRC) exosomes to educate tumor-favorable macrophages. With a SILAC-based mass spectrometry strategy, we successfully traced the proteome transported from CRC exosomes to macrophages. Such a proteome primarily focused on promoting cytoskeleton rearrangement, which was biologically validated with multiple cell lines. We reproduced the exosomal transportation of functional vimentin as a proof-of-concept example. In addition, we found that some CRC exosomes could be recognized by macrophages via Fc receptors. Therefore, we revealed the active and necessary role of exosomes secreted from CRC cells to transform cancer-favorable macrophages, with the cytoskeleton-centric proteins serving as the top functional unit.

Advances in the Chromosome-Centric Human Proteome Project: looking to the future

INTRODUCTION

The mission of the Chromosome-Centric Human Proteome Project (C-HPP), is to map and annotate the entire predicted human protein set (~20,000 proteins) encoded by each chromosome. The initial steps of the project are focused on 'missing proteins (MPs)', which lacked documented evidence for existence at protein level. In addition to remaining 2,579 MPs, we also target those annotated proteins having unknown functions, uPE1 proteins, alternative splice isoforms and post-translational modifications. We also consider how to investigate various protein functions involved in cis-regulatory phenomena, amplicons lncRNAs and smORFs. Areas covered: We will cover the scope, historic background, progress, challenges and future prospects of C-HPP. This review also addresses the question of how we can best improve the methodological approaches, select the optimal biological samples, and recommend stringent protocols for the identification and characterization of MPs. A new strategy for functional analysis of some of those annotated proteins having unknown function will also be discussed. Expert commentary: If the project moves well by reshaping the original goals, the current working modules and team work in the proposed extended planning period, it is anticipated that a progressively more detailed draft of an accurate chromosome-based proteome map will become available with functional information.

Why Are the Correlations between mRNA and Protein Levels so Low among the 275 Predicted Protein-Coding Genes on Human Chromosome 18?

In this work targeted (selected reaction monitoring, SRM, PASSEL: PASS00697) and panoramic (shotgun LC-MS/MS, PRIDE: PXD00244) mass-spectrometric methods as well as transcriptomic analysis of the same samples using RNA-Seq and PCR methods (SRA experiment IDs: SRX341198, SRX267708, SRX395473, SRX390071) were applied for quantification of chromosome 18 encoded transcripts and proteins in human liver and HepG2 cells. The obtained data was used for the estimation of quantitative mRNA-protein ratios for the 275 genes of the selected chromosome in the selected tissues. The impact of methodological limitations of existing analytical proteomic methods on gene-specific mRNA-protein ratios and possible ways of overcoming these limitations for detection of missing proteins are also discussed.

Proteomic and network analysis of human serum albuminome by integrated use of quick crosslinking and two-step precipitation

Affinity- and chemical-based methods are usually employed to prepare human serum albuminome; however, these methods remain technically challenging. Herein, we report the development of a two-step precipitation (TSP) method by combined use of polyethylene glycol (PEG) and ethanol. PEG precipitation was newly applied to remove immunoglobulin G for albuminome preparation, which is simple, cost effective, efficient and compatible with downstream ethanol precipitation. Nonetheless, chemical extraction using TSP may disrupt weak and transient protein interactions with human serum albumin (HSA) leading to an incomplete albuminome. Accordingly, rapid fixation based on formaldehyde crosslinking (FC) was introduced into the TSP procedure. The developed FC-TSP method increased the number of identified proteins, probably by favouring real-time capture of weakly bound proteins in the albuminome. A total of 171 proteins excluding HSA were identified from the fraction obtained with FC-TSP. Further interaction network and cluster analyses revealed 125 HSA-interacting proteins and 14 highly-connected clusters. Compared with five previous studies, 55 new potential albuminome proteins including five direct and 50 indirect binders were only identified by our strategy and 12 were detected as common low-abundance proteins. Thus, this new strategy has the potential to effectively survey the human albuminome, especially low-abundance proteins of clinical interest.

Integrated Translatome and Proteome: Approach for Accurate Portraying of Widespread Multifunctional Aspects of Trichoderma

Genome-wide studies of transcripts expression help in systematic monitoring of genes and allow targeting of candidate genes for future research. In contrast to relatively stable genomic data, the expression of genes is dynamic and regulated both at time and space level at different level in. The variation in the rate of translation is specific for each protein. Both the inherent nature of an mRNA molecule to be translated and the external environmental stimuli can affect the efficiency of the translation process. In biocontrol agents (BCAs), the molecular response at translational level may represents noise-like response of absolute transcript level and an adaptive response to physiological and pathological situations representing subset of mRNAs population actively translated in a cell. The molecular responses of biocontrol are complex and involve multistage regulation of number of genes. The use of high-throughput techniques has led to rapid increase in volume of transcriptomics data of Trichoderma. In general, almost half of the variations of transcriptome and protein level are due to translational control. Thus, studies are required to integrate raw information from different “omics” approaches for accurate depiction of translational response of BCAs in interaction with plants and plant pathogens. The studies on translational status of only active mRNAs bridging with proteome data will help in accurate characterization of only a subset of mRNAs actively engaged in translation. This review highlights the associated bottlenecks and use of state-of-the-art procedures in addressing the gap to accelerate future accomplishment of biocontrol mechanisms.

Motile hepatocellular carcinoma cells preferentially secret sugar metabolism regulatory proteins via exosomes

Exosomes are deliverers of critically functional proteins, capable of transforming target cells in numerous cancers, including hepatocellular carcinoma (HCC). We hypothesize that the motility of HCC cells can be featured by comparative proteome of exosomes. Hence, we performed the super-SILAC-based MS analysis on the exosomes secreted by three human HCC cell lines, including the non-motile Hep3B cell, and the motile 97H and LM3 cells. More than 1400 exosomal proteins were confidently quantified in each MS analysis with highly biological reproducibility. We justified that 469 and 443 exosomal proteins represented differentially expressed proteins (DEPs) in the 97H/Hep3B and LM3/Hep3B comparisons, respectively. These DEPs focused on sugar metabolism-centric canonical pathways per ingenuity pathway analysis, which was consistent with the gene ontology analysis on biological process enrichment. These pathways included glycolysis I, gluconeogenesis I and pentose phosphate pathways; and the DEPs enriched in these pathways could form a tightly connected network. By analyzing the relative abundance of proteins and translating mRNAs, we found significantly positive correlation between exosomes and cells. The involved exosomal proteins were again focusing on sugar metabolism. In conclusion, motile HCC cells tend to preferentially export more sugar metabolism-associated proteins via exosomes that differentiate them from non-motile HCC cells.

Proteogenomics: Key Driver for Clinical Discovery and Personalized Medicine

Proteogenomics is a multi-omics research field that has the aim to efficiently integrate genomics, transcriptomics and proteomics. With this approach it is possible to identify new patient-specific proteoforms that may have implications in disease development, specifically in cancer. Understanding the impact of a large number of mutations detected at the genomics level is needed to assess the effects at the proteome level. Proteogenomics data integration would help in identifying molecular changes that are persistent across multiple molecular layers and enable better interpretation of molecular mechanisms of disease, such as the causal relationship between single nucleotide polymorphisms (SNPs) and the expression of transcripts and translation of proteins compared to mainstream proteomics approaches. Identifying patient-specific protein forms and getting a better picture of molecular mechanisms of disease opens the avenue for precision and personalized medicine. Proteogenomics is, however, a challenging interdisciplinary science that requires the understanding of sample preparation, data acquisition and processing for genomics, transcriptomics and proteomics. This chapter aims to guide the reader through the technology and bioinformatics aspects of these multi-omics approaches, illustrated with proteogenomics applications having clinical or biological relevance.

In-depth analysis of the synaptic plasma membrane proteome of small hippocampal slices using an integrated approach

Comprehensive knowledge of the synaptic plasma membrane (SPM) proteome of a distinct brain region in a defined pathological state would greatly advance the understanding of the underlying biology of synaptic plasticity. The development of innovative approaches for studying the SPM proteome of small brain tissues is highly desired. This study presents a suitable protocol that integrates biotinylation-based affinity capture of cell surface-exposed proteins, isolation of synaptosomes, and biochemical extraction of SPM proteins from biotinylated hippocampal slices. The effectiveness of this integrated method was initially confirmed using immunoblot analysis of synaptic markers. Subsequently, we used highly sensitive mass spectrometry and streamlined bioinformatics to analyze the obtained SPM protein-enriched fraction. Our workflow positively identified 241 SPM proteins comprising 85 previously reported classical proteins from the pre- and/or post-synaptic membrane and 156 nonclassical proteins that localized to both the plasma membrane and synapse, and have not been previously reported as SPM proteins. Further analyses revealed considerable similarities in the physicochemical and functional properties of these proteins. Analysis of the interaction network using STRING indicated that the two groups showed a relatively strong functional correlation. Using MCODE analysis, we observed that 65 nonclassical SPM proteins formed 12 highly interconnected clusters with 47 classical SPM proteins, suggesting that they were the more likely SPM candidates. Taken together, the results of this study provide an integrated tool for analyzing the SPM proteome of small brain tissues, as well as a dataset of putative novel SPM proteins to improve the understanding of hippocampal synaptic plasticity.

[PCR analysis of the absolute number of copies of human chromosome 18 transcripts in liver and HepG2 cells]

Using reverse transcription in conjunction with the quantitative real-time PCR or digital droplet PCR, the transcriptome profiling of human chromosome 18 has been carried out in liver hepatocytes and hepatoblastoma cells (HepG2 cell line) in terms of the absolute number of each transcript per cell. The transcript abundance varies within the range of 0.006 to 9635 and 0.011 to 4819 copies per cell for HepG2 cell line and hepatocytes, respectively. The expression profiles for genes of chromosome 18 in hepatocytes and HepG2 cells were found to significantly correlate: the Spearman's correlation coefficient was equal to 0.81. The distribution of frequency of transcripts over their abundance was bimodal for HepG2 cells and unimodal for liver hepatocytes. Bioinformatic analysis of the differential gene expression has revealed that genes of chromosome 18, overexpressed in HepG2 cells compared to hepatocytes, are associated with cell division and cell adhesion processes. It is assumed that the enhanced expression of those genes in HepG2 cells is related to the proliferation activity of cultured cells. The differences in transcriptome profiles have to be taken into account when modelling liver hepatocytes with cultured HepG2 cells.

Comprehensive Proteomics Analysis Reveals Metabolic Reprogramming of Tumor-Associated Macrophages Stimulated by the Tumor Microenvironment

Tumor-associated macrophages (TAMs) are major components of the tumor microenvironment. Although a role for TAMs in promoting tumor progression has been revealed, the differentiation mechanisms and intrinsic signals of TAMs regulated by the tumor microenvironment remain unclear. Here we constructed an in vitro TAMs cell model, TES-TAMs, which is from tumor-extract-stimulated bone-marrow-derived macrophages. We performed a comparative proteomics analysis of bone-marrow-derived macrophages and TES-TAMs, which indicated that TES-TAMs possessed characteristic molecular expression of TAMs. Intriguingly, the signal pathways enriched in up-regulated differentially expressed proteins of TAMs demonstrated that glycolysis metabolism reprogramming may play an important role in TAM differentiation. We found that hexokinase-2, a key mediator of aerobic glycolysis, and the downstream proteins PFKL and ENO1 were remarkably increased in both TES-TAMs and primary TAMs from our MMTV-PyMT mice model. This phenomenon was then verified in human THP-1 cell lines stimulated by tumor extract solution from breast cancer patient. Taken together, our study provides insight into the induction of TAM differentiation by the tumor microenvironment through metabolic reprogramming.

State of the Art of Chromosome 18-Centric HPP in 2016: Transcriptome and Proteome Profiling of Liver Tissue and HepG2 Cells

A gene-centric approach was applied for a large-scale study of expression products of a single chromosome. Transcriptome profiling of liver tissue and HepG2 cell line was independently performed using two RNA-Seq platforms (SOLiD and Illumina) and also by Droplet Digital PCR (ddPCR) and quantitative RT-PCR. Proteome profiling was performed using shotgun LC-MS/MS as well as selected reaction monitoring with stable isotope-labeled standards (SRM/SIS) for liver tissue and HepG2 cells. On the basis of SRM/SIS measurements, protein copy numbers were estimated for the Chromosome 18 (Chr 18) encoded proteins in the selected types of biological material. These values were compared with expression levels of corresponding mRNA. As a result, we obtained information about 158 and 142 transcripts for HepG2 cell line and liver tissue, respectively. SRM/SIS measurements and shotgun LC-MS/MS allowed us to detect 91 Chr 18-encoded proteins in total, while an intersection between the HepG2 cell line and liver tissue proteomes was ∼66%. In total, there were 16 proteins specifically observed in HepG2 cell line, while 15 proteins were found solely in the liver tissue. Comparison between proteome and transcriptome revealed a poor correlation (R² ≈ 0.1) between corresponding mRNA and protein expression levels. The SRM and shotgun data sets (obtained during 2015-2016) are available in PASSEL (PASS00697) and ProteomeExchange/PRIDE (PXD004407). All measurements were also uploaded into the in-house Chr 18 Knowledgebase at http://kb18.ru/protein/matrix/416126 .

Mapping and analyzing the human liver proteome: progress and potential

INTRODUCTION

The liver is an important organ in humans. Hepatocellular carcinoma (HCC) is one of the deadliest cancers in the world. Progress in the Human Liver Proteome Project (HLPP) has improved understanding of the liver and the liver cancer proteome.

AREAS COVERED

Here, we summarize the recent progress in liver proteome modification profiles, proteomic studies in liver cancer, proteomic study in the search for novel liver cancer biomarkers and drug targets, and progress of the Chromosome Centric Human Proteome Project (CHPP) in the past five years in the Institutes of Biomedical Sciences (IBS) of Fudan University. Expert commentary: Recent advances and findings discussed here provide great promise of improving the outcome of patients with liver cancer.

Length-dependent translation initiation benefits the functional proteome of human cells

We previously found that shorter mRNAs are preferably translated in various eukaryotic cells. However, the theoretical basis of this phenomenon is unclear. We hypothesize that shorter mRNA length correlates to the decreased translational error rate to reduce the energy consumption on defective protein degradation. In this study, we established a computational model to explain the length-dependent translation initiation efficiency. We provided mathematical evidence that this translational preference, rather than the protein degradation, is a major factor to shape the genome-wide length-dependent protein abundance. As deducted, we simulated that shorter mRNA length is a determinant of initiation circularization time. Furthermore, our model unveiled that preferentially translating shorter mRNAs benefits the energy efficiency on the proteome functionality. We proposed that cancer cells tend to hijack this evolutionary mechanism by counteracting the higher translational error rate. In conclusion, our model provides insights into the nature of the global length-dependent translational control and its biological significance.

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.

Assessing Transcription Regulatory Elements To Evaluate the Expression Status of Missing Protein Genes on Chromosomes 11 and 19

During an investigation of missing proteins with the RNA-seq data acquired from three liver cancer cell lines, the majority of the missing protein coding genes (MPGs) located at chromosome 11 (chr11) had no corresponding mRNAs, while a high percentage of the MPGs on chr19 were detected at the mRNA level. The phenomenon, which was also observed in more than 40 cell lines, led to an inquiry of causation of the different transcriptional statuses of the MPGs in the two chromosomes. We hypothesized that the special chromatin structure was a key element to regulate MPG transcription. Upon a systematical comparison of the effects of DNase I hypersensitive sites (DHSs), transcription factors (TFs), and histone modifications toward these genes or MPGs with/without mRNA evidence in chr11 and 19, we attributed the poor transcription of the MPGs to the weak capacity of these transcription regulatory elements, regardless of which chromosome the MPGs were located. We further analyzed the gene contents in chr11 and found a number of genes related to sensory functions in the presence of chr11. We postulate that a high number of sensory-related genes, which are located within special chromatin structure, could bring a low detection rate of MPGs in chr11.

Quest for Missing Proteins: Update 2015 on Chromosome-Centric Human Proteome Project

This paper summarizes the recent activities of the Chromosome-Centric Human Proteome Project (C-HPP) consortium, which develops new technologies to identify yet-to-be annotated proteins (termed "missing proteins") in biological samples that lack sufficient experimental evidence at the protein level for confident protein identification. The C-HPP also aims to identify new protein forms that may be caused by genetic variability, post-translational modifications, and alternative splicing. Proteogenomic data integration forms the basis of the C-HPP's activities; therefore, we have summarized some of the key approaches and their roles in the project. We present new analytical technologies that improve the chemical space and lower detection limits coupled to bioinformatics tools and some publicly available resources that can be used to improve data analysis or support the development of analytical assays. Most of this paper's content has been compiled from posters, slides, and discussions presented in the series of C-HPP workshops held during 2014. All data (posters, presentations) used are available at the C-HPP Wiki (http://c-hpp.webhosting.rug.nl/) and in the Supporting Information.

Mining Missing Membrane Proteins by High-pH Reverse-Phase StageTip Fractionation and Multiple Reaction Monitoring Mass Spectrometry

Despite significant efforts in the past decade toward complete mapping of the human proteome, 3564 proteins (neXtProt, 09-2014) are still "missing proteins". Over one-third of these missing proteins are annotated as membrane proteins, owing to their relatively challenging accessibility with standard shotgun proteomics. Using nonsmall cell lung cancer (NSCLC) as a model study, we aim to mine missing proteins from disease-associated membrane proteome, which may be still largely under-represented. To increase identification coverage, we employed Hp-RP StageTip prefractionation of membrane-enriched samples from 11 NSCLC cell lines. Analysis of membrane samples from 20 pairs of tumor and adjacent normal lung tissue was incorporated to include physiologically expressed membrane proteins. Using multiple search engines (X!Tandem, Comet, and Mascot) and stringent evaluation of FDR (MAYU and PeptideShaker), we identified 7702 proteins (66% membrane proteins) and 178 missing proteins (74 membrane proteins) with PSM-, peptide-, and protein-level FDR of 1%. Through multiple reaction monitoring using synthetic peptides, we provided additional evidence of eight missing proteins including seven with transmembrane helix domains. This study demonstrates that mining missing proteins focused on cancer membrane subproteome can greatly contribute to map the whole human proteome. All data were deposited into ProteomeXchange with the identifier PXD002224.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology

Integrated -omics approaches are quickly spreading across microbiology research labs, leading to (i) the possibility of detecting previously hidden features of microbial cells like multi-scale spatial organization and (ii) tracing molecular components across multiple cellular functional states. This promises to reduce the knowledge gap between genotype and phenotype and poses new challenges for computational microbiologists. We underline how the capability to unravel the complexity of microbial life will strongly depend on the integration of the huge and diverse amount of information that can be derived today from -omics experiments. In this work, we present opportunities and challenges of multi -omics data integration in current systems biology pipelines. We here discuss which layers of biological information are important for biotechnological and clinical purposes, with a special focus on bacterial metabolism and modelling procedures. A general review of the most recent computational tools for performing large-scale datasets integration is also presented, together with a possible framework to guide the design of systems biology experiments by microbiologists.

Proteogenomic analysis and global discovery of posttranslational modifications in prokaryotes

We describe an integrated workflow for proteogenomic analysis and global profiling of posttranslational modifications (PTMs) in prokaryotes and use the model cyanobacterium Synechococcus sp. PCC 7002 (hereafter Synechococcus 7002) as a test case. We found more than 20 different kinds of PTMs, and a holistic view of PTM events in this organism grown under different conditions was obtained without specific enrichment strategies. Among 3,186 predicted protein-coding genes, 2,938 gene products (>92%) were identified. We also identified 118 previously unidentified proteins and corrected 38 predicted gene-coding regions in the Synechococcus 7002 genome. This systematic analysis not only provides comprehensive information on protein profiles and the diversity of PTMs in Synechococcus 7002 but also provides some insights into photosynthetic pathways in cyanobacteria. The entire proteogenomics pipeline is applicable to any sequenced prokaryotic organism, and we suggest that it should become a standard part of genome annotation projects.