Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line

ZFP36 Inhibits Tumor Progression of Human Prostate Cancer by Targeting CDK6 and Oxidative Stress

Background

The expression of ZFP36 in previous study was reduced in prostate cancer (PCa) tissues as compared to benign prostate tissues, indicating the potential of ZFP36 as an auxiliary marker for PCa. Further evaluation was conducted in clinical samples for in vitro and in vivo experiments, to prove the potential possibility that ZFP36 dysregulation participated in the malignant phenotype of PCa, to determine its potential mechanism for tumor regulation, and to provide a new theoretical basis for gene therapy of PCa.

Methods

First, the expression of ZFP36 in prostate tissue and PCa tissue was explored, and the relationship between ZFP36 and clinical features of PCa patients was illustrated. Subsequently, the impact of ZFP36 on the biology of PCa cells and relevant downstream pathways of ZFP36's biological impact on PCa were elucidated. Finally, whether oxidative stress mediated the regulation of ZFP36 in PCa was verified by the determination of oxidative stress-related indicators and bioinformatics analysis.

Results

The downregulation of ZFP36 in PCa tissue had a positive correlation with high Gleason scores, advanced pathological stage, and biochemical recurrence. ZFP36 was identified as an independent prognostic factor for PCa patients' BCR-free survival (P = 0.022) by survival analysis. Following a subsequent experiment of function gain and loss, ZFP36 inhibited the proliferation, invasion, and migration in DU145 and 22RV1 cells and inhibits tumor growth in the mouse model. Additionally, high-throughput sequencing screened out CDK6 as the downstream target gene of ZFP36. Western blot/Q-PCR demonstrated that overexpression of ZFP36 could reduce the expression of CDK6 at both cellular and animal levels, and the dual-luciferase experiment and RIP experiment proved that CDK6 was the downstream target of ZFP36, indicating that CDK6 was a downstream target of ZFP36, which mediated tumor cell growth by blocking cell cycle at the G1 stage. Furthermore, ZFP36 inhibited oxidative stress in PCa cells.

Conclusions

In PCa, ZFP36 might be a tumor suppressor that regulated growth, invasion, and migration of PCa cells. The lately discovered ZFP36-CDK6 axis demonstrated the molecular mechanism of PCa progression to a certain extent which might act as a new possible therapeutic target of PCa therapy.

Enzyme activity profiling for physiological phenotyping within functional phenomics: plant growth and stress responses

High-throughput profiling of key enzyme activities of carbon, nitrogen, and antioxidant metabolism is emerging as a valuable approach to integrate cell physiological phenotyping into a holistic functional phenomics approach. However, the analyses of the large datasets generated by this method represent a bottleneck, often keeping researchers from exploiting the full potential of their studies. We address these limitations through the exemplary application of a set of data evaluation and visualization tools within a case study. This includes the introduction of multivariate statistical analyses that can easily be implemented in similar studies, allowing researchers to extract more valuable information to identify enzymatic biosignatures. Through a literature meta-analysis, we demonstrate how enzyme activity profiling has already provided functional information on the mechanisms regulating plant development and response mechanisms to abiotic stress and pathogen attack. The high robustness of the distinct enzymatic biosignatures observed during developmental processes and under stress conditions underpins the enormous potential of enzyme activity profiling for future applications in both basic and applied research. Enzyme activity profiling will complement molecular -omics approaches to contribute to the mechanistic understanding required to narrow the genotype-to-phenotype knowledge gap and to identify predictive biomarkers for plant breeding to develop climate-resilient crops.

Drought induces epitranscriptome and proteome changes in stem-differentiating xylem of Populus trichocarpa

Understanding gene expression and regulation requires insights into RNA transcription, processing, modification, and translation. However, the relationship between the epitranscriptome and the proteome under drought stress remains undetermined in poplar (Populus trichocarpa). In this study, we used Nanopore direct RNA sequencing and tandem mass tag-based proteomic analysis to examine epitranscriptomic and proteomic regulation induced by drought treatment in stem-differentiating xylem (SDX). Our results revealed a decreased full-length read ratio under drought treatment and, especially, a decreased association between transcriptome and proteome changes in response to drought. Epitranscriptome analysis of cellulose- and lignin-related genes revealed an increased N6-Methyladenosine (m6A) ratio, which was accompanied by decreased RNA abundance and translation, under drought stress. Interestingly, usage of the distal poly(A) site increased during drought stress. Finally, we found that transcripts of highly expressed genes tend to have shorter poly(A) tail length (PAL), and drought stress increased the percentage of transcripts with long PAL. These findings provide insights into the interplay among m6A, polyadenylation, PAL, and translation under drought stress in P. trichocarpa SDX.

Presence of GnRH3 in sturgeon and the roles of GnRH1 and GnRH2 on the regulation of LH/FSH in mature female sterlet Acipenser ruthenus in vitro

Three forms of gonadotropin-releasing hormones (GnRHs), ArGnRH1, ArGnRH2, and ArGnRH3, were identified in sterlet. Compared with their orthologue, ArGnRH1 and ArGnRH2 have conserved core decapeptide but show low identity in the signal peptide and the rest of the sequences. The existence of the GnRH3 paralogue of sturgeon was predicted for the first time with TBLASTN by using the amino acid sequences of catshark and whale shark GnRH3 precursor as queries against the whole genome and transcript data of sterlet. The predicted ArGnRH3 cDNA sequence was composed of three exons containing all the elements of the GnRH family. The successful molecular cloning of GnRH3 from sterlets verified its expression in the brain of sturgeons. The analysis of the ArGnRH3 amino acid sequence revealed a completely conserved decapeptide sequence that shows 100% identity with the sequence of teleosts and differs in one amino acid with that of the cartilaginous fish (catshark and whale shark) at the 5th position. The structure of the phylogenetic tree showed that a total of 52 vertebrate GnRH sequences were clustered into three main clades corresponding to GnRH1, GnRH2, and GnRH3. The ArGnRH3 sequence is the oldest GnRH3 identified in teleosts. The tissue distribution analysis showed that ArGnRH1 was expressed in all the 13 examined tissues of females and in most of the tested tissues of male fish, with the highest expression in the pituitary and hypothalamus. ArGnRH2 is only expressed in the pituitary, hypothalamus, and gonads of both female and male sterlets. ArGnRH3 mRNA could be detected in the pituitary, hypothalamus, and gonad in both female and male fish. It is also present in the spleen, head kidney, and gill in female fish and in kidney and heart in male fish. However, the ArGnRH3 only showed weak expression in all the positive tissues. ArGnRH1 and ArGnRH2 active decapeptides were synthesized to investigate their roles on the regulation of LH/FSH using a mixed brain cell line from a sexually mature female sterlet. The results showed that ArGnRH1 and ArGnRH2 exerted different effects on the gene expression and release of gonadotropins. ArGnRH1 promoted the expression of fshβ significantly around 48 h, and the expression was suppressed when the treatment time was extended to 72 h. ArGnRH1 had no significant effects on the level of either mRNA or secreted lh in any of the tested treatment length or concentrations. Moreover, ArGnRH1 did not stimulate the activity of gonadotropins in the maturation stage of female sturgeons. ArGnRH2 promoted the expression of fshβ at 24 h and 48 h and increased mRNA level of lhβ at 6 h and 48 h, accompanied by the significant secretion of LH at 72 h, although the high mRNA level of fsh did not correlate with the secretion of FSH in ArGnRH2-treated groups. In conclusion, ArGnRH2 plays an important role in the maturation stage of female sterlets. Therefore, ArGnRH2 has the potential to induce ovulation and spermiation in sturgeons.

Quantitative Protein Analysis of ZPB2, ZPB1 and ZPC in the Germinal Disc and a Non-Germinal Disc Region of the Inner Perivitelline Layer in Two Genetic Lines of Turkey Hens That Differ in Fertility

The avian inner perivitelline layer (IPVL), containing the zona pellucida (ZP) family of proteins, surrounds the ovulated ovum. In mammalian species, ZP proteins serve as key component(s) in binding sperm and initiating the acrosome reaction. Sperm binding at the germinal disc (GD) region of the IPVL initiates fertilization in avian species, and the amount of sperm binding at the GD reflects female fertility. The current research determined whether reported differences in mRNA expression in two genetic lines of turkey hens (E, high fertility and F, low fertility) translated to the protein level. ZPB2 in the IPVL is greater in the GD region compared with the nongerminal disc (NGD) region, as indicated by both mRNA and protein expression. However, protein expressions of ZPB1 and ZPC in the IPVL of E- and F-line turkey hens was in contrast to previously reported mRNA expression. The results indicate that the mRNA expression of ZP proteins at their site of synthesis in E- and F-line hens often does not directly correlate with the IPVL abundance of these proteins. The greater protein concentration of ZPB2 in the GD region compared with the NGD regions suggests that this protein may be critical for sperm binding at the GD region.

Human organ rejuvenation by VEGF-A: Lessons from the skin

Transplanting aged human skin onto young SCID/beige mice morphologically rejuvenates the xenotransplants. This is accompanied by angiogenesis, epidermal repigmentation, and substantial improvements in key aging-associated biomarkers, including ß-galactosidase, p16^ink4a, SIRT1, PGC1α, collagen 17A, and MMP1. Angiogenesis- and hypoxia-related pathways, namely, vascular endothelial growth factor A (VEGF-A) and HIF1A, are most up-regulated in rejuvenated human skin. This rejuvenation cascade, which can be prevented by VEGF-A-neutralizing antibodies, appears to be initiated by murine VEGF-A, which then up-regulates VEGF-A expression/secretion within aged human skin. While intradermally injected VEGF-loaded nanoparticles suffice to induce a molecular rejuvenation signature in aged human skin on old mice, VEGF-A treatment improves key aging parameters also in isolated, organ-cultured aged human skin, i.e., in the absence of functional skin vasculature, neural, or murine host inputs. This identifies VEGF-A as the first pharmacologically pliable master pathway for human organ rejuvenation in vivo and demonstrates the potential of our humanized mouse model for clinically relevant aging research.

Regulation of the Intestinal Extra-Adrenal Steroidogenic Pathway Component LRH-1 by Glucocorticoids in Ulcerative Colitis

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) and can be treated with glucocorticoids (GC), although some patients are unresponsive to this therapy. The transcription factor LRH-1/NR5A2 is critical to intestinal cortisol production (intestinal steroidogenesis), being reduced in UC patients. However, the relationship between LRH-1 expression and distribution with altered corticosteroid responses is unknown. To address this, we categorized UC patients by their steroid response. Here, we found that steroid-dependent and refractory patients presented reduced glucocorticoid receptor (GR)-mediated intestinal steroidogenesis compared to healthy individuals and responder patients, possibly related to increased colonic mucosa GR isoform beta (GRβ) content and cytoplasmic LRH-1 levels in epithelial and lamina propria cells. Interestingly, an intestinal epithelium-specific GR-induced knockout (GR^iKO) dextran sodium sulfate (DSS)-colitis mice model presented decreased epithelial LRH-1 expression, whilst it increased in the lamina propria compared to DSS-treated control mice. Mechanistically, GR directly induced NR5A2 gene expression in CCD841CoN cells and human colonic organoids. Furthermore, GR bound to two glucocorticoid-response elements within the NR5A2 promoter in dexamethasone-stimulated CCD841CoN cells. We conclude that GR contributes to intestinal steroidogenesis by inducing LRH-1 in epithelial cells, suggesting LRH-1 as a potential marker for glucocorticoid-impaired response in UC. However, further studies with a larger patient cohort will be necessary to confirm role of LRH-1 as a therapeutic biomarker.

Vitronectin and Its Interaction with PAI-1 Suggests a Functional Link to Vascular Changes in AMD Pathobiology

The pathogenesis of age-related macular degeneration (AMD), a frequent disorder of the central retina, is incompletely understood. Genome-wide association studies (GWAS) suggest a strong contribution of genomic variation in AMD susceptibility. Nevertheless, little is known about biological mechanisms of the disease. We reported previously that the AMD-associated polymorphism rs704C > T in the vitronectin (VTN) gene influences protein expression and functional aspects of encoded vitronectin, a human blood and extracellular matrix (ECM) protein. Here, we refined the association of rs704 with AMD in 16,144 cases and 17,832 controls and noted that rs704 is carried exclusively by the neovascular AMD subtype. Interaction studies demonstrate that rs704 affects the ability of vitronectin to bind the angiogenic regulator plasminogen activator inhibitor 1 (PAI-1) but has no influence on stabilizing its active state. Western blot analysis and confocal imaging reveal a strong enrichment of PAI-1 in the ECM of cultured endothelial cells and RPE cell line ARPE-19 exposed to vitronectin. Large-scale gene expression of VTN and PAI-1 showed positive correlations and a statistically significant increase in human retinal and blood tissues aged 60 years and older. Our results suggest a mechanism by which the AMD-associated rs704 variant in combination with ageing may contribute to the vascular complications in AMD.

CGRP and the Calcitonin Receptor are Co-Expressed in Mouse, Rat and Human Trigeminal Ganglia Neurons

The neuropeptide calcitonin gene-related peptide (CGRP) is expressed in the trigeminal ganglia, a key site in craniofacial pain and migraine. CGRP potently activates two receptors: the CGRP receptor and the AMY₁ receptor. These receptors are heterodimers consisting of receptor activity-modifying protein 1 (RAMP1) with either the calcitonin receptor-like receptor (CLR) to form the CGRP receptor or the calcitonin receptor (CTR) to form the AMY₁ receptor. The expression of the CGRP receptor in trigeminal ganglia has been described in several studies; however, there is comparatively limited data available describing AMY₁ receptor expression and in which cellular subtypes it is found. This research aimed to determine the relative distributions of the AMY₁ receptor subunit, CTR, and CGRP in neurons or glia in rat, mouse and human trigeminal ganglia. Antibodies against CTR, CGRP and neuronal/glial cell markers were applied to trigeminal ganglia sections to investigate their distribution. CTR-like and CGRP-like immunoreactivity were observed in both discrete and overlapping populations of neurons. In rats and mice, 30–40% of trigeminal ganglia neurons displayed CTR-like immunoreactivity in their cell bodies, with approximately 78–80% of these also containing CGRP-like immunoreactivity. Although human cases were more variable, a similar overall pattern of CTR-like immunoreactivity to rodents was observed in the human trigeminal ganglia. CTR and CGRP appeared to be primarily colocalized in small to medium sized neurons, suggesting that colocalization of CTR and CGRP may occur in C-fiber neurons. CGRP-like or CTR-like immunoreactivity were not typically observed in glial cells. Western blotting confirmed that CTR was expressed in the trigeminal ganglia of all three species. These results confirm that CTR is expressed in trigeminal ganglia neurons. The identification of populations of neurons that express both CGRP and CTR suggests that CGRP could act in an autocrine manner through a CTR-based receptor, such as the AMY₁ receptor. Overall, this suggests that a trigeminal ganglia CTR-based receptor may be activated during migraine and could therefore represent a potential target to develop treatments for craniofacial pain and migraine.

Halting ErbB-2 isoforms retrograde transport to the nucleus as a new theragnostic approach for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is clinically defined by the absence of estrogen and progesterone receptors and the lack of membrane overexpression or gene amplification of receptor tyrosine kinase ErbB-2/HER2. Due to TNBC heterogeneity, clinical biomarkers and targeted therapies for this disease remain elusive. We demonstrated that ErbB-2 is localized in the nucleus (NErbB-2) of TNBC cells and primary tumors, from where it drives growth. We also discovered that TNBC expresses both wild-type ErbB-2 (WTErbB-2) and alternative ErbB-2 isoform c (ErbB-2c). Here, we revealed that the inhibitors of the retrograde transport Retro-2 and its cyclic derivative Retro-2.1 evict both WTErbB-2 and ErbB-2c from the nucleus of BC cells and tumors. Using BC cells from several molecular subtypes, as well as normal breast cells, we demonstrated that Retro-2 specifically blocks proliferation of BC cells expressing NErbB-2. Importantly, Retro-2 eviction of both ErbB-2 isoforms from the nucleus resulted in a striking growth abrogation in multiple TNBC preclinical models, including tumor explants and xenografts. Our mechanistic studies in TNBC cells revealed that Retro-2 induces a differential accumulation of WTErbB-2 at the early endosomes and the plasma membrane, and of ErbB-2c at the Golgi, shedding new light both on Retro-2 action on endogenous protein cargoes undergoing retrograde transport, and on the biology of ErbB-2 splicing variants. In addition, we revealed that the presence of a functional signal peptide and a nuclear export signal (NES), both located at the N-terminus of WTErbB-2, and absent in ErbB-2c, accounts for the differential subcellular distribution of ErbB-2 isoforms upon Retro-2 treatment. Our present discoveries provide evidence for the rational repurposing of Retro-2 as a novel therapeutic agent for TNBC.

Hypertension alters the function and expression profile of the peptide cotransporters PEPT1 and PEPT2 in the rodent renal proximal tubule

Hypertension is a major risk factor for kidney and cardiovascular disease. The treatment of hypertensive individuals by selected ACE inhibitors and certain di-and tripeptides halts the progression of renal deterioration and extends life-span. Renal reabsorption of these low molecular weight substrates are mediated by the PEPT1 and PEPT2 cotransporters. This study aims to investigate whether hypertension and ageing affects renal PEPT cotransporters at gene, protein expression and distribution as well as function in the superficial cortex and the outer medulla of the kidney. Membrane vesicles from the brush border (BBMV) and outer medulla (OMMV) were isolated from the kidneys of young Wistar Kyoto (Y-WKY), young spontaneously hypertensive (Y-SHR), and middle aged SHR (M-SHR) rats. Transport activity was measured using the substrate, β-Ala-Lys (AMCA). Gene expression levels of PEPT genes were assessed with qRT-PCR while renal localisation of PEPT cotransporters was examined by immunohistochemistry with Western Blot validation. The K_m and V_max of renal PEPT1 were decreased significantly in SHR compared to WKY BBMV, whilst the Vmax of PEPT2 showed differences between SHR and WKY. By contrast to the reported cortical distribution of PEPT1, PEPT1-staining was detected in the outer medulla, whilst PEPT2 was expressed primarily in the cortex of all SHR; PEPT1 was significantly upregulated in the cortex of Y-SHR. These outcomes are indicative of a redistribution of PEPT1 and PEPT2 in the kidney proximal tubule under hypertensive conditions that has potential repercussions for nutrient handling and the therapeutic use of ACE inhibitors in hypertensive individuals.

Integrating transcription-factor abundance with chromatin accessibility in human erythroid lineage commitment

Master transcription factors (TFs) directly regulate present and future cell states by binding DNA regulatory elements and driving gene-expression programs. Their abundance influences epigenetic priming to different cell fates at the chromatin level, especially in the context of differentiation. In order to link TF protein abundance to changes in TF motif accessibility and open chromatin, we developed InTAC-seq, a method for simultaneous quantification of genome-wide chromatin accessibility and intracellular protein abundance in fixed cells. Our method produces high-quality data and is a cost-effective alternative to single-cell techniques. We showcase our method by purifying bone marrow (BM) progenitor cells based on GATA-1 protein levels and establish high GATA-1-expressing BM cells as both epigenetically and functionally similar to erythroid-committed progenitors.

Pinpointing Cancer Sub-Type Specific Metabolic Tasks Facilitates Identification of Anti-cancer Targets

Metabolic reprogramming is one of the hallmarks of tumorigenesis. Understanding the metabolic changes in cancer cells may provide attractive therapeutic targets and new strategies for cancer therapy. The metabolic states are not the same in different cancer types or subtypes, even within the same sample of solid tumors. In order to understand the heterogeneity of cancer cells, we used the Pareto tasks inference method to analyze the metabolic tasks of different cancers, including breast cancer, lung cancer, digestive organ cancer, digestive tract cancer, and reproductive cancer. We found that cancer subtypes haves different propensities toward metabolic tasks, and the biological significance of these metabolic tasks also varies greatly. Normal cells treat metabolic tasks uniformly, while different cancer cells focus on different pathways. We then integrated the metabolic tasks into the multi-objective genome-scale metabolic network model, which shows higher accuracy in the in silico prediction of cell states after gene knockout than the conventional biomass maximization model. The predicted potential single drug targets could potentially turn into biomarkers or drug design targets. We further implemented the multi-objective genome-scale metabolic network model to predict synthetic lethal target pairs of the Basal and Luminal B subtypes of breast cancer. By analyzing the predicted synthetic lethal targets, we found that mitochondrial enzymes are potential targets for drug combinations. Our study quantitatively analyzes the metabolic tasks of cancer and establishes cancer type-specific metabolic models, which opens a new window for the development of specific anti-cancer drugs and provides promising treatment plans for specific cancer subtypes.

Modeling the ribosomal small subunit dynamic in Saccharomyces cerevisiae based on TCP-seq data

Translation Complex Profile Sequencing (TCP-seq), a protocol that was developed and implemented on Saccharomyces cerevisiae, provides the footprints of the small subunit (SSU) of the ribosome (with additional factors) across the entire transcriptome of the analyzed organism. In this study, based on the TCP-seq data, we developed for the first-time a predictive model of the SSU density and analyzed the effect of transcript features on the dynamics of the SSU scan in the 5′UTR. Among others, our model is based on novel tools for detecting complex statistical relations tailored to TCP-seq. We quantitatively estimated the effect of several important features, including the context of the upstream AUG, the upstream ORF length and the mRNA folding strength. Specifically, we suggest that around 50% of the variance related to the read counts (RC) distribution near a start codon can be attributed to the AUG context score. We provide the first large scale direct quantitative evidence that shows that indeed AUG context affects the small sub-unit movement. In addition, we suggest that strong folding may cause the detachment of the SSU from the mRNA. We also identified a number of novel sequence motifs that can affect the SSU scan; some of these motifs affect transcription factors and RNA binding proteins. The results presented in this study provide a better understanding of the biophysical aspects related to the SSU scan along the 5′UTR and of translation initiation in S. cerevisiae, a fundamental step toward a comprehensive modeling of initiation.

Variation in Release Factor Abundance Is Not Needed to Explain Trends in Bacterial Stop Codon Usage

In bacteria stop codons are recognized by one of two class I release factors (RF1) recognizing TAG, RF2 recognizing TGA, and TAA being recognized by both. Variation across bacteria in the relative abundance of RF1 and RF2 is thus hypothesized to select for different TGA/TAG usage. This has been supported by correlations between TAG:TGA ratios and RF1:RF2 ratios across multiple bacterial species, potentially also explaining why TAG usage is approximately constant despite extensive variation in GC content. It is, however, possible that stop codon trends are determined by other forces and that RF ratios adapt to stop codon usage, rather than vice versa. Here, we determine which direction of the causal arrow is the more parsimonious. Our results support the notion that RF1/RF2 ratios become adapted to stop codon usage as the same trends, notably the anomalous TAG behavior, are seen in contexts where RF1:RF2 ratios cannot be, or are unlikely to be, causative, that is, at 3'untranslated sites never used for translation termination, in intragenomic analyses, and across archaeal species (that possess only one RF1). We conclude that specifics of RF biology are unlikely to fully explain TGA/TAG relative usage. We discuss why the causal relationships for the evolution of synonymous stop codon usage might be different from those affecting synonymous sense codon usage, noting that transitions between TGA and TAG require two-point mutations one of which is likely to be deleterious.

Increased oxytocinergic system activity in the cardiac muscle in spontaneously hypertensive SHR rats

INTRODUCTION

The present study aimed to determine whether the presence of cardiac hypertrophy due to arterial hypertension is associated with a change in the activity of the oxytocinergic system in cardiomyocytes.

MATERIAL AND METHODS

The experiments were performed on male, spontaneously hypertensive rats (SHR, n = 10) and normotensive Wistar-Kyoto rats (WKY, n = 12). Blood samples were collected from both SHR and WKY animals to asses plasma oxytocin (OT) concentration; the rats were sacrificed by decapitation. Samples of the left and right ventricles were harvested for the analysis of the OT and oxytocin receptor (OTR) protein by ELISA, and OT and OTR mRNA expression by RT-PCR. Immunohistopathological studies were performed to confirm the presence of OTR receptors in the cardiac muscle of the ventricles.

RESULTS

Plasma OT concentration did not differ between SHR and WKY rats. In the SHR rats, the expression of OT mRNA and the OT protein level was higher in the left and the right ventricle, while OTR mRNA expression was significantly lower in both the left and the right ventricle. However, the level of OTR protein was higher only in the left ventricle of the SHR rats. The presence of OTR receptors was confirmed by immunohistochemical analysis in the muscle of the right and left ventricle.

CONCLUSIONS

The presence of arterial hypertension is associated with increased activity of the oxytocinergic system in the heart, especially in the area of the left ventricle. These findings support the important role of this system in the maintenance of cardiovascular homeostasis.

A Standardized Brain Molecular Atlas: A Resource for Systems Modeling and Simulation

Accurate molecular concentrations are essential for reliable analyses of biochemical networks and the creation of predictive models for molecular and systems biology, yet protein and metabolite concentrations used in such models are often poorly constrained or irreproducible. Challenges of using data from different sources include conflicts in nomenclature and units, as well as discrepancies in experimental procedures, data processing and implementation of the model. To obtain a consistent estimate of protein and metabolite levels, we integrated and normalized data from a large variety of sources to calculate Adjusted Molecular Concentrations. We found a high degree of reproducibility and consistency of many molecular species across brain regions and cell types, consistent with tight homeostatic regulation. We demonstrated the value of this normalization with differential protein expression analyses related to neurodegenerative diseases, brain regions and cell types. We also used the results in proof-of-concept simulations of brain energy metabolism. The standardized Brain Molecular Atlas overcomes the obstacles of missing or inconsistent data to support systems biology research and is provided as a resource for biomolecular modeling.

Transcriptomic and proteomic analysis of pyrethroid resistance in the CKR strain of Aedes aegypti

Aedes aegypti is an important vector of human viral diseases. This mosquito is distributed globally and thrives in urban environments, making it a serious risk to human health. Pyrethroid insecticides have been the mainstay for control of adult A. aegypti for decades, but resistance has evolved, making control problematic in some areas. One major mechanism of pyrethroid resistance is detoxification by cytochrome P450 monooxygenases (CYPs), commonly associated with the overexpression of one or more CYPs. Unfortunately, the molecular basis underlying this mechanism remains unknown. We used a combination of RNA-seq and proteomic analysis to evaluate the molecular basis of pyrethroid resistance in the highly resistant CKR strain of A. aegypti. The CKR strain has the resistance mechanisms from the well-studied Singapore (SP) strain introgressed into the susceptible Rockefeller (ROCK) strain genome. The RNA-seq and proteomics data were complimentary; each offering insights that the other technique did not provide. However, transcriptomic results did not quantitatively mirror results of the proteomics. There were 10 CYPs which had increased expression of both transcripts and proteins. These CYPs appeared to be largely trans-regulated, except for some CYPs for which we could not rule out gene duplication. We identified 65 genes and lncRNAs as potentially being responsible for elevating the expression of CYPs in CKR. Resistance was associated with multiple loci on chromosome 1 and at least one locus on chromosome 3. We also identified five CYPs that were overexpressed only as proteins, suggesting that stabilization of CYP proteins could be a mechanism of resistance. Future studies to increase the resolution of the resistance loci, and to examine the candidate genes and lncRNAs identified here will greatly enhance our understanding of CYP-mediated resistance in A. aegypti.

Effect of Ionizing Radiation on the Transcript Variants Expression of p21 Gene

PURPOSE

CDK1A is one of the most important genes that have different key roles in cell lines. This gene has several transcript variants. Investigating of expression of each one actually can be so important because any one of them may have a separate unknown role in cancer cells so can be used to increase therapeutic efficacy.

METHODS

A549, MDA-MB-231 and Hek-AD cell lines were used in this study. Firstly, three primers for variants of p21 gene were designed by Snapgene and BLAST software. Secondly, the variants expression was checked for each cell lines by RT-qPCR technique, separately. Then the variants that expressed in the cells were selected for more investigation. Finally 2 Gy irradiation was used to evaluate the effect of that on variants expression.

RESULTS

The results show that for all cell lines, primer num1 and 3 expressed before any stimuli. After irradiation, for MDA-MB-231 and A549, the expression of primer num3 was decreased, while for Hek-AD no change was observed. The primer num1 expression after the irradiation was different for the cells, V1 expression was decreased in A549 by fold of 0.03 while expression of this for MDA-MB-231 cells was not changed after 2Gy irradiation.

CONCLUSION

It is very necessary to pay attention to the function of each splice variant as well as the response to external stimuli. Understanding the role of each variant in a gene is critical and researchers can use that to improve radiotherapy as well.

Regulation of gene expression via translational buffering

Translation of an mRNA represents a critical step during the expression of protein-coding genes. As mechanisms governing post-transcriptional regulation of gene expression are progressively unveiled, it is becoming apparent that transcriptional programs are not fully reflected in the proteome. Herein, we highlight a previously underappreciated post-transcriptional mode of regulation of gene expression termed translational buffering. In principle, translational buffering opposes the impact of alterations in mRNA levels on the proteome. We further describe three types of translational buffering: compensation, which maintains protein levels e.g. across species or individuals; equilibration, which retains pathway stoichiometry; and offsetting, which acts as a reversible mechanism that maintains the levels of selected subsets of proteins constant despite genetic alteration and/or stress-induced changes in corresponding mRNA levels. While mechanisms underlying compensation and equilibration have been reviewed elsewhere, the principal focus of this review is on the less-well understood mechanism of translational offsetting. Finally, we discuss potential roles of translational buffering in homeostasis and disease.

G1-like PB2 gene improves virus replication and competitive advantage of H9N2 virus

H9N2 subtype avian influenza virus has dramatically evolved and undergone extensive reassortment since its emergence in early 1990s in China. The genotype S (G57), emerging in 2007 with the substitution of F98-like PB2 and M gene by G1-like ones, has become the overwhelming predominant genotype for the past 11 years since 2010. Here, we found that virus with G1-like PB2 were more efficient in protein expression and in infectious virus production than that with F98-like PB2 gene. By coinfected MDCK cells with the reassortant virus, more survival opportunity for viruses with G1-like PB2 than that of F/98-like was observed. Besides, in animal experiments, we found that the G1-like PB2 increases virus infectivity, replication, and virus shedding of H9N2 in chickens. Our results suggested that the substitution of G1-like PB2 play important role in promoting the fitness of genotype S H9N2 virus in China.

The plasticity of mRNA translation during cancer progression and therapy resistance

Translational control of mRNAs during gene expression allows cells to promptly and dynamically adapt to a variety of stimuli, including in neoplasia in response to aberrant oncogenic signalling (for example, PI3K-AKT-mTOR, RAS-MAPK and MYC) and microenvironmental stress such as low oxygen and nutrient supply. Such translational rewiring allows rapid, specific changes in the cell proteome that shape specific cancer phenotypes to promote cancer onset, progression and resistance to anticancer therapies. In this Review, we illustrate the plasticity of mRNA translation. We first highlight the diverse mechanisms by which it is regulated, including by translation factors (for example, eukaryotic initiation factor 4F (eIF4F) and eIF2), RNA-binding proteins, tRNAs and ribosomal RNAs that are modulated in response to aberrant intracellular pathways or microenvironmental stress. We then describe how translational control can influence tumour behaviour by impacting on the phenotypic plasticity of cancer cells as well as on components of the tumour microenvironment. Finally, we highlight the role of mRNA translation in the cellular response to anticancer therapies and its promise as a key therapeutic target.

ZFP36L2 Role in Thyroid Functionality

Thyroid hormone levels are usually genetically determined. Thyrocytes produce a unique set of enzymes that are dedicated to thyroid hormone synthesis. While thyroid transcriptional regulation is well-characterized, post-transcriptional mechanisms have been less investigated. Here, we describe the involvement of ZFP36L2, a protein that stimulates degradation of target mRNAs, in thyroid development and function, by in vivo and in vitro gene targeting in thyrocytes. Thyroid-specific Zfp36l2-/- females were hypothyroid, with reduced levels of circulating free Thyroxine (cfT4) and Triiodothyronine (cfT3). Their hypothyroidism was due to dyshormonogenesis, already evident one week after weaning, while thyroid development appeared normal. We observed decreases in several thyroid-specific transcripts and proteins, such as Nis and its transcriptional regulators (Pax8 and Nkx2.1), and increased apoptosis in Zfp36l2-/- thyroids. Nis, Pax8, and Nkx2.1 mRNAs were also reduced in Zfp36l2 knock-out thyrocytes in vitro (L2KO), in which we confirmed the increased apoptosis. Finally, in L2KO cells, we showed an altered response to TSH stimulation regarding both thyroid-specific gene expression and cell proliferation and survival. This result was supported by increases in P21/WAF1 and p-P38MAPK levels. Mechanistically, we confirmed Notch1 as a target of ZFP36L2 in the thyroid since its levels were increased in both in vitro and in vivo models. In both models, the levels of Id4 mRNA, a potential inhibitor of Pax8 activity, were increased. Overall, the data indicate that the regulation of mRNA stability by ZFP36L2 is a mechanism that controls the function and survival of thyrocytes.

Anticancer activity of RAPTA-EA1 in triple-negative BRCA1 proficient breast cancer cells: single and combined treatment with the PARP inhibitor olaparib

RAPTA-EA1 is a promising glutathione transferase (GSTP-1) inhibitor that has previously been shown to inhibit the growth of various breast cancer cells. We studied the anticancer activity of RAPTA-EA1 on triple-negative BRCA1 competent breast cancer MDA-MB-231 cells. MDA-MB-231 cells are significantly more sensitive to RAPTA-EA1 than MCF-7 cells. Treatment reveals a higher degree of cytotoxicity than cisplatin against both cell lines. Ruthenium accumulation in MDA-MB-231 cells is mainly in the nuclear fraction (43%), followed by the cytoplasm (30%), and the mitochondria (27%). RAPTA-EA1 blocks cell growth at the G2/M phase, leading to nuclear condensation and cell death. The compound slightly inhibits DNA replication of the 3,426-bp fragment of the BRCA1 exon 11 of the cells, with approximately 0.6 lesion per the BRCA1 fragment. The expression of BRCA1 mRNA and its protein in the Ru-treated cells is curtailed by 50–80% compared to the untreated controls. Growth inhibition of the triple-negative BRCA1 wild-type MDA-MB-231 and the sporadic BRCA1 wild-type MCF-7 cells by olaparib (a poly [ADP-ribose] polymerase (PARP) inhibitor) is dose-dependent, with MDA-MB-231 cells being two-fold less susceptible to the drug than MCF-7 cells. Combining olaparib with RAPTA-EA1 results in a combination index (CI) of 0.78 (almost additive) in MDA-MB-231 cells and 0.24 (potent synergy) in the MCF-7 cells. The PARP inhibitor alone differently regulates the expression of BRCA1 mRNA in both cell lines, whereas the olaparib-RAPTA-EA1 combination induces overexpression of BRCA1 mRNA in these cells. However, the expression level of the BRCA1 protein is dramatically reduced after treatment with the combined inhibitors, compared with the untreated controls. This observation highlights the cellular responses of triple-negative BRCA1 proficient breast cancer MDA-MB-231 cells to RAPTA-EA1 through BRCA1 inhibition and provides insights into alternative treatments for breast cancer.

Gene and protein expression in human megakaryocytes derived from induced pluripotent stem cells

BACKGROUND

There is interest in deriving megakaryocytes (MKs) from pluripotent stem cells (iPSC) for biological studies. We previously found that genomic structural integrity and genotype concordance is maintained in iPSC-derived MKs.

OBJECTIVE

To establish a comprehensive dataset of genes and proteins expressed in iPSC-derived MKs.

METHODS

iPSCs were reprogrammed from peripheral blood mononuclear cells (MNCs) and MKs were derived from the iPSCs in 194 healthy European American and African American subjects. mRNA was isolated and gene expression measured by RNA sequencing. Protein expression was measured in 62 of the subjects using mass spectrometry.

RESULTS AND CONCLUSIONS

MKs expressed genes and proteins known to be important in MK and platelet function and demonstrated good agreement with previous studies in human MKs derived from CD34+ progenitor cells. The percent of cells expressing the MK markers CD41 and CD42a was consistent in biological replicates, but variable across subjects, suggesting that unidentified subject-specific factors determine differentiation of MKs from iPSCs. Gene and protein sets important in platelet function were associated with increasing expression of CD41/42a, while those related to more basic cellular functions were associated with lower CD41/42a expression. There was differential gene expression by the sex and race (but not age) of the subject. Numerous genes and proteins were highly expressed in MKs but not known to play a role in MK or platelet function; these represent excellent candidates for future study of hematopoiesis, platelet formation, and/or platelet function.

Quantitative Modeling of Protein Synthesis Using Ribosome Profiling Data

Quantitative prediction on protein synthesis requires accurate translation initiation and codon translation rates. Ribosome profiling data, which provide steady-state distribution of relative ribosome occupancies along a transcript, can be used to extract these rate parameters. Various methods have been developed in the past few years to measure translation-initiation and codon translation rates from ribosome profiling data. In the review, we provide a detailed analysis of the key methods employed to extract the translation rate parameters from ribosome profiling data. We further discuss how these approaches were used to decipher the role of various structural and sequence-based features of mRNA molecules in the regulation of gene expression. The utilization of these accurate rate parameters in computational modeling of protein synthesis may provide new insights into the kinetic control of the process of gene expression.

Learning the Regulatory Code of Gene Expression

Data-driven machine learning is the method of choice for predicting molecular phenotypes from nucleotide sequence, modeling gene expression events including protein-DNA binding, chromatin states as well as mRNA and protein levels. Deep neural networks automatically learn informative sequence representations and interpreting them enables us to improve our understanding of the regulatory code governing gene expression. Here, we review the latest developments that apply shallow or deep learning to quantify molecular phenotypes and decode the cis-regulatory grammar from prokaryotic and eukaryotic sequencing data. Our approach is to build from the ground up, first focusing on the initiating protein-DNA interactions, then specific coding and non-coding regions, and finally on advances that combine multiple parts of the gene and mRNA regulatory structures, achieving unprecedented performance. We thus provide a quantitative view of gene expression regulation from nucleotide sequence, concluding with an information-centric overview of the central dogma of molecular biology.

TMT-based quantitative proteomics analysis reveals the key proteins related with the differentiation process of goat intramuscular adipocytes

Background

Intramuscular adipocytes differentiation is a complex process, which is regulated by various transcription factor, protein factor regulators and signal transduction pathways. However, the proteins and signal pathways that regulates goat intramuscular adipocytes differentiation remains unclear.

Result

In this study, based on nanoscale liquid chromatography mass spectrometry analysis (LC-MS/MS), the tandem mass tag (TMT) labeling analysis was used to investigate the differentially abundant proteins (DAPs) related with the differentiation process of goat intramuscular adipocytes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes enrichment and protein-protein interaction network analyses were performed for the characterization of the identified DAPs. The candidate proteins were verified by parallel reaction monitoring analysis. As a result, a total of 123 proteins, 70 upregulation proteins and 53 downregulation proteins, were identified as DAPs which may be related with the differentiation process of goat intramuscular adipocytes. Furthermore, the cholesterol metabolism pathway, glucagon signaling pathway and glycolysis / gluconeogenesis pathway were noticed that may be the important signal pathways for goat Intramuscular adipocytes differentiation.

Conclusions

By proteomic comparison between goat intramuscular preadipocytes (P_IMA) and intramuscular adipocytes (IMA), we identified a series protein that might play important role in the goat intramuscular fat differentiation, such as SRSF10, CSRP3, APOH, PPP3R1, CRTC2, FOS, SERPINE1 and AIF1L, could serve as candidates for further elucidate the molecular mechanism of IMF differentiation in goats.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07730-y.

Comparative analysis of the relationship between translation efficiency and sequence features of endogenous proteins in multiple organisms

The translation efficiency of protein genes is known to be affected by sequence features. Previous studies have found that various sequence features based on codon usage and mRNA secondary structure contribute to translation efficiency. However, most studies have focused on a specific organism, usually a model organism such as Escherichia coli or Saccharomyces cerevisiae. Here, we investigate whether the relationship between translation efficiency and sequence features is conserved among multiple organisms using publicly available ribosome profiling data and RNA-Seq data. We analyze nine organisms from various taxa: Staphylococcus aureus, five species of Streptomyces, two strains of E. coli, and S. cerevisiae. We reveal that the relationship between translation efficiency and sequence features differs across organisms, partly reflecting their taxonomy. The codon adaptation index shows high correlation in all analyzed organisms. Our study provides an insight into the diversity and commonality of sequence determinants of protein expression in these organisms.

Predicting mRNA Abundance Directly from Genomic Sequence Using Deep Convolutional Neural Networks

Algorithms that accurately predict gene structure from primary sequence alone were transformative for annotating the human genome. Can we also predict the expression levels of genes based solely on genome sequence? Here, we sought to apply deep convolutional neural networks toward that goal. Surprisingly, a model that includes only promoter sequences and features associated with mRNA stability explains 59% and 71% of variation in steady-state mRNA levels in human and mouse, respectively. This model, termed Xpresso, more than doubles the accuracy of alternative sequence-based models and isolates rules as predictive as models relying on chromatic immunoprecipitation sequencing (ChIP-seq) data. Xpresso recapitulates genome-wide patterns of transcriptional activity, and its residuals can be used to quantify the influence of enhancers, heterochromatic domains, and microRNAs. Model interpretation reveals that promoter-proximal CpG dinucleotides strongly predict transcriptional activity. Looking forward, we propose cell-type-specific gene-expression predictions based solely on primary sequences as a grand challenge for the field.

Profiling of Small Ribosomal Subunits Reveals Modes and Regulation of Translation Initiation

Translation initiation is often attributed as the rate-determining step of eukaryotic protein synthesis and key to gene expression control. Despite this centrality, the series of steps involved in this process is poorly understood. Here, we capture the transcriptome-wide occupancy of ribosomes across all stages of translation initiation, enabling us to characterize the transcriptome-wide dynamics of ribosome recruitment to mRNAs, scanning across 5' UTRs and stop codon recognition, in a higher eukaryote. We provide mechanistic evidence for ribosomes attaching to the mRNA by threading the mRNA through the small subunit. Moreover, we identify features that regulate the recruitment and processivity of scanning ribosomes and redefine optimal initiation contexts. Our approach enables deconvoluting translation initiation into separate stages and identifying regulators at each step.

Predicting mean ribosome load for 5'UTR of any length using deep learning

The 5’ untranslated region plays a key role in regulating mRNA translation and consequently protein abundance. Therefore, accurate modeling of 5’UTR regulatory sequences shall provide insights into translational control mechanisms and help interpret genetic variants. Recently, a model was trained on a massively parallel reporter assay to predict mean ribosome load (MRL)—a proxy for translation rate—directly from 5’UTR sequence with a high degree of accuracy. However, this model is restricted to sequence lengths investigated in the reporter assay and therefore cannot be applied to the majority of human sequences without a substantial loss of information. Here, we introduced frame pooling, a novel neural network operation that enabled the development of an MRL prediction model for 5’UTRs of any length. Our model shows state-of-the-art performance on fixed length randomized sequences, while offering better generalization performance on longer sequences and on a variety of translation-related genome-wide datasets. Variant interpretation is demonstrated on a 5’UTR variant of the gene HBB associated with beta-thalassemia. Frame pooling could find applications in other bioinformatics predictive tasks. Moreover, our model, released open source, could help pinpoint pathogenic genetic variants.

The human genome carries a complex code. It consists of genes, which provide blueprints to assemble proteins, and regulatory elements, which control when, where, and how often particular genes are transcribed and translated into protein. To read the genome correctly and specifically to find the causes of inherited diseases, we need to be able to find and interpret these regulatory elements. Here, we focus on particular regions of the genome, the so-called 5’ untranslated regions, which play an important role in determining how often a transcribed gene is translated into protein. We develop deep learning models which can quantitatively interpret regulatory elements in human 5’ untranslated regions and use this information to predict a proxy of the translation efficiency. Our model generalizes a previous model to 5’ untranslated regions of any length, just as they are encountered in natural human genes. Because this model requires only the sequence as input, it can give estimates for the impact of mutations in the sequence, even if these particular mutations are very rare or entirely novel. Such estimates could help pinpoint mutations that disrupt the normal functioning of gene regulation, which could be used to better diagnose patients suffering from rare genetic disorders.

Multifaceted control of mRNA translation machinery in cancer

The mRNA translation machinery is tightly regulated through several, at times overlapping, mechanisms that modulate its efficiency and accuracy. Due to their fast rate of growth and metabolism, cancer cells require an excessive amount of mRNA translation and protein synthesis. However, unfavorable conditions, such as hypoxia, amino acid starvation, and oxidative stress, which are abundant in cancer, as well as many anti-cancer treatments inhibit mRNA translation. Cancer cells adapt to the various internal and environmental stresses by employing specialised transcript-specific translation to survive and gain a proliferative advantage. We will highlight the major signaling pathways and mechanisms of translation that regulate the global or mRNA-specific translation in response to the intra- or extra-cellular signals and stresses that are key components in the process of tumourigenesis.

SeP is elevated in NAFLD and participates in NAFLD pathogenesis through AMPK/ACC pathway

Nonalcoholic fatty liver disease (NAFLD) is prevalent chronic liver diseases with unknown mechanism and no curative treatment. Hepatokines have demonstrated importance in NAFLD but, role of selenoprotein P (SeP) in NAFLD is unknown. A total of 79 patients with NAFLD and 79 healthy controls were included in this case-control study. SeP is elevated in patients with NAFLD. With elevating level of SeP, NAFLD prevalence, and detecting rate increases. As NAFLD aggravated, serum SeP increases. Correlation analysis demonstrates that SeP is positively associated with NAFLD risk factors including body mass index, alanine aminotransferase, aspartate aminotransferase, gamma-glutamyltransferase, and serum uric acid. Both NAFLD in vivo and in vitro models, SeP protein level is higher in liver. Small interfering RNA of SEPP1 inhibited TG accumulation by activating adenosine monophosphate activated protein kinase/acetyl-CoA carboxylase (AMPK/ACC), and overexpression of SEPP1 aggravated lipid accumulation and inhibited AMPK/ACC phosphorylation. SeP expression is activated in NAFLD and exacerbated NAFLD through AMPK/ACC, providing insight into new diagnostic, therapeutic target in NAFLD.

Proteomic/transcriptomic analysis of erythropoiesis

PURPOSE OF REVIEW

Erythropoiesis is a hierarchical process by which hematopoietic stem cells give rise to red blood cells through gradual cell fate restriction and maturation. Deciphering this process requires the establishment of dynamic gene regulatory networks (GRNs) that predict the response of hematopoietic cells to signals from the environment. Although GRNs have historically been derived from transcriptomic data, recent proteomic studies have revealed a major role for posttranscriptional mechanisms in regulating gene expression during erythropoiesis. These new findings highlight the need to integrate proteomic data into GRNs for a refined understanding of erythropoiesis.

RECENT FINDINGS

Here, we review recent proteomic studies that have furthered our understanding of erythropoiesis with a focus on quantitative mass spectrometry approaches to measure the abundance of transcription factors and cofactors during differentiation. Furthermore, we highlight challenges that remain in integrating transcriptomic, proteomic, and other omics data into a predictive model of erythropoiesis, and discuss the future prospect of single-cell proteomics.

SUMMARY

Recent proteomic studies have considerably expanded our knowledge of erythropoiesis beyond the traditional transcriptomic-centric perspective. These findings have both opened up new avenues of research to increase our understanding of erythroid differentiation, while at the same time presenting new challenges in integrating multiple layers of information into a comprehensive gene regulatory model.

Proteogenomic interrogation of cancer cell lines: an overview of the field

Introduction: Cancer cell lines (CCLs) have been a major resource for cancer research. Over the past couple of decades, they have been instrumental in omic profiling method development and as model systems to generate new knowledge in cell and cancer biology. More recently, with the increasing amount of genomic, transcriptomic and proteomic data being generated in hundreds of CCLs, there is growing potential for integrative proteogenomic data analyses to be performed.Areas covered: In this review, we first describe the most commonly used proteome profiling methods in CCLs. We then discuss how these proteomics data can be integrated with genomics data for proteogenomics analyses. Finally, we highlight some of the recent biological discoveries that have arisen from proteogenomics analyses of CCLs.Expert opinion: Protegeonomics analyses of CCLs have so far enabled the discovery of novel proteins and proteoforms. It has also improved our understanding of biological processes including post-transcriptional regulation of protein abundance and the presentation of antigens by major histocompatibility complex alleles. With proteomics data to be generated in hundreds to thousands of CCLs in coming years, there will be further potential for large-scale proteogenomics analyses and data integration with the phenotypically well-characterized CCLs.

Factors affecting the rapid changes of protein under short-term heat stress

BACKGROUND

Protein content determines the state of cells. The variation in protein abundance is crucial when organisms are in the early stages of heat stress, but the reasons affecting their changes are largely unknown.

RESULTS

We quantified 47,535 mRNAs and 3742 proteins in the filling grains of wheat in two different thermal environments. The impact of mRNA abundance and sequence features involved in protein translation and degradation on protein expression was evaluated by regression analysis. Transcription, codon usage and amino acid frequency were the main drivers of changes in protein expression under heat stress, and their combined contribution explains 58.2 and 66.4% of the protein variation at 30 and 40 °C (20 °C as control), respectively. Transcription contributes more to alterations in protein content at 40 °C (31%) than at 30 °C (6%). Furthermore, the usage of codon AAG may be closely related to the rapid alteration of proteins under heat stress. The contributions of AAG were 24 and 13% at 30 and 40 °C, respectively.

CONCLUSION

In this study, we analyzed the factors affecting the changes in protein expression in the early stage of heat stress and evaluated their influence.

EDC3 phosphorylation regulates growth and invasion through controlling P-body formation and dynamics

Regulation of mRNA stability and translation plays a critical role in determining protein abundance within cells. Processing bodies (P-bodies) are critical regulators of these processes. Here, we report that the Pim1 and 3 protein kinases bind to the P-body protein enhancer of mRNA decapping 3 (EDC3) and phosphorylate EDC3 on serine (S)161, thereby modifying P-body assembly. EDC3 phosphorylation is highly elevated in many tumor types, is reduced upon treatment of cells with kinase inhibitors, and blocks the localization of EDC3 to P-bodies. Prostate cancer cells harboring an EDC3 S161A mutation show markedly decreased growth, migration, and invasion in tissue culture and in xenograft models. Consistent with these phenotypic changes, the expression of integrin β1 and α6 mRNA and protein is reduced in these mutated cells. These results demonstrate that EDC3 phosphorylation regulates multiple cancer-relevant functions and suggest that modulation of P-body activity may represent a new paradigm for cancer treatment.

Leveraging Single-Cell Sequencing for Chimeric Antigen Receptor T Cell Therapies

Chimeric antigen receptor (CAR)-T cell therapies against cancer continue to make inroads in the clinic. However, progress is still hindered by subpar efficacy against many tumors. Gaining a better understanding of CAR-induced T cell activation would help identify and remediate the causes of treatment failure. Increasingly, technologies to analyze the transcriptome are used to molecularly profile the behavior of CAR-T cells, both before and after treatment. Here, we describe recent work on how gene expression signatures, especially those obtained from single-cell RNA sequencing (scRNA-seq), can be used to characterize CAR design, production conditions, therapy combinations, and finally disease outcome. In the future, scRNA-seq could become a standard tool for the development and clinical monitoring of CAR-T cell therapies.

A mark of disease: how mRNA modifications shape genetic and acquired pathologies

RNA modifications have recently emerged as a widespread and complex facet of gene expression regulation. Counting more than 170 distinct chemical modifications with far-reaching implications for RNA fate, they are collectively referred to as the epitranscriptome. These modifications can occur in all RNA species, including messenger RNAs (mRNAs) and noncoding RNAs (ncRNAs). In mRNAs the deposition, removal, and recognition of chemical marks by writers, erasers and readers influence their structure, localization, stability, and translation. In turn, this modulates key molecular and cellular processes such as RNA metabolism, cell cycle, apoptosis, and others. Unsurprisingly, given their relevance for cellular and organismal functions, alterations of epitranscriptomic marks have been observed in a broad range of human diseases, including cancer, neurological and metabolic disorders. Here, we will review the major types of mRNA modifications and editing processes in conjunction with the enzymes involved in their metabolism and describe their impact on human diseases. We present the current knowledge in an updated catalog. We will also discuss the emerging evidence on the crosstalk of epitranscriptomic marks and what this interplay could imply for the dynamics of mRNA modifications. Understanding how this complex regulatory layer can affect the course of human pathologies will ultimately lead to its exploitation toward novel epitranscriptomic therapeutic strategies.

Selection for Cheaper Amino Acids Drives Nucleotide Usage at the Start of Translation in Eukaryotic Genes

Coding regions have complex interactions among multiple selective forces, which are manifested as biases in nucleotide composition. Previous studies have revealed a decreasing GC gradient from the 5′-end to 3′-end of coding regions in various organisms. We confirmed that this gradient is universal in eukaryotic genes, but the decrease only starts from the ∼ 25th codon. This trend is mostly found in nonsynonymous (ns) sites at which the GC gradient is universal across the eukaryotic genome. Increased GC contents at ns sites result in cheaper amino acids, indicating a universal selection for energy efficiency toward the N-termini of encoded proteins. Within a genome, the decreasing GC gradient is intensified from lowly to highly expressed genes (more and more protein products), further supporting this hypothesis. This reveals a conserved selective constraint for cheaper amino acids at the translation start that drives the increased GC contents at ns sites. Elevated GC contents can facilitate transcription but result in a more stable local secondary structure around the start codon and subsequently impede translation initiation. Conversely, the GC gradients at four-fold and two-fold synonymous sites vary across species. They could decrease or increase, suggesting different constraints acting at the GC contents of different codon sites in different species. This study reveals that the overall GC contents at the translation start are consequences of complex interactions among several major biological processes that shape the nucleotide sequences, especially efficient energy usage.

Innate Immune Responses of Galleria mellonella to Mycobacterium bovis BCG Challenge Identified Using Proteomic and Molecular Approaches

The larvae of the insect Galleria mellonella, have recently been established as a non-mammalian infection model for the Mycobacterium tuberculosis complex (MTBC). To gain further insight into the potential of this model, we applied proteomic (label-free quantification) and transcriptomic (gene expression) approaches to characterise the innate immune response of G. mellonella to infection with Mycobacterium bovis BCG lux over a 168 h time course. Proteomic analysis of the haemolymph from infected larvae revealed distinct changes in the proteome at all time points (4, 48, 168 h). Reverse transcriptase quantitative PCR confirmed induction of five genes (gloverin, cecropin, IMPI, hemolin, and Hdd11), which encoded proteins found to be differentially abundant from the proteomic analysis. However, the trend between gene expression and protein abundance were largely inconsistent (20%). Overall, the data are in agreement with previous phenotypic observations such as haemocyte internalization of mycobacterial bacilli (hemolin/β-actin), formation of granuloma-like structures (Hdd11), and melanization (phenoloxidase activating enzyme 3 and serpins). Furthermore, similarities in immune expression in G. mellonella, mouse, zebrafish and in vitro cell-line models of tuberculosis infection were also identified for the mechanism of phagocytosis (β-actin). Cecropins (antimicrobial peptides), which share the same α-helical motif as a highly potent peptide expressed in humans (h-CAP-18), were induced in G. mellonella in response to infection, giving insight into a potential starting point for novel antimycobacterial agents. We believe that these novel insights into the innate immune response further contribute to the validation of this cost-effective and ethically acceptable insect model to study members of the MTBC.

Reciprocal relation between reporter gene transcription and translation efficiency in fission yeast

The fission yeast, Schizosaccharomyces pombe, is an excellent model for basic research but is not useful for commercial scale protein expression due to lack of strong expression vectors. Earlier, we showed that the lsd90 promoter elicited significantly greater GFP expression level than the adh1 and nmt1 promoters, albeit in different vector backbones. Here, we have systematically investigated the contribution of selectable markers, LEU2 and URA3m to GFP expression: while LEU2 elicited very low expression, the URA3m gene, with truncated promoter, elicited much greater GFP expression level with all promoters. Paradoxically, an inverse correlation was observed between the GFP transcription and translation efficiency. This system can be useful for understanding the factors governing recombinant gene expression and optimization of protein production.

A Modelling Framework Linking Resource-Based Stochastic Translation to the Optimal Design of Synthetic Constructs

Simple Summary

In synthetic biology, it is commonplace to design and insert gene expression constructs into cells for the production of useful proteins. In order to maximise production yield, it is useful to predict the performance of these “engineered cells” in advance of conducting experiments. This is typically a complex task, which in recent years has motivated the use of “whole-cell models” (WCMs) that act as computational tools for predicting different aspects of cell growth. Many useful WCMs exist, however a common problem is their over-simplification of ribosome movement on mRNA transcripts during translation. WCMs typically don’t consider that, for constructs with inefficient (“slow”) codons, ribosomes can stall and form “traffic jams”, thereby becoming unavailable for translation of other proteins. To more accurately address these scenarios, we have built a computational framework that combines whole-cell modelling with a detailed account of ribosome movement on mRNA. We show how our framework can be used to link the modular design of a gene expression construct (via its promoter, ribosome binding site and codon composition) to protein yield during continuous cell culture, with a particular focus on how the optimal design can change over time in the presence or absence of “slow” codons.

Abstract

The effect of gene expression burden on engineered cells has motivated the use of “whole-cell models” (WCMs) that use shared cellular resources to predict how unnatural gene expression affects cell growth. A common problem with many WCMs is their inability to capture translation in sufficient detail to consider the impact of ribosomal queue formation on mRNA transcripts. To address this, we have built a “stochastic cell calculator” (StoCellAtor) that combines a modified TASEP with a stochastic implementation of an existing WCM. We show how our framework can be used to link a synthetic construct’s modular design (promoter, ribosome binding site (RBS) and codon composition) to protein yield during continuous culture, with a particular focus on the effects of low-efficiency codons and their impact on ribosomal queues. Through our analysis, we recover design principles previously established in our work on burden-sensing strategies, namely that changing promoter strength is often a more efficient way to increase protein yield than RBS strength. Importantly, however, we show how these design implications can change depending on both the duration of protein expression, and on the presence of ribosomal queues.

Liquid Biopsy Enables Quantification of the Abundance and Interindividual Variability of Hepatic Enzymes and Transporters

Variability in individual capacity for hepatic elimination of therapeutic drugs is well recognized and is associated with variable expression and activity of liver enzymes and transporters. Although genotyping offers some degree of stratification, there is often large variability within the same genotype. Direct measurement of protein expression is impractical due to limited access to tissue biopsies. Hence, determination of variability in hepatic drug metabolism and disposition using liquid biopsy (blood samples) is an attractive proposition during drug development and in clinical practice. This study used a multi-"omic" strategy to establish a liquid biopsy technology intended to assess hepatic capacity for metabolism and disposition in individual patients. Plasma exosomal analysis (n = 29) revealed expression of 533 pharmacologically relevant genes at the RNA level, with 147 genes showing evidence of expression at the protein level in matching liver tissue. Correction of exosomal RNA expression using a novel shedding factor improved correlation against liver protein expression for 97 liver-enriched genes. Strong correlation was demonstrated for 12 key drug-metabolizing enzymes and 4 drug transporters. The developed test allowed reliable patient stratification, and in silico trials demonstrated utility in adjusting drug dose to achieve similar drug exposure between patients with variable hepatic elimination. Accordingly, this approach can be applied in characterization of volunteers prior to enrollment in clinical trials and for patient stratification in clinical practice to achieve more precise individual dosing.

3D projection electrophoresis for single-cell immunoblotting

Immunoassays and mass spectrometry are powerful single-cell protein analysis tools; however, interfacing and throughput bottlenecks remain. Here, we introduce three-dimensional single-cell immunoblots to detect both cytosolic and nuclear proteins. The 3D microfluidic device is a photoactive polyacrylamide gel with a microwell array-patterned face (xy) for cell isolation and lysis. Single-cell lysate in each microwell is "electrophoretically projected" into the 3rd dimension (z-axis), separated by size, and photo-captured in the gel for immunoprobing and confocal/light-sheet imaging. Design and analysis are informed by the physics of 3D diffusion. Electrophoresis throughput is > 2.5 cells/s (70× faster than published serial sampling), with 25 immunoblots/mm2 device area (>10× increase over previous immunoblots). The 3D microdevice design synchronizes analyses of hundreds of cells, compared to status quo serial analyses that impart hours-long delay between the first and last cells. Here, we introduce projection electrophoresis to augment the heavily genomic and transcriptomic single-cell atlases with protein-level profiling.

5' Untranslated Region Elements Show High Abundance and Great Variability in Homologous ABCA Subfamily Genes

The 12 members of the ABCA subfamily in humans are known for their ability to transport cholesterol and its derivatives, vitamins, and xenobiotics across biomembranes. Several ABCA genes are causatively linked to inborn diseases, and the role in cancer progression and metastasis is studied intensively. The regulation of translation initiation is implicated as the major mechanism in the processes of post-transcriptional modifications determining final protein levels. In the current bioinformatics study, we mapped the features of the 5' untranslated regions (5'UTR) known to have the potential to regulate translation, such as the length of 5'UTRs, upstream ATG codons, upstream open-reading frames, introns, RNA G-quadruplex-forming sequences, stem loops, and Kozak consensus motifs, in the DNA sequences of all members of the subfamily. Subsequently, the conservation of the features, correlations among them, ribosome profiling data as well as protein levels in normal human tissues were examined. The 5'UTRs of ABCA genes contain above-average numbers of upstream ATGs, open-reading frames and introns, as well as conserved ones, and these elements probably play important biological roles in this subfamily, unlike RG4s. Although we found significant correlations among the features, we did not find any correlation between the numbers of 5'UTR features and protein tissue distribution and expression scores. We showed the existence of single nucleotide variants in relation to the 5'UTR features experimentally in a cohort of 105 breast cancer patients. 5'UTR features presumably prepare a complex playground, in which the other elements such as RNA binding proteins and non-coding RNAs play the major role in the fine-tuning of protein expression.

In-Depth Mass Spectrometry-Based Single-Cell and Nanoscale Proteomics

Leukemic stem cells are highly dynamic and heterogeneous. Analysis of leukemic stem cells at the single-cell level should provide a wealth of insights that would not be possible using bulk measurements. Mass spectrometry (MS)-based proteomic workflows can quantify hundreds or thousands of proteins from a biological sample and has proven invaluable for biomedical research, but samples comprising large numbers of cells are typically required due to limited sensitivity. Recent developments in sample processing, chromatographic separations, and MS instrumentation are now extending in-depth proteome profiling to single mammalian cells. Here, we describe specific techniques that increase the sensitivity of single-cell proteomics by orders of magnitude, enabling the promise of single-cell proteomics to become a reality. We anticipate such techniques can significantly advance the understanding of leukemic stem cells.

The changing chromatome as a driver of disease: A panoramic view from different methodologies

Chromatin-bound proteins underlie several fundamental cellular functions, such as control of gene expression and the faithful transmission of genetic and epigenetic information. Components of the chromatin proteome (the "chromatome") are essential in human life, and mutations in chromatin-bound proteins are frequently drivers of human diseases, such as cancer. Proteomic characterization of chromatin and de novo identification of chromatin interactors could, thus, reveal important and perhaps unexpected players implicated in human physiology and disease. Recently, intensive research efforts have focused on developing strategies to characterize the chromatome composition. In this review, we provide an overview of the dynamic composition of the chromatome, highlight the importance of its alterations as a driving force in human disease (and particularly in cancer), and discuss the different approaches to systematically characterize the chromatin-bound proteome in a global manner.

Integration and Comparison of Transcriptomic and Proteomic Data for Meningioma

Meningioma are the most frequent primary intracranial tumour. Management of aggressive meningioma is complex, and development of effective biomarkers or pharmacological interventions is hampered by an incomplete knowledge of molecular landscape. Here, we present an integrated analysis of two complementary omics studies to investigate alterations in the "transcriptome-proteome" profile of high-grade (III) compared to low-grade (I) meningiomas. We identified 3598 common transcripts/proteins and revealed concordant up- and downregulation in grade III vs. grade I meningiomas. Concordantly upregulated genes included FABP7, a fatty acid binding protein and the monoamine oxidase MAOB, the latter of which we validated at the protein level and established an association with Food and Drug Administration (FDA)-approved drugs. Notably, we derived a plasma signature of 21 discordantly expressed genes showing positive changes in protein but negative in transcript levels of high-grade meningiomas, including the validated genes CST3, LAMP2, PACS1 and HTRA1, suggesting the acquisition of these proteins by tumour from plasma. Aggressive meningiomas were enriched in processes such as oxidative phosphorylation and RNA metabolism, whilst concordantly downregulated genes were related to reduced cellular adhesion. Overall, our study provides the first transcriptome-proteome characterisation of meningioma, identifying several novel and previously described transcripts/proteins with potential grade III biomarker and therapeutic significance.