Resolving chromosome-centric human proteome with translating mRNA analysis: a strategic demonstration

Evaluation of the antitumor effect of neoantigen peptide vaccines derived from the translatome of lung cancer

Emerging evidence suggests that tumor-specific neoantigens are ideal targets for cancer immunotherapy. However, how to predict tumor neoantigens based on translatome data remains obscure. Through the extraction of ribosome-nascent chain complexes (RNCs) from LLC cells, followed by RNC-mRNA extraction, RNC-mRNA sequencing, and comprehensive bioinformatic analysis, we successfully identified proteins undergoing translatome and exhibiting mutations in the cells. Subsequently, novel antigens identification was analyzed by the interaction between their high affinity and the Major Histocompatibility Complex (MHC). Neoantigens immunogenicity was analyzed by enzyme-linked immunospot assay (ELISpot). Finally, in vivo experiments in mice were conducted to evaluate the antitumor effects of translatome-derived neoantigen peptides on lung cancer. The results showed that ten neoantigen peptides were identified and synthesized by translatome data from LLC cells; 8 out of the 10 neoantigens had strong immunogenicity. The neoantigen peptide vaccine group exhibited significant tumor growth inhibition effect. In conclusion, neoantigen peptide vaccine derived from the translatome of lung cancer exhibited significant tumor growth inhibition effect.

Transcriptomic crosstalk between viral and host factors drives aberrant homeostasis of T-cell proliferation and cell death in HIV-infected immunological non-responders

BACKGROUND

Immunological non-responders (INRs) among people living with HIV have inherently higher mortality and morbidity rates. The underlying immunological mechanisms whereby failure of immune reconstitution occurs in INRs require elucidation.

METHOD

HIV-1 DNA and HIV-1 cell-associated RNA (CA-HIV RNA) quantifications were conducted via RT-qPCR. Transcriptome sequencing (RNA-seq), bioinformatics, and biological verifications were performed to discern the crosstalk between host and viral factors. Flow cytometry was employed to analyze cellular activation, proliferation, and death.

RESULTS

HIV-1 DNA and CA-HIV RNA levels were observed to be significantly higher in INRs compared to immunological responders (IRs). Evaluation of CD4/CD8 ratios showed a significantly negative correlation with HIV-1 DNA in IRs, but not in INRs. Bioinformatics analyses and biological verifications showed IRF7/INF-α regulated antiviral response was intensified in INRs. PBMCs of INRs expressed significantly more HIV integrase-mRNA (p31) than IRs. Resting (CD4+CD69- T-cells) and activated (CD4+CD69+ T-cells) HIV-1 reservoir harboring cells were significantly higher in INRs, with the co-occurrence of significantly higher cellular proliferation and cell death in CD4+ T-cells of INRs.

CONCLUSION

In INRs, the systematic crosstalk between the HIV-1 reservoir and host cells tends to maintain a persistent antiviral response-associated inflammatory environment, which drives aberrant cellular activation, proliferation, and death of CD4+ T-cells.

Advances and opportunities in methods to study protein translation - A review

It is generally believed that the regulation of gene expression involves protein translation occurring before RNA transcription. Therefore, it is crucial to investigate protein translation and its regulation. Recent advancements in biological sciences, particularly in the field of omics, have revolutionized protein translation research. These studies not only help characterize changes in protein translation during specific biological or pathological processes but also have significant implications in disease prevention and treatment. In this review, we summarize the latest methods in ribosome-based translation omics. We specifically focus on the application of fluorescence imaging technology and omics technology in studying overall protein translation. Additionally, we analyze the advantages, disadvantages, and application of these experimental methods, aiming to provide valuable insights and references to researchers studying translation.

Efficient Detection of the Alternative Spliced Human Proteome Using Translatome Sequencing

Alternative splicing (AS) isoforms create numerous proteoforms, expanding the complexity of the genome. Highly similar sequences, incomplete reference databases and the insufficient sequence coverage of mass spectrometry limit the identification of AS proteoforms. Here, we demonstrated full-length translating mRNAs (ribosome nascent-chain complex-bound mRNAs, RNC-mRNAs) sequencing (RNC-seq) strategy to sequence the entire translating mRNA using next-generation sequencing, including short-read and long-read technologies, to construct a protein database containing all translating AS isoforms. Taking the advantage of read length, short-read RNC-seq identified up to 15,289 genes and 15,906 AS isoforms in a single human cell line, much more than the Ribo-seq. The single-molecule long-read RNC-seq supplemented 4,429 annotated AS isoforms that were not identified by short-read datasets, and 4,525 novel AS isoforms that were not included in the public databases. Using such RNC-seq-guided database, we identified 6,766 annotated protein isoforms and 50 novel protein isoforms in mass spectrometry datasets. These results demonstrated the potential of full-length RNC-seq in investigating the proteome of AS isoforms.

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.

Comprehensive analysis of the translatome reveals the relationship between the translational and transcriptional control in high fat diet-induced liver steatosis

Translational regulation plays a critical role in gene expression. However, there are few genome-wide studies on translational regulation in non-alcoholic fatty liver disease (NAFLD), which is a severe non-communicable epidemic worldwide. In this study, we performed RNC-mRNA (mRNAs bound to ribosome-nascent chain complex) sequencing and mRNA sequencing to probe the translation status of high-fat-diet (HFD) induced mouse fatty liver. Generally, in the HFD group compared to the control group, changes of translation ratios and changes in mRNA abundance had a negative correlation. The relative abundance of RNC-mRNAs and mRNAs were positively correlated, yet the former changed more slowly than the latter. However, the rate of change became more balanced when it came to the livers of mice that were fed the HFD plus lycopene, an antioxidant. This indicated relatively independent roles of translational modulation and transcriptional regulation. Furthermore, many genes were differentially regulated at the transcriptional or translational levels, suggesting a new screening strategy for functional genes. In conclusion, our analysis revealed the different and correlated role of translational control with transcriptional regulation in the HFD-induced mouse fatty liver relative to the control, which indicates critical roles of translational control for liver steatosis; thus, adding a new dimension towards a better understanding and improvement of treatment for NAFLD.

Autoactivation of Translation Causes the Bloom of Prorocentrum donghaiense in Harmful Algal Blooms

Harmful algal blooms (HABs) are symptomatic of ecosystem imbalance, leading to major worldwide marine natural disasters, and seriously threaten the human health. Some HAB algae's exceptional genome size prohibited the genomic investigations on molecular mechanisms, for example, Prorocentrum. This study performed translatome sequencing (RNC-seq) for Prorocentrum donghaiense to assemble the translatome reference sequences on appropriate cost to enable the global molecular study at translatome and proteome levels. By analyzing the translatome and proteome of P. donghaiense in phosphor-rich, phosphor-deficient, and phosphor-restored media, we found massive up-regulation of energy and material production pathways in phosphor-rich conditions that enables autoactivation of translation, which is the key to its exponential growth in HABs. To break down the autoactivation, we demonstrated that mild translation delay using very low concentrations of cycloheximide efficiently controls the blooming without harming other aquatic organisms and humans. Our result provides a novel hint for controlling HABs and demonstrated the RNC-seq as an economic strategy on investigating functions of organisms with large and unknown genomes.

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/.

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.

PROTEOFORMER 2.0: Further Developments in the Ribosome Profiling-assisted Proteogenomic Hunt for New Proteoforms

PROTEOFORMER is a pipeline that enables the automated processing of data derived from ribosome profiling (RIBO-seq, i.e. the sequencing of ribosome-protected mRNA fragments). As such, genome-wide ribosome occupancies lead to the delineation of data-specific translation product candidates and these can improve the mass spectrometry-based identification. Since its first publication, different upgrades, new features and extensions have been added to the PROTEOFORMER pipeline. Some of the most important upgrades include P-site offset calculation during mapping, comprehensive data pre-exploration, the introduction of two alternative proteoform calling strategies and extended pipeline output features. These novelties are illustrated by analyzing ribosome profiling data of human HCT116 and Jurkat data. The different proteoform calling strategies are used alongside one another and in the end combined together with reference sequences from UniProt. Matching mass spectrometry data are searched against this extended search space with MaxQuant. Overall, besides annotated proteoforms, this pipeline leads to the identification and validation of different categories of new proteoforms, including translation products of up- and downstream open reading frames, 5' and 3' extended and truncated proteoforms, single amino acid variants, splice variants and translation products of so-called noncoding regions. Further, proof-of-concept is reported for the improvement of spectrum matching by including Prosit, a deep neural network strategy that adds extra fragmentation spectrum intensity features to the analysis. In the light of ribosome profiling-driven proteogenomics, it is shown that this allows validating the spectrum matches of newly identified proteoforms with elevated stringency. These updates and novel conclusions provide new insights and lessons for the ribosome profiling-based proteogenomic research field. More practical information on the pipeline, raw code, the user manual (README) and explanations on the different modes of availability can be found at the GitHub repository of PROTEOFORMER: https://github.com/Biobix/proteoformer.

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.

Proteogenomic Analyses Revealed Favorable Metabolism Pattern Alterations in Rotifer Brachionus plicatilis Fed with Selenium-rich Chlorella

Organoselenium have garnered attention because of their potential to be used as ingredients in new anti-aging and antioxidation medicines and food. Rotifers are frequently used as a model organism for aging research. In this study, we used Se-enriched Chlorella (Se- Chlorella), a novel organoselenium compound, to feed Brachionus plicatilis to establish a rotifer model with a prolonged lifespan. The results showed that the antioxidative effect in Se-enriched rotifer was associated with an increase in guaiacol peroxidase (GPX) and catalase (CAT). The authors then performed the first proteogenomic analysis of rotifers to understand their possible metabolic mechanisms. With the de novo assembly of RNA-Seq reads as the reference, we mapped the proteomic output generated by iTRAQ-based mass spectrometry. We found that the differentially expressed proteins were primarily involved in antireactive oxygen species (ROS) and antilipid peroxidation (LPO), selenocompound metabolism, glycolysis, and amino acid metabolisms. Furthermore, the ROS level of rotifers was diminished after Se- Chlorella feeding, indicating that Se- Chlorella could help rotifers to enhance their amino acid metabolism and shift the energy generating metabolism from tricarboxylic acid cycle to glycolysis, which leads to reduced ROS production. This is the first report to demonstrate the anti-aging effect of Se- Chlorella on rotifers and to provide a possible mechanism for this activity. Thus, Se- Chlorella is a promising novel organoselenium compound with the potential to prolong human lifespans.

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.

Recent insights into human bronchial proteomics - how are we progressing and what is next?

The human respiratory system is highly prone to diseases and complications. Many lung diseases, including lung cancer (LC), tuberculosis (TB), and chronic obstructive pulmonary disease (COPD) have been among the most common causes of death worldwide. Cystic fibrosis (CF), the most common genetic disease in Caucasians, has adverse impacts on the lungs. Bronchial proteomics plays a significant role in understanding the underlying mechanisms and pathogenicity of lung diseases and provides insights for biomarker and therapeutic target discoveries. Areas covered: We overview the recent achievements and discoveries in human bronchial proteomics by outlining how some of the different proteomic techniques/strategies are developed and applied in LC, TB, COPD, and CF. Also, the future roles of bronchial proteomics in predictive proteomics and precision medicine are discussed. Expert commentary: Much progress has been made in bronchial proteomics. Owing to the advances in proteomics, we now have better ability to isolate proteins from desired cellular compartments, greater protein separation methods, more powerful protein detection technologies, and more sophisticated bioinformatic techniques. These all contributed to our further understanding of lung diseases and for biomarker and therapeutic target discoveries.

Use of Microarray Datasets to generate Caco-2-dedicated Networks and to identify Reporter Genes of Specific Pathway Activity

Intestinal epithelial cells, like Caco-2, are commonly used to study the interaction between food, other luminal factors and the host, often supported by microarray analysis to study the changes in gene expression as a result of the exposure. However, no compiled dataset for Caco-2 has ever been initiated and Caco-2-dedicated gene expression networks are barely available. Here, 341 Caco-2-specific microarray samples were collected from public databases and from in-house experiments pertaining to Caco-2 cells exposed to pathogens, probiotics and several food compounds. Using these datasets, a gene functional association network specific for Caco-2 was generated containing 8937 nodes 129711 edges. Two in silico methods, a modified version of biclustering and the new Differential Expression Correlation Analysis, were developed to identify Caco-2-specific gene targets within a pathway of interest. These methods were subsequently applied to the AhR and Nrf2 signalling pathways and altered expression of the predicted target genes was validated by qPCR in Caco-2 cells exposed to coffee extracts, known to activate both AhR and Nrf2 pathways. The datasets and in silico method(s) to identify and predict responsive target genes can be used to more efficiently design experiments to study Caco-2/intestinal epithelial-relevant biological processes.

Regulation of viral gene expression by duck enteritis virus UL54

Duck enteritis virus (DEV) UL54 is a homologue of human herpes simplex virus-1 (HSV-1) ICP27, which plays essential regulatory roles during infection. Our previous studies indicated that DEV UL54 is an immediate-early protein that can shuttle between the nucleus and the cytoplasm. In the present study, we found that UL54-deleted DEV (DEV-ΔUL54) exhibits growth kinetics, a plaque size and a viral DNA copy number that are significantly different from those of its parent wild-type virus (DEV-LoxP) and the revertant (DEV-ΔUL54 (Revertant)). Relative viral mRNA levels, reflecting gene expression, the transcription phase and the translation stage, are also significantly different between DEV-ΔUL54-infected cells and DEV-LoxP/DEV-ΔUL54 (Revertant)-infected cells. However, the localization pattern of UL30 mRNA is obviously changed in DEV-ΔUL54-infected cells. These findings suggest that DEV UL54 is important for virus growth and may regulate viral gene expression during transcription, mRNA export and translation.

Genome-Wide and Experimental Resolution of Relative Translation Elongation Speed at Individual Gene Level in Human Cells

In the process of translation, ribosomes first assemble on mRNAs (translation initiation) and then translate along the mRNA (elongation) to synthesize proteins. Elongation pausing is deemed highly relevant to co-translational folding of nascent peptides and the functionality of protein products, which positioned the evaluation of elongation speed as one of the central questions in the field of translational control. By integrating three types of RNA-seq methods, we experimentally and computationally resolved elongation speed, with our proposed elongation velocity index (EVI), a relative measure at individual gene level and under physiological condition in human cells. We successfully distinguished slow-translating genes from the background translatome. We demonstrated that low-EVI genes encoded more stable proteins. We further identified cell-specific slow-translating codons, which might serve as a causal factor of elongation deceleration. As an example for the biological relevance, we showed that the relatively slow-translating genes tended to be associated with the maintenance of malignant phenotypes per pathway analyses. In conclusion, EVI opens a new view to understand why human cells tend to avoid simultaneously speeding up translation initiation and decelerating elongation, and the possible cancer relevance of translating low-EVI genes to gain better protein quality.

In protein synthesis, ribosome assembles to mRNA to initiate translation, followed by the process of elongation to read the codons along the mRNA molecule for polypeptide chain production. It is known that slowing down the elongation speed at certain regions of mRNA is critical for the correct folding of numerous proteins—the so-called “pause-to-fold”. However, it has been an open question to evaluate elongation speed under cellular physiological conditions in genome-wide scale. Here, we used three types of next-generation sequencing approaches to experimentally and computationally address this question. With a new relative measure of elongation velocity index (EVI), we successfully distinguished slow-translating genes. Their protein products are more stable than the background genes. We found that different cell types tended to have distinct slow-translating codons, which might be relevant to the cell/tissue specific tRNA composition. Such elongation deceleration is potentially disease-relevant: cancer cells tend to slow down numerous cancer-favorable genes, and vice versa. Furthermore, we justified that translation initiation and elongation are evolutionarily synergistic as no gene with both high initiation efficiency and low elongation speed was observed: that would cause a traffic jam of ribosomes that should be maximally avoided per evolution.

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.

Integrated Translatomics with Proteomics to Identify Novel Iron-Transporting Proteins in Streptococcus pneumoniae

Streptococcus pneumoniae (S.pneumoniae) is a major human pathogen causing morbidity and mortality worldwide. Efficiently acquiring iron from the environment is critical for S. pneumoniae to sustain growth and cause infection. There are only three known iron-uptake systems in Streptococcal species responsible for iron acquisition from the host, including ABC transporters PiaABC, PiuABC, and PitABC. Besides, no other iron-transporting system has been suggested. In this work, we employed our newly established translating mRNA analysis integrated with proteomics to evaluate the possible existence of novel iron transporters in the bacterium. We simultaneously deleted the iron-binding protein genes of the three iron-uptake systems to construct a piaA/piuA/pitA triple mutant (Tri-Mut) of S. pneumoniae D39, in which genes and proteins related to iron transport should be regulated in response to the deletion. With ribosome associated mRNA sequencing-based translatomics focusing on translating mRNA and iTRAQ quantitative proteomics based on the covalent labeling of peptides with tags of varying mass, we indeed observed a large number of genes and proteins representing various coordinated biological pathways with significantly altered expression levels in the Tri-Mut mutant. Highlighted in this observation is the identification of several new potential iron-uptake ABC transporters participating in iron metabolism of Streptococcus. In particular, putative protein SPD_1609 in operon 804 was verified to be a novel iron-binding protein with similar function to PitA in S. pneumoniae. These data derived from the integrative translatomics and proteomics analyses provided rich information and insightful clues for further investigations on iron-transporting mechanism in bacteria and the interplay between Streptococcal iron availability and the biological metabolic pathways.

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.

Proteomic Analysis of Anticancer TCMs Targeted at Mitochondria

Traditional Chinese medicine (TCM) is a rich resource of anticancer drugs. Increasing bioactive natural compounds extracted from TCMs are known to exert significant antitumor effects, but the action mechanisms of TCMs are far from clear. Proteomics, a powerful platform to comprehensively profile drug-regulated proteins, has been widely applied to the mechanistic investigation of TCMs and the identification of drug targets. In this paper, we discuss several bioactive TCM products including terpenoids, flavonoids, and glycosides that were extensively investigated by proteomics to illustrate their antitumor mechanisms in various cancers. Interestingly, many of these natural compounds isolated from TCMs mostly exert their tumor-suppressing functions by specifically targeting mitochondria in cancer cells. These TCM components induce the loss of mitochondrial membrane potential, the release of cytochrome c, and the accumulation of ROS, initiating apoptosis cascade signaling. Proteomics provides systematic views that help to understand the molecular mechanisms of the TCM in tumor cells; it bears the inherent limitations in uncovering the drug-protein interactions, however. Subcellular fractionation may be coupled with proteomics to capture and identify target proteins in mitochondria-enriched lysates. Furthermore, translating mRNA analysis, a new technology profiling the drug-regulated genes in translatome level, may be integrated into the systematic investigation, revealing global information valuable for understanding the action mechanism of TCMs.

ANGPTL7 regulates the expansion and repopulation of human hematopoietic stem and progenitor cells

Successful expansion of hematopoietic stem cells would benefit the use of hematopoietic stem cell transplants in the clinic. Several angiopoietin-like proteins, including angiopoietin-like 7, can support the activity of hematopoietic stem cells. However, effects of ANGPTL7 on human hematopoietic stem cells and the downstream signaling cascade activated by ANGPTL7 are poorly understood. Here, we established a human hematopoietic stem and progenitor cell-supportive mouse fetal liver cell line that specifically expressed the Angptl7 protein. Furthermore, we found ANGPTL7 is capable of stimulating human hematopoietic stem and progenitor cell expansion and increasing the repopulation activities of human hematopoietic progenitors in xenografts. RNA-sequencing analysis showed that ANGPTL7 activated the expression of CXCR4, HOXB4 and Wnt downstream targets in human hematopoietic progenitors. In addition, chemical manipulation of Wnt signaling diminished the effects of ANGPTL7 on human hematopoietic stem and progenitor cells in culture. In summary, we identify the secreted growth factor ANGPTL7 as a regulator of both human hematopoietic stem and progenitor cell expansion and regeneration.

N-terminomics and proteogenomics, getting off to a good start

Proteogenomics consists of the annotation or reannotation of protein-coding nucleic acid sequences based on the empirical observation of their gene products. While functional annotation of predicted genes is increasingly feasible given the multiplicity of genomes available for many branches of the tree of life, the accurate annotation of the translational start sites is still a point of contention. Extensive coverage of the proteome, including specifically the N-termini, is now possible, thanks to next-generation mass spectrometers able to record data from thousands of proteins at once. Efforts to increase the peptide coverage of protein sequences and to detect low abundance proteins are important to make proteomic and proteogenomic studies more comprehensive. In this review, we present the panoply of N-terminus-oriented strategies that have been developed over the last decade.

Non-model organisms, a species endangered by proteogenomics

Previously, large-scale proteomics was possible only for organisms whose genomes were sequenced, meaning the most common model organisms. The use of next-generation sequencers is now changing the deal. With "proteogenomics", the use of experimental proteomics data to refine genome annotations, a higher integration of omics data is gaining ground. By extension, combining genomic and proteomic data is becoming routine in many research projects. "Proteogenomic"-flavored approaches are currently expanding, enabling the molecular studies of non-model organisms at an unprecedented depth. Today draft genomes can be obtained using next-generation sequencers in a rather straightforward way and at a reasonable cost for any organism. Unfinished genome sequences can be used to interpret tandem mass spectrometry proteomics data without the need for time-consuming genome annotation, and the use of RNA-seq to establish nucleotide sequences that are directly translated into protein sequences appears promising. There are, however, certain drawbacks that deserve further attention for RNA-seq to become more efficient. Here, we discuss the opportunities of working with non-model organisms, the proteomic methods that have been used until now, and the dramatic improvements proffered by proteogenomics. These put the distinction between model and non-model organisms in great danger, at least in terms of proteomics!

BIOLOGICAL SIGNIFICANCE

Model organisms have been crucial for in-depth analysis of cellular and molecular processes of life. Focusing the efforts of thousands of researchers on the Escherichia coli bacterium, Saccharomyces cerevisiae yeast, Arabidopsis thaliana plant, Danio rerio fish and other models for which genetic manipulation was possible was certainly worthwhile in terms of fundamental and invaluable biological insights. Until recently, proteomics of non-model organisms was limited to tedious, homology-based techniques, but today draft genomes or RNA-seq data can be straightforwardly obtained using next-generation sequencers, allowing the establishment of a draft protein database for any organism. Thus, proteogenomics opens new perspectives for molecular studies of non-model organisms, although they are still difficult experimental organisms. This article is part of a Special Issue entitled: Proteomics of non-model organisms.

Metrics for the Human Proteome Project 2013-2014 and strategies for finding missing proteins

One year ago the Human Proteome Project (HPP) leadership designated the baseline metrics for the Human Proteome Project to be based on neXtProt with a total of 13,664 proteins validated at protein evidence level 1 (PE1) by mass spectrometry, antibody-capture, Edman sequencing, or 3D structures. Corresponding chromosome-specific data were provided from PeptideAtlas, GPMdb, and Human Protein Atlas. This year, the neXtProt total is 15,646 and the other resources, which are inputs to neXtProt, have high-quality identifications and additional annotations for 14,012 in PeptideAtlas, 14,869 in GPMdb, and 10,976 in HPA. We propose to remove 638 genes from the denominator that are "uncertain" or "dubious" in Ensembl, UniProt/SwissProt, and neXtProt. That leaves 3844 "missing proteins", currently having no or inadequate documentation, to be found from a new denominator of 19,490 protein-coding genes. We present those tabulations and web links and discuss current strategies to find the missing proteins.