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

Chronic Aroclor 1260 exposure alters the mouse liver proteome, selenoproteins, and metals in steatotic liver disease

The prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) continues to increase due in part to the obesity epidemic and to environmental exposures to metabolism disrupting chemicals. A single gavage exposure of male mice to Aroclor 1260 (Ar1260), an environmentally relevant mixture of non-dioxin-like polychlorinated biphenyls (PCBs), resulted in steatohepatitis and altered RNA modifications in selenocysteine tRNA 34 weeks post-exposure. Unbiased approaches identified the liver proteome, selenoproteins, and levels of 25 metals. Ar1260 altered the abundance of 128 proteins. Enrichment analysis of the liver Ar1260 proteome included glutathione metabolism and translation of selenoproteins. Hepatic glutathione peroxidase 4 (GPX4) and Selenoprotein O (SELENOO) were increased and Selenoprotein F (SELENOF), Selenoprotein S (SELENOS), Selenium binding protein 2 (SELENBP2) were decreased with Ar1260 exposure. Increased copper, selenium (Se), and zinc and reduced iron levels were detected. These data demonstrate that Ar1260 exposure alters the (seleno)proteome, Se, and metals in MASLD-associated pathways.

Workability of mRNA Sequencing for Predicting Protein Abundance

Transcriptomics methods (RNA-Seq, PCR) today are more routine and reproducible than proteomics methods, i.e., both mass spectrometry and immunochemical analysis. For this reason, most scientific studies are limited to assessing the level of mRNA content. At the same time, protein content (and its post-translational status) largely determines the cell's state and behavior. Such a forced extrapolation of conclusions from the transcriptome to the proteome often seems unjustified. The ratios of "transcript-protein" pairs can vary by several orders of magnitude for different genes. As a rule, the correlation coefficient between transcriptome-proteome levels for different tissues does not exceed 0.3-0.5. Several characteristics determine the ratio between the content of mRNA and protein: among them, the rate of movement of the ribosome along the mRNA and the number of free ribosomes in the cell, the availability of tRNA, the secondary structure, and the localization of the transcript. The technical features of the experimental methods also significantly influence the levels of the transcript and protein of the corresponding gene on the outcome of the comparison. Given the above biological features and the performance of experimental and bioinformatic approaches, one may develop various models to predict proteomic profiles based on transcriptomic data. This review is devoted to the ability of RNA sequencing methods for protein abundance prediction.

Gene-centric coverage of the human liver transcriptome: QPCR, Illumina, and Oxford Nanopore RNA-Seq

It has been shown that the best coverage of the HepG2 cell line transcriptome encoded by genes of a single chromosome, chromosome 18, is achieved by a combination of two sequencing platforms, Illumina RNA-Seq and Oxford Nanopore Technologies (ONT), using cut-off levels of FPKM > 0 and TPM > 0, respectively. In this study, we investigated the extent to which the combination of these transcriptomic analysis methods makes it possible to achieve a high coverage of the transcriptome encoded by the genes of other human chromosomes. A comparative analysis of transcriptome coverage for various types of biological material was carried out, and the HepG2 cell line transcriptome was compared with the transcriptome of liver tissue cells. In addition, the contribution of variability in the coverage of expressed genes in human transcriptomes to the creation of a draft human transcriptome was evaluated. For human liver tissues, ONT makes an extremely insignificant contribution to the overall coverage of the transcriptome. Thus, to ensure maximum coverage of the liver tissue transcriptome, it is sufficient to apply only one technology: Illumina RNA-Seq (FPKM > 0).

TRIM28 Is a Novel Regulator of CD133 Expression Associated with Cancer Stem Cell Phenotype

CD133 is an extensively studied marker of the most malignant tumor cell population, designated as cancer stem cells (CSCs). However, the function of this glycoprotein and its involvement in cell regulatory cascades are still poorly understood. Here we show a positive correlation between the level of CD133 plasma membrane expression and the proliferative activity of cells of the Caco-2, HT-29, and HUH7 cancer cell lines. Despite a substantial difference in the proliferative activities of cell populations with different levels of CD133 expression, transcriptomic and proteomic profiling revealed only minor distinctions between them. Nonetheless, a further in silico assessment of the differentially expressed transcripts and proteins revealed 16 proteins that could be involved in the regulation of CD133 expression; these were assigned ranks reflecting the apparent extent of their involvement. Among them, the TRIM28 transcription factor had the highest rank. The prominent role of TRIM28 in CD133 expression modulation was confirmed experimentally in the Caco2 cell line clones: the knockout, though not the knockdown, of the TRIM28 gene downregulated CD133. These results for the first time highlight an important role of the TRIM28 transcription factor in the regulation of CD133-associated cancer cell heterogeneity.

[PCR analysis of the expression of chromosome 18 genes in human liver tissue: interindividual variability]

Using human chromosome 18 (Ch18) genes as an example, a PCR analysis of the interindividual variability of gene expression in liver tissue was performed. Although the quantitative profiles of the Ch18 transcriptome, expressed in the number of cDNA copies per single cell, showed a high degree of correlation between donors (Pearson correlation coefficients ranged from 0.963 to 0.966), the expression of the significant number of genes (from 13% to 19%, depending on the method of experimental data normalization) varied by more than 4-fold when comparing donors pairwise. At the same time, the proportion of differentially expressed genes increased with a decrease in the level of their expression. It is shown that the higher quantitative variability of low-abundance transcripts is mainly not technical, but biological. Bioinformatic analysis of the interindividual variability of the differential expression of chromosome 18 genes in human liver tissue did not reveal any statistically significant groups of genes related to certain biological processes that indicated a rather transient nature of the interindividual variability of their expression, probably reflecting the response of cells of an individual to specific external stimuli.

Genome of the Single Human Chromosome 18 as a "Gold Standard" for Its Transcriptome

The cutoff level applied in sequencing analysis varies according to the sequencing technology, sample type, and study purpose, which can largely affect the coverage and reliability of the data obtained. In this study, we aimed to determine the optimal combination of parameters for reliable RNA transcriptome data analysis. Toward this end, we compared the results obtained from different transcriptome analysis platforms (quantitative polymerase chain reaction, Illumina RNASeq, and Oxford Nanopore Technologies MinION) for the transcriptome encoded by human chromosome 18 (Chr 18) using the same sample types (HepG2 cells and liver tissue). A total of 275 protein-coding genes encoded by Chr 18 was taken as the gene set for evaluation. The combination of Illumina RNASeq and MinION nanopore technologies enabled the detection of at least one transcript for each protein-coding gene encoded by Chr 18. This combination also reduced the probability of false-positive detection of low-copy transcripts due to the simultaneous confirmation of the presence of a transcript by the two fundamentally different technologies: short reads essential for reliable detection (Illumina RNASeq) and long-read sequencing data (MinION). The combination of these technologies achieved complete coverage of all 275 protein-coding genes on Chr 18, identifying transcripts with non-zero expression levels. This approach can improve distinguishing the biological and technical reasons for the absence of mRNA detection for a given gene in transcriptomics.

Comparative Analysis of Skeleton Muscle Proteome Profile between Yak and Cattle Provides Insight into High-Altitude Adaptation

Background::

Mechanisms underlying yak adaptation to high-altitude environments have been investigated at the levels of morphology, anatomy, physiology, genome and transcriptome, but have not been explored at the proteome level.

Objective:

The protein profiles were compared between yak and cattle to explore molecular mechanisms underlying yak adaptation to high altitude conditions.

Methods:

In the present study, an antibody microarray chip was developed, which included 6,500 mouse monoclonal antibodies. Immunoprecipitation and mass spectrometry were performed on 12 selected antibodies which showed that the chip was highly specific. Using this chip, muscle tissue proteome was compared between yak and cattle, and 12 significantly Differentially Expressed Proteins (DEPs) between yak and cattle were identified. Their expression levels were validated using Western blot.

Results:

ompared with cattle, higher levels of Rieske Iron-Sulfur Protein (RISP), Cytochrome C oxidase subunit 4 isoform 1, mitochondrial (COX4I1), ATP synthase F1 subunit beta (ATP5F1B), Sarcoplasmic/ Endoplasmic Reticulum Calcium ATPase1 (SERCA1) and Adenosine Monophosphate Deaminase1 (AMPD1) in yak might improve oxygen utilization and energy metabolism. Pyruvate Dehydrogenase protein X component (PDHX) and Acetyltransferase component of pyruvate dehydrogenase complex (DLAT) showed higher expression levels and L-lactate dehydrogenase A chain (LDHA) showed lower expression level in yak, which might help yak reduce the accumulation of lactic acid. In addition, higher expression levels of Filamin C (FLNC) and low levels of AHNAK and Four and a half LIM domains 1 (FHL1) in yak might reduce the risks of pulmonary arteries vasoconstriction, remodeling and hypertension.

Conclusion:

Overall, the present study reported the differences in protein profile between yak and cattle, which might be helpful to further understand molecular mechanisms underlying yak adaptation to high altitude environments.

Variant in NHLRC2 leads to increased hnRNP C2 in developing neurons and the hippocampus of a mouse model of FINCA disease

Background

FINCA disease is a pediatric cerebropulmonary disease caused by variants in the NHL repeat-containing 2 (NHLRC2) gene. Neurological symptoms are among the first manifestations of FINCA disease, but the consequences of NHLRC2 deficiency in the central nervous system are currently unexplored.

Methods

The orthologous mouse gene is essential for development, and its complete loss leads to early embryonic lethality. In the current study, we used CRISPR/Cas9 to generate an Nhlrc2 knockin (KI) mouse line, harboring the FINCA patient missense mutation (c.442G > T, p.Asp148Tyr). A FINCA mouse model, resembling the compound heterozygote genotype of FINCA patients, was obtained by crossing the KI and Nhlrc2 knockout mouse lines. To reveal NHLRC2-interacting proteins in developing neurons, we compared cortical neuronal precursor cells of E13.5 FINCA and wild-type mouse embryos by two-dimensional difference gel electrophoresis.

Results

Despite the significant decrease in NHLRC2, the mice did not develop severe early onset multiorgan disease in either sex. We discovered 19 altered proteins in FINCA neuronal precursor cells; several of which are involved in vesicular transport pathways and actin dynamics which have been previously reported in other cell types including human to have an association with dysfunctional NHLRC2. Interestingly, isoform C2 of hnRNP C1/C2 was significantly increased in both developing neurons and the hippocampus of adult female FINCA mice, connecting NHLRC2 dysfunction with accumulation of RNA binding protein.

Conclusions

We describe here the first NHLRC2-deficient mouse model to overcome embryonic lethality, enabling further studies on predisposing and causative mechanisms behind FINCA disease. Our novel findings suggest that disrupted RNA metabolism may contribute to the neurodegeneration observed in FINCA patients.

Is It Possible to Find Needles in a Haystack? Meta-Analysis of 1000+ MS/MS Files Provided by the Russian Proteomic Consortium for Mining Missing Proteins

Despite direct or indirect efforts of the proteomic community, the fraction of blind spots on the protein map is still significant. Almost 11% of human genes encode missing proteins; the existence of which proteins is still in doubt. Apparently, proteomics has reached a stage when more attention and curiosity need to be exerted in the identification of every novel protein in order to expand the unusual types of biomaterials and/or conditions. It seems that we have exhausted the current conventional approaches to the discovery of missing proteins and may need to investigate alternatives. Here, we present an approach to deciphering missing proteins based on the use of non-standard methodological solutions and encompassing diverse MS/MS data, obtained for rare types of biological samples by members of the Russian Proteomic community in the last five years. These data were re-analyzed in a uniform manner by three search engines, which are part of the SearchGUI package. The study resulted in the identification of two missing and five uncertain proteins detected with two peptides. Moreover, 149 proteins were detected with a single proteotypic peptide. Finally, we analyzed the gene expression levels to suggest feasible targets for further validation of missing and uncertain protein observations, which will fully meet the requirements of the international consortium. The MS data are available on the ProteomeXchange platform (PXD014300).

Challenges of the Human Proteome Project: 10-Year Experience of the Russian Consortium

This manuscript collects all the efforts of the Russian Consortium, bottlenecks revealed in the course of the C-HPP realization, and ways of their overcoming. One of the main bottlenecks in the C-HPP is the insufficient sensitivity of proteomic technologies, hampering the detection of low- and ultralow-copy number proteins forming the "dark part" of the human proteome. In the frame of MP-Challenge, to increase proteome coverage we suggest an experimental workflow based on a combination of shotgun technology and selected reaction monitoring with two-dimensional alkaline fractionation. Further, to detect proteins that cannot be identified by such technologies, nanotechnologies such as combined atomic force microscopy with molecular fishing and/or nanowire detection may be useful. These technologies provide a powerful tool for single molecule analysis, by analogy with nanopore sequencing during genome analysis. To systematically analyze the functional features of some proteins (CP50 Challenge), we created a mathematical model that predicts the number of proteins differing in amino acid sequence: proteoforms. According to our data, we should expect about 100 000 different proteoforms in the liver tissue and a little more in the HepG2 cell line. The variety of proteins forming the whole human proteome significantly exceeds these results due to post-translational modifications (PTMs). As PTMs determine the functional specificity of the protein, we propose using a combination of gene-centric transcriptome-proteomic analysis with preliminary fractionation by two-dimensional electrophoresis to identify chemically modified proteoforms. Despite the complexity of the proposed solutions, such integrative approaches could be fruitful for MP50 and CP50 Challenges in the framework of the C-HPP.

The "Missing" Proteome: Undetected Proteins, Not-Translated Transcripts, and Untranscribed Genes

The Chromosome-centric Human Proteome Project aims at characterizing the expression of proteins encoded in each chromosome at the tissue, cell, and subcellular levels. The proteomic profiling of a particular tissue or cell line commonly results in a substantial portion of proteins that are not observed (the "missing" proteome). The concurrent transcriptome profiling of the analyzed tissue/cells samples may help define the set of untranscribed genes in a given type of tissue or cell, thus narrowing the size of the "missing" proteome and allowing us to focus on defining the reasons behind undetected proteins, namely, whether they are technical (insufficient sensitivity of protein detection) or biological (correspond to not-translated transcripts). We believe that the quantitative polymerase chain reaction (qPCR) can provide an efficient approach to studying low-abundant transcripts related to undetected proteins due to its high sensitivity and the possibility of ensuring the specificity of detection via the simple Sanger sequencing of PCR products. Here we illustrated the feasibility of such an approach on a set of low-abundant transcripts. Although inapplicable to the analysis of whole transcriptome, qPCR can successfully be utilized to profile a limited cohort of transcripts encoded on a particular chromosome, as we previously demonstrated for human chromosome 18.

Plasma proteomic and autoantibody profiles reveal the proteomic characteristics involved in longevity families in Bama, China

Background

Chinese Bama Yao Autonomous County is a well-known longevity region in the world. In the past 30 years, population and genome studies were undertaken to investigate the secret of longevity and showed that longevity is the result of a combination of multiple factors, such as genetic, environmental and other causes. In this study, characteristics of the blood plasma proteomic and autoantibody profiles of people from Bama longevity family were investigated.

Methods

Sixty-six plasma donors from Chinese Bama longevity area were recruited in this study. Thirty-three offsprings of longevous families were selected as case studies (Longevous group) and 33 ABO (blood type), age, and gender-matched subjects from non-longevous families were selected as controls (Normal group). Each group contains 3 biological replicates. Tandem mass tag-based proteomic technique was used to investigate the differentially expressed plasma proteins between the two groups. The auto-reactive IgG antibody profiles of the 3 pooled samples in each group were revealed by human proteome microarrays with 17,000 recombinant human proteins.

Results

Firstly, 525 plasma proteins were quantified and 12 proteins were discovered differentially expressed between the two groups. Secondly, more than 500 proteins were recognized by plasma antibodies, 14 proteins ware differentially reacted with the autoantibodies in the two groups. Bioinformatics analysis showed some of the differential proteins and targeted autoantigens were involved in cancer, cardiovascular disease and immunity.

Conclusions

Proteomic and autoantibody profiles varied between the offspring of longevous and normal families which are from the same area and shared the same environmental factors. The identified differences were reported to be involved in several physiological and pathological pathways. The identified proteins will contribute to a better understanding of the proteomic characteristics of people from Bama longevous area and a revelation of the molecular mechanisms of longevity.

Alterations of Human Plasma Proteome Profile on Adaptation to High-Altitude Hypobaric Hypoxia

For individuals migrating to or residing permanently in high-altitude regions, environmental hypobaric hypoxia is a primary challenge that induces several physiological or pathological responses. It is well documented that human beings adapt to hypobaric hypoxia via some protective mechanisms, such as erythropoiesis and overproduction of hemoglobin; however, little is known on the alterations of plasma proteome profiles in accommodation to high-altitude hypobaric hypoxia. In the present study, we investigated differential plasma proteomes of high altitude natives and lowland normal controls by a TMT-based proteomic approach. A total of 818 proteins were identified, of which 137 were differentially altered. Bioinformatics (including GO, KEGG, protein-protein interactions, etc.) analysis showed that the differentially altered proteins were basically involved in complement and coagulation cascades, antioxidative stress, and glycolysis. Validation results demonstrated that CCL18, C9, PF4, MPO, and S100A9 were notably up-regulated, and HRG and F11 were down-regulated in high altitude natives, which were consistent with TMT-based proteomic results. Our findings highlight the contributions of complement and coagulation cascades, antioxidative stress, and glycolysis in acclimatization to hypobaric hypoxia and provide a foundation for developing potential diagnostic or/and therapeutic biomarkers for high altitude hypobaric hypoxia-induced diseases.

TMT-Based Quantitative Proteomic Analysis Reveals Proteomic Changes Involved in Longevity

PURPOSE

Individual lifespans vary widely, and longevity is the main concern from ancient to modern times. This study is aimed to identify plasma proteins associated with longevity by proteomics technique.

EXPERIMENTAL DESIGN

Tandem mass tags (TMT)-based proteomics analysis is performed for the plasma of Bama longevity group and a control group to analyze the differentially expressed proteins (DEPs). A validation set is used to verify the results of TMT-based proteomics.

RESULTS

Between Bama natives and the control individuals, the authors identify 175 DEPs, which are mainly involved in complement and coagulation cascades, metabolism of glyco and lipid, and regulation of actin cytoskeleton. Consistent with the proteomic analysis, plasma levels of MMP2, CCL5, and PF4 are significantly lower in Bama participants than in controls, whereas IGFBP2 and C9 increase in Bama individuals, in the validation set. By ROC analysis, combinations of these five proteins result in a high AUC value (0.991, 95% CI, 0.929-1.000, p < 0.0001) to distinguish longevous participants from controls.

CONCLUSIONS AND CLINICAL RELEVANCE

The results highlight the roles of complement and coagulation cascades, metabolism of glyco and lipid, and inflammatory and immune response may play important roles in longevity. And the DEPs may serve as clinically useful biomarkers for healthy aging and predicting longevity.

The Gene-Centric Content Management System and Its Application for Cognitive Proteomics

The Human Proteome Project is moving into the next phase of creating and/or reconsidering the functional annotations of proteins using the chromosome-centric paradigm. This challenge cannot be solved exclusively using automated means, but rather requires human intelligence for interpreting the combined data. To foster the integration between human cognition and post-genome array a number of specific tools were recently developed, among them CAPER, GenomewidePDB, and The Proteome Browser (TPB). For the purpose of tackling the task of protein functional annotating the Gene-Centric Content Management System (GenoCMS) was expanded with new features. The goal was to enable bioinformaticans to develop self-made applications and to position these applets within the generalized informational canvas supported by GenoCMS. We report the results of GenoCMS-enabled integration of the concordant informational flows in the chromosome-centric framework of the human chromosome 18 project. The workflow described in the article can be scaled to other human chromosomes, and also supplemented with new tracks created by the user. The GenoCMS is an example of a project-oriented informational system, which are important for public data sharing.