Gene-specific correlation of RNA and protein levels in human cells and tissues

Estrogen receptor beta expression and role in cancers

Estrogen drives the growth of some cancers, such as breast cancer, via estrogen receptor alpha (ERα). Estrogen also activates ERβ, but whether ERβ is expressed and has a role in different cancers is debated. The use of nonspecific antibodies has contributed to the confusion, and this review delves into ERβ's controversial role in cancer and focuses on tumor expression that can be supported by non-antibody-dependent assays. We discuss its expression at the transcript level and focus on its potential role in lymphoma, granulosa cell tumors, testicular, and adrenal cancers, emphasizing recent findings and the complexities that necessitate further research.

Age-Specific ADME Gene Expression in Infant Intestinal Enteroids

In childhood, developmental changes and environmental interactions highly affect orally dosed drug disposition across the age range. To optimize dosing regimens and ensure safe use of drugs in pediatric patients, understanding this age-dependent biology is necessary. In this proof-of-concept study, we aimed to culture age-specific enteroids from infant tissue which represent its original donor material, specifically for drug transport and metabolism. Enteroid lines from fresh infant tissues (n = 8, age range: 0.3-45 postnatal weeks) and adult tissues (n = 3) were established and expanded to 3D self-organizing enteroids. The gene expression of drug transporters P-gp (ABCB1), BCRP (ABCG2), MRP2 (ABCC2), and PEPT1 (SLC15A1) and drug metabolizing enzymes CYP3A4, CYP2C18, and UGT1A1 was determined with RT-qPCR in fresh tissue and its derivative differentiated enteroids. Expression levels of P-gp, BCRP, MRP2, and CYP3A4 were similar between tissues and enteroids. PEPT1 and CYP2C18 expression was lower in enteroids compared to that in the tissue. The expression of UGT1A1 in the tissue was lower than that in enteroids. The gene expression did not change with the enteroid passage number for all genes studied. Similar maturational patterns in tissues and enteroids were visually observed for P-gp, PEPT1, MRP2, CYP3A4, CYP2C18, and VIL1. In this explorative study, interpatient variability was high, likely due to the diverse patient characteristics of the sampled population (e.g., disease, age, and treatment). To summarize, maturational patterns of clinically relevant ADME genes in tissue were maintained in enteroids. These findings are an important step toward the potential use of pediatric enteroids in pediatric drug development, which in the future may lead to improved pediatric safety predictions during drug development. We reason that such an approach can contribute to a potential age-specific platform to study and predict drug exposure and intestinal safety in pediatrics.

Comprehensive analysis of the endothelin system in the kidneys of mice, rats, and humans

The intrarenal endothelin (ET) system is an established moderator of kidney physiology and mechanistic contributor to the pathophysiology and progression of chronic kidney disease in humans and rodents. The aim of the present study was to characterize ET system by combining single cell RNA sequencing (scRNA-seq) data with immunolocalization in human and rodent kidneys of both sexes. Using publicly available scRNA-seq data, we assessed sex and kidney disease status (human), age and sex (rats), and diurnal expression (mice) on the kidney ET system expression. In normal human biopsies of both sexes and in rodent kidney samples, the endothelin-converting enzyme-1 (ECE1) and ET-1 were prominent in the glomeruli and endothelium. These data agreed with the scRNA-seq data from these three species, with ECE1/Ece1 mRNA enriched in the endothelium. However, the EDN1/Edn1 gene (encodes ET-1) was rarely detected, even though it was immunolocalized within the kidneys, and plasma and urinary ET-1 excretion are easily measured. Within each species, there were some sex-specific differences. For example, in kidney biopsies from living donors, men had a greater glomerular endothelial cell endothelin receptor B (Ednrb) compared with women. In mice, females had greater kidney endothelial cell Ednrb than male mice. As commercially available antibodies did not work in all species, and RNA expression did not always correlate with protein levels, multiple approaches should be considered to maintain required rigor and reproducibility of the pre- and clinical studies evaluating the intrarenal ET system.

Improving cell type identification with Gaussian noise-augmented single-cell RNA-seq contrastive learning

Cell type identification is an important task for single-cell RNA-sequencing (scRNA-seq) data analysis. Many prediction methods have recently been proposed, but the predictive accuracy of difficult cell type identification tasks is still low. In this work, we proposed a novel Gaussian noise augmentation-based scRNA-seq contrastive learning method (GsRCL) to learn a type of discriminative feature representations for cell type identification tasks. A large-scale computational evaluation suggests that GsRCL successfully outperformed other state-of-the-art predictive methods on difficult cell type identification tasks, while the conventional random genes masking augmentation-based contrastive learning method also improved the accuracy of easy cell type identification tasks in general.

IS-PRM-Based Peptide Targeting Informed by Long-Read Sequencing for Alternative Proteome Detection

Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of predefined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (lrRNA-seq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNaseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This lrRNA-seq-informed Tomahto targeted approach is a new modality for generating protein-level evidence of alternative isoforms─a critical first step in designing functional studies and eventually clinical assays.

Multilevel gene expression changes in lineages containing adaptive copy number variants

Copy-number variants (CNVs) are an important class of recurrent variants that mediate adaptive evolution. While CNVs can increase the relative fitness of the organism, they can also incur a cost. We previously evolved populations of Saccharomyces cerevisiae over hundreds of generations in glutamine-limited (Gln-) chemostats and observed the recurrent evolution of CNVs at the GAP1 locus. To understand the role that expression plays in adaptation, both in relation to the adaptation of the organism to the selective condition, and as a consequence of the CNV, we measured the transcriptome, translatome, and proteome of 4 strains of evolved yeast, each with a unique CNV, and their ancestor in Gln- conditions. We find CNV-amplified genes correlate with higher RNA abundance; however, this effect is reduced at the level of the proteome, consistent with post-transcriptional dosage compensation. By normalizing each level of expression by the abundance of the preceding step we were able to identify widespread divergence in the efficiency of each step in the gene in the efficiency of each step in gene expression. Genes with significantly different translational efficiency were enriched for potential regulatory mechanisms including either upstream open reading frames, RNA binding sites for SSD1, or both. Genes with lower protein expression efficiency were enriched for genes encoding proteins in protein complexes. Taken together, our study reveals widespread changes in gene expression at multiple regulatory levels in lineages containing adaptive CNVs highlighting the diverse ways in which adaptive evolution shapes gene expression.

Simulated complexes formed from a set of postsynaptic proteins suggest a localised effect of a hypomorphic Shank mutation

BACKGROUND

The postsynaptic density is an elaborate protein network beneath the postsynaptic membrane involved in the molecular processes underlying learning and memory. The postsynaptic density is built up from the same major proteins but its exact composition and organization differs between synapses. Mutations perturbing protein: protein interactions generally occurring in this network might lead to effects specific for cell types or processes, the understanding of which can be especially challenging.

RESULTS

In this work we use systems biology-based modeling of protein complex distributions in a simplified set of major postsynaptic proteins to investigate the effect of a hypomorphic Shank mutation perturbing a single well-defined interaction. We use data sets with widely variable abundances of the constituent proteins. Our results suggest that the effect of the mutation is heavily dependent on the overall availability of all the protein components of the whole network and no trivial correspondence between the expression level of the directly affected proteins and overall complex distribution can be observed.

CONCLUSIONS

Our results stress the importance of context-dependent interpretation of mutations. Even the weakening of a generally occurring protein: protein interaction might have well-defined effects, and these can not easily be predicted based only on the abundance of the proteins directly affected. Our results provide insight on how cell-specific effects can be exerted by a mutation perturbing a generally occurring interaction even when the wider interaction network is largely similar.

Multiplexed imaging to reveal tissue dendritic cell spatial localisation and function

Dendritic cells (DCs) play a pivotal role in immune surveillance, acting as sentinels that coordinate immune responses within tissues. Although differences in the identity and functional states of DC subpopulations have been identified through multiparametric flow cytometry and single-cell RNA sequencing, these methods do not provide information about the spatial context in which the cells are located. This knowledge is crucial for understanding tissue organisation and cellular cross-talk. Recent developments in multiplex imaging techniques can now offer insights into this complex spatial and functional landscape. This review provides a concise overview of these imaging methodologies, emphasising their application in identifying DCs to delineate their tissue-specific functions and aiding newcomers in navigating this field.

Exploring the role of vitamin D-VDR pathway in pemphigus foliaceous: a novel perspective on disease pathogenesis

Several auto-immune diseases have been linked to vitamin D deficiency as a contributing environmental factor. Its pleiotropic effects on the immune system, especially its essential role in maintaining immune tolerance, make the vitamin D pathway of great interest. In this study, we focused on Pemphigus foliaceous (PF) in Tunisian population. we aimed to quantify the Serum 25[OH]D levels using chemiluminescence assay and to analyze the differential expression of the VDR, CYP27B1 and CYP24A1 genes in the circulating blood cells and lesional skin tissue of PF patients using Q-PCR. A genetic explanation was then sought to explore any direct relationship between tag polymorphisms and the inherited features of PF. Results confirmed a vitamin D hypovitaminosis in Tunisian PF patients. Interestingly, a differential gene expression correlated to the disease stratification was noted. Indeed, at the systemic level, an upregulation of VDR and CYP27B1 genes was observed in healthy controls compared to PF patients. Notably, in lesional skin tissue, the clinical and serological remission phase was correlated with high transcriptional levels of the VDR gene and conversely a drop in expression of the CYP24A1 gene. Genetic analysis indicated the involvement of the most appealing polymorphisms, rs2228570 and poly (A) microsatellite, in PF etiopathogenesis. Indeed, CAC13 haplotype was associated with a higher risk of PF development. Our findings suggest that alterations in the vitamin D-VDR pathway may influence PF physiopathology, making this pathway a potential target for pharmacological modulation, especially for cortico-resistant PF patients.

scDM: A deep generative method for cell surface protein prediction with diffusion model

The executors of organismal functions are proteins, and the transition from RNA to protein is subject to post-transcriptional regulation; therefore, considering both RNA and surface protein expression simultaneously can provide additional evidence of biological processes. Cellular indexing of transcriptomes and epitopes by sequencing (CITE-Seq) technology can measure both RNA and protein expression in single cells, but these experiments are expensive and time-consuming. Due to the lack of computational tools for predicting surface proteins, we used datasets obtained with CITE-seq technology to design a deep generative prediction method based on diffusion models and to find biological discoveries through the prediction results. In our method, the scDM, which predicts protein expression values from RNA expression values of individual cells, uses a novel way of encoding the data into a model and generates predicted samples by introducing Gaussian noise to gradually remove the noise to learn the data distribution during the modelling process. Comprehensive evaluation across different datasets demonstrated that our predictions yielded satisfactory results and further demonstrated the effectiveness of incorporating information from single-cell multiomics data into diffusion models for biological studies. We also found that new directions for discovering therapeutic drug targets could be provided by jointly analysing the predictive value of surface protein expression and cancer cell drug scores.

IsoBayes: a Bayesian approach for single-isoform proteomics inference

Studying protein isoforms is an essential step in biomedical research; at present, the main approach for analyzing proteins is via bottom-up mass spectrometry proteomics, which return peptide identifications, that are indirectly used to infer the presence of protein isoforms. However, the detection and quantification processes are noisy; in particular, peptides may be erroneously detected, and most peptides, known as shared peptides, are associated to multiple protein isoforms. As a consequence, studying individual protein isoforms is challenging, and inferred protein results are often abstracted to the gene-level or to groups of protein isoforms. Here, we introduce IsoBayes, a novel statistical method to perform inference at the isoform level. Our method enhances the information available, by integrating mass spectrometry proteomics and transcriptomics data in a Bayesian probabilistic framework. To account for the uncertainty in the measurement process, we propose a two-layer latent variable approach: first, we sample if a peptide has been correctly detected (or, alternatively filter peptides); second, we allocate the abundance of such selected peptides across the protein(s) they are compatible with. This enables us, starting from peptide-level data, to recover protein-level data; in particular, we: i) infer the presence/absence of each protein isoform (via a posterior probability), ii) estimate its abundance (and credible interval), and iii) target isoforms where transcript and protein relative abundances significantly differ. We benchmarked our approach in simulations, and in two multi-protease real datasets: our method displays good sensitivity and specificity when detecting protein isoforms, its estimated abundances highly correlate with the ground truth, and can detect changes between protein and transcript relative abundances. IsoBayes is freely distributed as a Bioconductor R package, and is accompanied by an example usage vignette.

Aspartate-β-hydroxylase and hypoxia marker expression in head and neck carcinomas: implications for HPV-associated tumors

BACKGROUND

A proportion of head and neck carcinomas (HNSCCs) are induced by high-risk human papillomaviruses (HPVs) and are associated with better patient outcomes compared to patients with HNSCCs related to tobacco and alcohol abuse. In the microenvironment of solid tumors, including HNSCCs, oxygen levels are often reduced, and a hypoxic state is induced. This can lead to a poor treatment response and a worse patient prognosis. One of the hypoxia-responsive genes is aspartate-β-hydroxylase (ASPH), whose activity promotes the growth, invasiveness, and metastasis of many types of solid tumors.

METHODS

In our study, HNSCC samples were analyzed for the expression of ASPH and selected endogenous hypoxia markers by real-time PCR and/or multiplex fluorescence immunohistochemistry.

RESULTS

Except for the EPAS1 gene, which had higher mRNA expression in the HPV-negative group of HNSCC (p < 0.05), we found no other differences in the expression of the tested genes that were related to HPV status. On the contrary, a statistically significantly higher number of cells producing ASPH (p < 0.0001), HIF1A (p < 0.0001), GLUT1 (p < 0.0001), and MMP13 (p < 0.05) proteins were detected in the HPV-positive tumor group than in the HPV-negative sample group. All the evaluated markers, except for MMP9/13, were more abundant in the tumor parenchyma than in the tumor stroma. The Cox proportional hazard models showed that increased numbers of cells with GLUT1 and HIF1A protein expression were positive prognostic markers for overall and disease-specific survival in patients independent of HPV tumor status.

CONCLUSION

The study examined HNSCC samples and found that elevated ASPH and hypoxia marker proteins, typically associated with poor prognosis, may actually indicate active HPV infection, the strongest prognostic factor in HNSCC patients. In cases where HPV status is uncertain, increased expression of HIF1A and GLUT1 can serve as positive prognostic factors.

Spatial-temporal comparison of Eph/Ephrin gene expression in ocular lenses from aging and knockout mice

Cataracts, defined as any opacity in the transparent ocular lens, remain the leading cause of blindness and visual impairment in the world; however, the etiology of this pathology is not fully understood. Studies in mice and humans have found that the EphA2 receptor and the ephrin-A5 ligand play important roles in maintaining lens homeostasis and transparency. However, due to the diversity of the family of Eph receptors and ephrin ligands and their promiscuous binding, identifying functional interacting partners remains a challenge. Previously, 12 of the 14 Ephs and 8 of 8 ephrins in mice were characterized to be expressed in the mouse lens. To further narrow down possible genes of interest in life-long lens homeostasis, we collected and separated the lens epithelium from the fiber cell mass and isolated RNA from each compartment in samples from young adult and middle-aged mice that were either wild-type, EphA2-/- (knockout), or ephrin-A5 -/- . Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was implemented to compare transcript levels of 33 Eph and ephrin gene variants in each tissue compartment. Our results show that, of the Eph and ephrin variants screened, 5 of 33 showed age-related changes, and 2 of 33 showed genotype-related changes in lens epithelium. In the isolated fibers, more dynamic gene expression changes were observed, in which 12 of 33 variants showed age-related changes, and 6 of 33 showed genotype-related changes. These data allow for a more informed decision in determining mechanistic leads in Eph-ephrin-mediated signaling in the lens.

The potential role of nitric oxide in the anticonvulsant effects of betulin in pentylenetetrazole (PTZ)-induced seizures in mice

Epilepsy poses a significant challenge, especially for drug-resistant cases, necessitating novel treatment avenues. This study explores the potential interplay between nitric oxide (NO) and the anticonvulsant effects of betulin, a triterpene with promising neuroprotective properties. While betulin exhibits anticonvulsant effects, the specific involvement of NO remains inadequately understood, constituting a pivotal gap in current knowledge. One hundred NMRI mice were randomly assigned to diverse treatment groups, with seizures induced by pentylenetetrazol (PTZ). Parameters such as seizure threshold, nitrite levels, total antioxidant capacity (TAC), malondialdehyde (MDA) levels, and iNOS/nNOS gene expressions were assessed. Betulin significantly increased seizure thresholds and mitigated PTZ-induced NO levels. These findings suggest a potential modulation of NO-related pathways, emphasizing betulin's anti-inflammatory and antioxidant attributes. The study sheds light on betulin's multifaceted impact on oxidative stress, NO regulation, and iNOS/nNOS gene expressions. The ability of betulin to suppress iNOS/nNOS gene expressions, leading to reduce NO production, underscores its potential as an anticonvulsant.

Multi-Omic Analysis of Esophageal Adenocarcinoma Uncovers Candidate Therapeutic Targets and Cancer-Selective Posttranscriptional Regulation

Efforts to address the poor prognosis associated with esophageal adenocarcinoma (EAC) have been hampered by a lack of biomarkers to identify early disease and therapeutic targets. Despite extensive efforts to understand the somatic mutations associated with EAC over the past decade, a gap remains in understanding how the atlas of genomic aberrations in this cancer impacts the proteome and which somatic variants are of importance for the disease phenotype. We performed a quantitative proteomic analysis of 23 EACs and matched adjacent normal esophageal and gastric tissues. We explored the correlation of transcript and protein abundance using tissue-matched RNA-seq and proteomic data from seven patients and further integrated these data with a cohort of EAC RNA-seq data (n = 264 patients), EAC whole-genome sequencing (n = 454 patients), and external published datasets. We quantified protein expression from 5879 genes in EAC and patient-matched normal tissues. Several biomarker candidates with EAC-selective expression were identified, including the transmembrane protein GPA33. We further verified the EAC-enriched expression of GPA33 in an external cohort of 115 patients and confirm this as an attractive diagnostic and therapeutic target. To further extend the insights gained from our proteomic data, an integrated analysis of protein and RNA expression in EAC and normal tissues revealed several genes with poorly correlated protein and RNA abundance, suggesting posttranscriptional regulation of protein expression. These outlier genes, including SLC25A30, TAOK2, and AGMAT, only rarely demonstrated somatic mutation, suggesting post-transcriptional drivers for this EAC-specific phenotype. AGMAT was demonstrated to be overexpressed at the protein level in EAC compared to adjacent normal tissues with an EAC-selective, post-transcriptional mechanism of regulation of protein abundance proposed. Integrated analysis of proteome, transcriptome, and genome in EAC has revealed several genes with tumor-selective, posttranscriptional regulation of protein expression, which may be an exploitable vulnerability.

Environmental enrichment and the combined interventions of EE and metformin enhance hippocampal neuron survival and hippocampal-dependent memory in type 2 diabetic rats under stress through the BDNF-TrkB signaling pathways

BACKGROUND

Type 2 diabetes (T2D) with depression causes severe cognitive impairments. The devastating conditions will further compromise the overall quality of life. The overconsumption of high-fat and high-sucrose (HFS) diet is one of the modifiable risk factors for T2D, depression, and cognitive impairments. Thus, it is essential to identify effective therapeutic strategies to overcome the cognitive impairments in T2D with depression. We proposed environmental enrichment (EE) which encompasses social, cognitive, and physical components as the alternative treatment for such impairments. We also investigated the potential neuroprotective properties of the antidiabetic drug metformin. This study aimed to investigate the effects of EE and metformin interventions on hippocampal neuronal death, and hippocampal-dependent memory impairment in T2D rats under stress.

METHODS

Thirty-two male rats (200-250 g) were divided into four groups: C group (standard diet + conventional cage), DS group [HFS-induced T2D + restraint stress (RS)], DSE group [HFS-induced T2D + RS + EE] and DSEM group [HFS + RS + EE + metformin]. Serum corticosterone (CORT) was measured to evaluate stress levels. The serum Free Oxygen Radicals Testing (FORT) and Free Oxygen Radicals Defence Test (FORD) were measured to evaluate the systemic oxidative status (OS). Serum brain-derived neurotrophic factor (BDNF) and T-maze tasks were performed to evaluate cognitive functions. Rats were humanely sacrificed to collect brains for histological, morphometric, and hippocampal gene expression studies.

RESULTS

The CORT and the serum FORT levels in the DSE and DSEM groups were lower than in the DS group. Meanwhile, the serum BDNF, T-maze scores, histological, and morphometric analysis were improved in the DSE and DSEM groups than in the DS group. These findings supported that EE and the combined interventions of EE and metformin had neuroprotective properties. The hippocampal gene expression analysis revealed that the DSE and DSEM groups showed improved regulation of BDNF-TrkB signalling pathways, including the BDNF/TrkB binding, PI3K - Akt pathway, Ras-MAPK pathway, PLCγ-Ca2+ pathway, and CREB transcription.

CONCLUSION

EE and the combined interventions of EE and metformin improved hippocampal neuron survival and hippocampal-dependent memory in T2D rats under stress by enhancing gene expression regulation of neurogenesis and synaptic plasticity.

Unraveling hallmark suitability for staging pre- and post-implantation stem cell models

The advent of novel 2D and 3D models for human development, including trophoblast stem cells and blastoids, has expanded opportunities for investigating early developmental events, gradually illuminating the enigmatic realm of human development. While these innovations have ushered in new prospects, it has become essential to establish well-defined benchmarks for the cell sources of these models. We aimed to propose a comprehensive characterization of pluripotent and trophoblastic stem cell models by employing a combination of transcriptomic, proteomic, epigenetic, and metabolic approaches. Our findings reveal that extended pluripotent stem cells share many characteristics with primed pluripotent stem cells, with the exception of metabolic activity. Furthermore, our research demonstrates that DNA hypomethylation and high metabolic activity define trophoblast stem cells. These results underscore the necessity of considering multiple hallmarks of pluripotency rather than relying on a single criterion. Multiplying hallmarks alleviate stage-matching bias.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein coexpression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Deep learning the cis-regulatory code for gene expression in selected model plants

Elucidating the relationship between non-coding regulatory element sequences and gene expression is crucial for understanding gene regulation and genetic variation. We explored this link with the training of interpretable deep learning models predicting gene expression profiles from gene flanking regions of the plant species Arabidopsis thaliana, Solanum lycopersicum, Sorghum bicolor, and Zea mays. With over 80% accuracy, our models enabled predictive feature selection, highlighting e.g. the significant role of UTR regions in determining gene expression levels. The models demonstrated remarkable cross-species performance, effectively identifying both conserved and species-specific regulatory sequence features and their predictive power for gene expression. We illustrated the application of our approach by revealing causal links between genetic variation and gene expression changes across fourteen tomato genomes. Lastly, our models efficiently predicted genotype-specific expression of key functional gene groups, exemplified by underscoring known phenotypic and metabolic differences between Solanum lycopersicum and its wild, drought-resistant relative, Solanum pennellii.

Age-Invariant Genes: Multi-Tissue Identification and Characterization of Murine Reference Genes

Studies of the aging transcriptome focus on genes that change with age. But what can we learn from age-invariant genes-those that remain unchanged throughout the aging process? These genes also have a practical application: they serve as reference genes (often called housekeeping genes) in expression studies. Reference genes have mostly been identified and validated in young organisms, and no systematic investigation has been done across the lifespan. Here, we build upon a common pipeline for identifying reference genes in RNA-seq datasets to identify age-invariant genes across seventeen C57BL/6 mouse tissues (brain, lung, bone marrow, muscle, white blood cells, heart, small intestine, kidney, liver, pancreas, skin, brown, gonadal, marrow, and subcutaneous adipose tissue) spanning 1 to 21+ months of age. We identify 9 pan-tissue age-invariant genes and many tissue-specific age-invariant genes. These genes are stable across the lifespan and are validated in independent bulk RNA-seq datasets and RT-qPCR. We find age-invariant genes have shorter transcripts on average and are enriched for CpG islands. Interestingly, pathway enrichment analysis for age-invariant genes identifies an overrepresentation of molecular functions associated with some, but not all, hallmarks of aging. Thus, though hallmarks of aging typically involve changes in cell maintenance mechanisms, select genes associated with these hallmarks resist fluctuations in expression with age. Finally, our analysis concludes no classical reference gene is appropriate for aging studies in all tissues. Instead, we provide tissue-specific and pan-tissue genes for assays utilizing reference gene normalization (i.e., RT-qPCR) that can be applied to animals across the lifespan.

Transcriptomic and Proteomic Spatial Profiling of Pediatric and Adult Diffuse Midline Glioma H3 K27-Altered, Reveals Region Specific Differences and Limited Overlap between mRNA and Protein

Diffuse midline glioma, H3 K27 -altered (DMG-Alt) are highly aggressive malignancies of the central nervous system (CNS) that primarily affect the pediatric population. Large scale spatial transcriptomic studies have implicated that tumor microenvironmental landscape plays an important role in determining the phenotypic differences in tumor presentation and clinical course, however, data connecting overall transcriptomic changes to the protein level is lacking. The NanoString GeoMx™ Digital Spatial Profiler platform was used to determine the spatial transcriptomic and proteomic landscape in a cohort of both pediatric and adult H3 K27 -altered DMG biopsy samples. Three fluorescently labeled antibodies targeting immune cells (CD45), epithelial cells (PanCK), tumor cells ( H3 K27M ) and a nucleic acid stain (SYTO-13) were used to establish regions of interest (ROI) for genomic and proteomic analysis. We found genetic alterations within the tumor which can be delineated across patient age and spatial location. We show that the H3 K27M mutation itself has a profound impact on tumor cells transcriptomics and interestingly we found limited fidelity between overall transcriptome and proteome. Our data also validate the previously described OPC like precursor signature at the proteomic level and reveal a special shift in the signature based on the local TME composition.

Proteomic Analyses Reveal the Role of Alpha-2-Macroglobulin in Canine Osteosarcoma Cell Migration

Canine osteosarcoma (OSA) is an aggressive bone neoplasia with high metastatic potential. Metastasis is the main cause of death associated with OSA, and there is no current treatment available for metastatic disease. Proteomic analyses, including matrix-assisted laser desorption/ionisation-time of flight mass spectrometry (MALDI TOF/TOF MS), are widely used to select molecular targets and identify proteins that may play a key role in primary tumours and at various steps of the metastatic cascade. The main aim of this study was to identify proteins differently expressed in canine OSA cell lines with different malignancy phenotypes (OSCA-8 and OSCA-32) compared to canine osteoblasts (CnOb). The intermediate aim of the study was to compare canine OSA cell migration capacity and assess its correlation with the malignancy phenotypes of each cell line. Using MALDI-TOF/TOF MS analyses, we identified eight proteins that were significantly differentially expressed (p ≤ 0.05) in canine OSA cell lines compared to CnOb: cilia- and flagella-associated protein 298 (CFAP298), general transcription factor II-I (GTF2I), mirror-image polydactyly gene 1 protein (MIPOL1), alpha-2 macroglobulin (A2M), phosphoglycerate mutase 1 (PGAM1), ubiquitin (UB2L6), ectodysplasin-A receptor-associated adapter protein (EDARADD), and leucine-rich-repeat-containing protein 72 (LRRC72). Using the Simple Western technique, we confirmed high A2M expression in CnOb compared to OSCA-8 and OSCA-32 cell lines (with intermediate and low A2M expression, respectively). Then, we confirmed the role of A2M in cancer cell migration by demonstrating significantly inhibited OSA cell migration by treatment with A2M (both at 10 and 30 mM concentrations after 12 and 24 h) in a wound-healing assay. This study may be the first report indicating A2M's role in OSA cell metastasis; however, further in vitro and in vivo studies are needed to confirm its possible role as an anti-metastatic agent in this malignancy.

A Pilot Urinary Proteome Study Reveals Widespread Influences of Circadian Rhythm Disruption by Sleep Deprivation

It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.

IS-PRM-based peptide targeting informed by long-read sequencing for alternative proteome detection

Alternative splicing is a major contributor of transcriptomic complexity, but the extent to which transcript isoforms are translated into stable, functional protein isoforms is unclear. Furthermore, detection of relatively scarce isoform-specific peptides is challenging, with many protein isoforms remaining uncharted due to technical limitations. Recently, a family of advanced targeted MS strategies, termed internal standard parallel reaction monitoring (IS-PRM), have demonstrated multiplexed, sensitive detection of pre-defined peptides of interest. Such approaches have not yet been used to confirm existence of novel peptides. Here, we present a targeted proteogenomic approach that leverages sample-matched long-read RNA sequencing (LR RNAseq) data to predict potential protein isoforms with prior transcript evidence. Predicted tryptic isoform-specific peptides, which are specific to individual gene product isoforms, serve as "triggers" and "targets" in the IS-PRM method, Tomahto. Using the model human stem cell line WTC11, LR RNAseq data were generated and used to inform the generation of synthetic standards for 192 isoform-specific peptides (114 isoforms from 55 genes). These synthetic "trigger" peptides were labeled with super heavy tandem mass tags (TMT) and spiked into TMT-labeled WTC11 tryptic digest, predicted to contain corresponding endogenous "target" peptides. Compared to DDA mode, Tomahto increased detectability of isoforms by 3.6-fold, resulting in the identification of five previously unannotated isoforms. Our method detected protein isoform expression for 43 out of 55 genes corresponding to 54 resolved isoforms. This LR RNA seq-informed Tomahto targeted approach, called LRP-IS-PRM, is a new modality for generating protein-level evidence of alternative isoforms - a critical first step in designing functional studies and eventually clinical assays.

Spatiotemporal analysis of mRNA-protein relationships enhances transcriptome-based developmental inference

Elucidating the complex relationships between mRNA and protein expression at high spatiotemporal resolution is critical for unraveling multilevel gene regulation and enhancing mRNA-based developmental analyses. In this study, we conduct a single-cell analysis of mRNA and protein expression of transcription factors throughout C. elegans embryogenesis. Initially, cellular co-presence of mRNA and protein is low, increasing to a medium-high level (73%) upon factoring in delayed protein synthesis and long-term protein persistence. These factors substantially affect mRNA-protein concordance, leading to potential inaccuracies in mRNA-reliant gene detection and specificity characterization. Building on the learned relationship, we infer protein presence from mRNA expression and demonstrate its utility in identifying tissue-specific genes and elucidating relationships between genes and cells. This approach facilitates identifying the role of sptf-1/SP7 in neuronal lineage development. Collectively, this study provides insights into gene expression dynamics during rapid embryogenesis and approaches for improving the efficacy of transcriptome-based developmental analyses.

Resource allocation in mammalian systems

Cells execute biological functions to support phenotypes such as growth, migration, and secretion. Complementarily, each function of a cell has resource costs that constrain phenotype. Resource allocation by a cell allows it to manage these costs and optimize their phenotypes. In fact, the management of resource constraints (e.g., nutrient availability, bioenergetic capacity, and macromolecular machinery production) shape activity and ultimately impact phenotype. In mammalian systems, quantification of resource allocation provides important insights into higher-order multicellular functions; it shapes intercellular interactions and relays environmental cues for tissues to coordinate individual cells to overcome resource constraints and achieve population-level behavior. Furthermore, these constraints, objectives, and phenotypes are context-dependent, with cells adapting their behavior according to their microenvironment, resulting in distinct steady-states. This review will highlight the biological insights gained from probing resource allocation in mammalian cells and tissues.

Multiplex protein imaging in tumour biology

Tissue imaging has become much more colourful in the past decade. Advances in both experimental and analytical methods now make it possible to image protein markers in tissue samples in high multiplex. The ability to routinely image 40-50 markers simultaneously, at single-cell or subcellular resolution, has opened up new vistas in the study of tumour biology. Cellular phenotypes, interaction, communication and spatial organization have become amenable to molecular-level analysis, and application to patient cohorts has identified clinically relevant cellular and tissue features in several cancer types. Here, we review the use of multiplex protein imaging methods to study tumour biology, discuss ongoing attempts to combine these approaches with other forms of spatial omics, and highlight challenges in the field.

Molecular Behavior of α-Synuclein Is Associated with Membrane Transport, Lipid Metabolism, and Ubiquitin-Proteasome Pathways in Lewy Body Disease

Lewy body diseases (LBDs) feature α-synuclein (α-syn)-containing Lewy bodies, with misfolded α-syn potentially propagating as seeds. Using a seeding amplification assay, we previously reported distinct α-syn seeding in LBD cases based on the area under seeding curves. This study revealed that LBD cases showing different α-syn seeding kinetics have distinct proteomics profiles, emphasizing disruptions in mitochondria and lipid metabolism in high-seeder cases. Though the mechanisms underlying LBD development are intricate, the factors influencing α-syn seeding activity remain elusive. To address this and complement our previous findings, we conducted targeted transcriptome analyses in the substantia nigra using the nanoString nCounter assay together with histopathological evaluations in high (n = 4) and low (n = 3) nigral α-syn seeders. Neuropathological findings (particularly the substantia nigra) were consistent between these groups and were characterized by neocortical LBD associated with Alzheimer's disease neuropathologic change. Among the 1811 genes assessed, we identified the top 20 upregulated and downregulated genes and pathways in α-syn high seeders compared with low seeders. Notably, alterations were observed in genes and pathways related to transmembrane transporters, lipid metabolism, and the ubiquitin-proteasome system in the high α-syn seeders. In conclusion, our findings suggest that the molecular behavior of α-syn is the driving force in the neurodegenerative process affecting the substantia nigra through these identified pathways. These insights highlight their potential as therapeutic targets for attenuating LBD progression.

uPAR (PLAUR) Marks Two Intra-Tumoral Subtypes of Glioblastoma: Insights from Single-Cell RNA Sequencing

Urokinase plasminogen activator receptor (uPAR) encoded by the PLAUR gene is known as a clinical marker for cell invasiveness in glioblastoma multiforme (GBM). It is additionally implicated in various processes, including angiogenesis and inflammation within the tumor microenvironment. However, there has not been a comprehensive study that depicts the overall functions and molecular cooperators of PLAUR with respect to intra-tumoral subtypes of GBM. Using single-cell RNA sequencing data from 37 GBM patients, we identified PLAUR as a marker gene for two distinct subtypes in GBM. One subtype is featured by inflammatory activities and the other subtype is marked by ECM remodeling processes. Using the whole-transcriptome data from single cells, we are able to uncover the molecular cooperators of PLAUR for both subtypes without presuming biological pathways. Two protein networks comprise the molecular context of PLAUR, with each of the two subtypes characterized by a different dominant network. We concluded that targeting PLAUR directly influences the mechanisms represented by these two protein networks, regardless of the subtype of the targeted cell.

Translation regulation in response to stress

Cell stresses occur in a wide variety of settings: in disease, during industrial processes, and as part of normal day-to-day rhythms. Adaptation to these stresses requires cells to alter their proteome. Cells modify the proteins they synthesize to aid proteome adaptation. Changes in both mRNA transcription and translation contribute to altered protein synthesis. Here, we discuss the changes in translational mechanisms that occur following the onset of stress, and the impact these have on stress adaptation.

Early insights into the role of Exoc6B associated with spondyloepimetaphyseal dysplasia with joint laxity type 3 in primary ciliogenesis and chondrogenic differentiation in vitro

BACKGROUND

Spondyloepimetaphyseal dysplasia with joint laxity type 3 (SEMDJL3) is a rare skeletal dysplasia associated with EXOC6B, a component of the exocyst complex, involved in vesicle tethering and exocytosis at the plasma membrane. So far, EXOC6B and the pathomechanisms underlying SEMDJL3 remain obscure.

METHODS AND RESULTS

Exoc6b was detected largely at the perinuclear regions and the primary cilia base in ATDC5 prechondrocytes. Its shRNA lentiviral knockdown impeded primary ciliogenesis. In Exoc6b silenced prechondrocytes, Hedgehog signaling was attenuated, including when stimulated with Smoothened agonist. Exoc6b knockdown deregulated the mRNA and protein levels of Col2a1, a marker of chondrocyte proliferation at 7- and 14-days following differentiation. It led to the upregulation of Ihh another marker of proliferative chondrocytes. The levels of Col10a1, a marker of chondrocyte hypertrophy was enhanced at 14 days of differentiation. Congruently, Axin2, a canonical Wnt pathway modulator that inhibits chondrocyte hypertrophy was repressed. The expression of Mmp13 and Adamts4 that are terminal chondrocyte hypertrophy markers involved in extracellular matrix (ECM) remodelling were downregulated at 7 and 14 days of chondrogenesis. Bglap that encodes for the most abundant non-collagenous bone matrix constituent and promotes ECM calcification was suppressed at 14 days of chondrocyte differentiation. ECM mineralization was assessed by Alizarin Red staining. Gene expression and ciliogenesis were investigated by reverse transcription quantitative real-time PCR, immunoblotting, and immunocytochemistry.

CONCLUSIONS

These findings provide initial insights into the potential role of Exoc6b in primary ciliogenesis and chondrogenic differentiation, contributing towards a preliminary understanding of the molecular pathomechanisms underlying SEMDJL3.

FAVA: high-quality functional association networks inferred from scRNA-seq and proteomics data

MOTIVATION

Protein networks are commonly used for understanding how proteins interact. However, they are typically biased by data availability, favoring well-studied proteins with more interactions. To uncover functions of understudied proteins, we must use data that are not affected by this literature bias, such as single-cell RNA-seq and proteomics. Due to data sparseness and redundancy, functional association analysis becomes complex.

RESULTS

To address this, we have developed FAVA (Functional Associations using Variational Autoencoders), which compresses high-dimensional data into a low-dimensional space. FAVA infers networks from high-dimensional omics data with much higher accuracy than existing methods, across a diverse collection of real as well as simulated datasets. FAVA can process large datasets with over 0.5 million conditions and has predicted 4210 interactions between 1039 understudied proteins. Our findings showcase FAVA's capability to offer novel perspectives on protein interactions. FAVA functions within the scverse ecosystem, employing AnnData as its input source.

AVAILABILITY AND IMPLEMENTATION

Source code, documentation, and tutorials for FAVA are accessible on GitHub at https://github.com/mikelkou/fava. FAVA can also be installed and used via pip/PyPI as well as via the scverse ecosystem https://github.com/scverse/ecosystem-packages/tree/main/packages/favapy.

Dynamics of Whole Transcriptome Analysis (WTA) and Surface markers expression (AbSeq) in Immune Cells of COVID-19 Patients and Recovered captured through Single Cell Genomics

Introduction

Single-cell multi-omics studies, such as multidimensional transcriptomics (whole transcriptomic analysis, WTA), and surface marker analysis (antibody sequencing, AbSeq), have turned out to be valuable techniques that offer inaccessible possibilities for single-cell profiling of mRNA, lncRNA, and proteins.

Methods

We used this technique to understand the dynamics of mRNA and protein-level differences in healthy, COVID-19-infected and recovered individuals using peripheral blood mononuclear cells (PBMCs). Our results demonstrate that compared to mRNA expression, protein abundance is a better indicator of the disease state.

Results

We demonstrate that compared to mRNA expression, protein abundance is a better indicator of the disease state. We observed high levels of cell identity and regulatory markers, CD3E, CD4, CD8A, CD5, CD7, GITR, and KLRB1 in healthy individuals, whereas markers related to cell activation, CD38, CD28, CD69, CD62L, CD14, and CD16 elevated in the SARS-CoV-2 infected patients at both WTA and AbSeq levels. Curiously, in recovered individuals, there was a high expression of cytokine and chemokine receptors (CCR5, CCR7, CCR4, CXCR3, and PTGRD2). We also observed variations in the expression of markers within cell populations under different states.

Discussion

Furthermore, our study emphasizes the significance of employing an oligo-based method (AbSeq) that can help in diagnosis, prognosis, and protection from disease/s by identifying cell surface markers that are unique to different cell types or states. It also allows simultaneous study of a vast array of markers, surpassing the constraints of techniques like FACS to query the vast repertoire of proteins.

TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis

A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.

An Aptamer-Based Proteomic Analysis of Plasma from Cats (Felis catus) with Clinical Feline Infectious Peritonitis

Feline infectious peritonitis (FIP) is a systemic disease manifestation of feline coronavirus (FCoV) and is the most important cause of infectious disease-related deaths in domestic cats. FIP has a variable clinical manifestation but is most often characterized by widespread vasculitis with visceral involvement and/or neurological disease that is typically fatal in the absence of antiviral therapy. Using an aptamer-based proteomics assay, we analyzed the plasma protein profiles of cats who were naturally infected with FIP (n = 19) in comparison to the plasma protein profiles of cats who were clinically healthy and negative for FCoV (n = 17) and cats who were positive for the enteric form of FCoV (n = 9). We identified 442 proteins that were significantly differentiable; in total, 219 increased and 223 decreased in FIP plasma versus clinically healthy cat plasma. Pathway enrichment and associated analyses showed that differentiable proteins were related to immune system processes, including the innate immune response, cytokine signaling, and antigen presentation, as well as apoptosis and vascular integrity. The relevance of these findings is discussed in the context of previous studies. While these results have the potential to inform diagnostic, therapeutic, and preventative investigations, they represent only a first step, and will require further validation.

Detection of the Arabidopsis Proteome and Its Post-translational Modifications and the Nature of the Unobserved (Dark) Proteome in PeptideAtlas

This study describes a new release of the Arabidopsis thaliana PeptideAtlas proteomics resource (build 2023-10) providing protein sequence coverage, matched mass spectrometry (MS) spectra, selected post-translational modifications (PTMs), and metadata. 70 million MS/MS spectra were matched to the Araport11 annotation, identifying ∼0.6 million unique peptides and 18,267 proteins at the highest confidence level and 3396 lower confidence proteins, together representing 78.6% of the predicted proteome. Additional identified proteins not predicted in Araport11 should be considered for the next Arabidopsis genome annotation. This release identified 5198 phosphorylated proteins, 668 ubiquitinated proteins, 3050 N-terminally acetylated proteins, and 864 lysine-acetylated proteins and mapped their PTM sites. MS support was lacking for 21.4% (5896 proteins) of the predicted Araport11 proteome: the "dark" proteome. This dark proteome is highly enriched for E3 ligases, transcription factors, and for certain (e.g., CLE, IDA, PSY) but not other (e.g., THIONIN, CAP) signaling peptides families. A machine learning model trained on RNA expression data and protein properties predicts the probability that proteins will be detected. The model aids in discovery of proteins with short half-life (e.g., SIG1,3 and ERF-VII TFs) and for developing strategies to identify the missing proteins. PeptideAtlas is linked to TAIR, tracks in JBrowse, and several other community proteomics resources.

A High-Throughput PIXUL-Matrix-Based Toolbox to Profile Frozen and Formalin-Fixed Paraffin-Embedded Tissues Multiomes

Large-scale high-dimensional multiomics studies are essential to unravel molecular complexity in health and disease. We developed an integrated system for tissue sampling (CryoGrid), analytes preparation (PIXUL), and downstream multiomic analysis in a 96-well plate format (Matrix), MultiomicsTracks96, which we used to interrogate matched frozen and formalin-fixed paraffin-embedded (FFPE) mouse organs. Using this system, we generated 8-dimensional omics data sets encompassing 4 molecular layers of intracellular organization: epigenome (H3K27Ac, H3K4m3, RNA polymerase II, and 5mC levels), transcriptome (messenger RNA levels), epitranscriptome (m6A levels), and proteome (protein levels) in brain, heart, kidney, and liver. There was a high correlation between data from matched frozen and FFPE organs. The Segway genome segmentation algorithm applied to epigenomic profiles confirmed known organ-specific superenhancers in both FFPE and frozen samples. Linear regression analysis showed that proteomic profiles, known to be poorly correlated with transcriptomic data, can be more accurately predicted by the full suite of multiomics data, compared with using epigenomic, transcriptomic, or epitranscriptomic measurements individually.

Transcriptomic and proteomic fingerprints induced by the fungicides difenoconazole and metalaxyl in zebrafish embryos

In this study, we applied OMICs analysis to identify substance-specific biomarker candidates, which may act as early indicators for specific ecotoxic modes of actions (MoA). Zebrafish embryos were exposed to two sublethal concentrations of difenoconazole and metalaxyl according to a modified protocol of the OECD test guideline No. 236. At the end of exposure, total RNA and protein were extracted, followed by transcriptomics and proteomics analysis. The analysis of significantly differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) revealed a positive exposure-response correlation in all test concentrations for both fungicides. Similarly, also a positive correlation between the obtained transcriptome and proteome data was observed, highlighting the robustness of our approach. From the detected DEGs, candidate biomarkers specific for difenoconazole (apoa1b, gatm, mylpfb and acta1b) and metalaxyl (lgals2b, abat, fabp1b.1 and myh9a) were selected, and their biological functions were discussed to assess the predictive potential.

Exploring the Potential of siRNA Delivery in Acute Myeloid Leukemia for Therapeutic Silencing

We investigated the feasibility of using siRNA therapy for acute myeloid leukemia (AML) by developing macromolecular carriers that facilitated intracellular delivery of siRNA. The carriers were derived from low-molecular-weight (<2 kDa) polyethyleneimine (PEI) and modified with a range of aliphatic lipids. We identified linoleic acid and lauric acid-modified PEI as optimal carriers for siRNA delivery to AML cell lines KG1 and KG1a, as well as AML patient-derived mononuclear cells. As they have been proven to be potent targets in the treatment of AML, we examined the silencing of BCL2L12 and survivin and showed how it leads to the decrease in proliferation of KG1 and stem-cell-like KG1a cells. By optimizing the transfection schedule, we were able to enhance the effect of the siRNAs on proliferation over a period of 10 days. We additionally showed that with proper modifications of PEI, other genes, including MAP2K3, CDC20, and SOD-1, could be targeted to decrease the proliferation of AML cells. Our studies demonstrated the versatility of siRNA delivery with modified PEI to elicit an effect in leukemic cells that are difficult to transfect, offering an alternative to conventional drugs for more precise and targeted treatment options.

System analysis of surface CD markers during the process of granulocytic differentiation

Plasma membrane proteins with extracellular-exposed domains are responsible for transduction of extracellular signals into intracellular responses, and their accessibility to therapeutic molecules makes them attractive targets for drug development. In this work, using omics technologies and immunochemical methods, we have studied changes in the content of markers of clusters of differentiation (CD markers) of neutrophils (CD33, CD97, CD54, CD38, CD18, CD11b, CD44, and CD71) at the level of transcripts and proteins in NB4, HL-60 and K562 cell lines, induced by the treatment with all-trans-retinoic acid (ATRA). Transcriptomic analysis revealed the induction of CD38, CD54, CD11b, and CD18 markers as early as 3 h after the addition of the inducer in the ATRA-responsive cell lines HL-60 and NB4. After 24 h, a line-specific expression pattern of CD markers could be observed in all cell lines. Studies of changes in the content of CD antigens by means of flow cytometry and targeted mass spectrometry (MS) gave similar results. The proteomic profile of the surface markers (CD38, CD54, CD11b, and CD18), characteristic of the NB4 and HL-60 lines, reflects different molecular pathways for the implementation of ATRA-induced differentiation of leukemic cells into mature neutrophils.

A New Era of Integration between Multiomics and Spatio-Temporal Analysis for the Translation of EMT towards Clinical Applications in Cancer

Epithelial-mesenchymal transition (EMT) is crucial to metastasis by increasing cancer cell migration and invasion. At the cellular level, EMT-related morphological and functional changes are well established. At the molecular level, critical signaling pathways able to drive EMT have been described. Yet, the translation of EMT into efficient diagnostic methods and anti-metastatic therapies is still missing. This highlights a gap in our understanding of the precise mechanisms governing EMT. Here, we discuss evidence suggesting that overcoming this limitation requires the integration of multiple omics, a hitherto neglected strategy in the EMT field. More specifically, this work summarizes results that were independently obtained through epigenomics/transcriptomics while comprehensively reviewing the achievements of proteomics in cancer research. Additionally, we prospect gains to be obtained by applying spatio-temporal multiomics in the investigation of EMT-driven metastasis. Along with the development of more sensitive technologies, the integration of currently available omics, and a look at dynamic alterations that regulate EMT at the subcellular level will lead to a deeper understanding of this process. Further, considering the significance of EMT to cancer progression, this integrative strategy may enable the development of new and improved biomarkers and therapeutics capable of increasing the survival and quality of life of cancer patients.

Effect of herbivore stress on transgene behaviour in maize crosses with different genetic backgrounds: cry1Ab transgene transcription, insecticidal protein expression and bioactivity against insect pests

Background

Decades after their first commercial release, many theoretical assumptions are still taken for granted in the deployment of genetically modified (GM) crops. Theoretically, in the case of maize, active transcription of the cry1Ab transgene would result in dose-dependent production of the insecticidal Cry1Ab protein, which would in turn induce dose-dependent mortality on lepidopteran pests. We produced data to realistically approach this question by using a model that includes two genetic background contexts from two geographical provenances in Brazil and South Africa, and two lepidopteran pests (Helicoverpa armigera and Spodoptera littoralis). However, in this study, the effect of insect herbivory was superimposed to investigate possible stress-induced effects in transgene expression at three levels: mRNA, protein and bioactivity.

Results

Overall, we found that herbivore damage by H. armigera was reflected only at the translational level, with a higher level of Cry1Ab protein measured in the Brazilian crosses under herbivore stress. On the other hand, compared to non-stress growing conditions, the herbivore damage by S. littoralis was not directly reflected in mRNA, protein or bioactivity in the South African crosses.

Conclusions

The differences between South African and Brazilian genetic backgrounds, and between the stressor effect of the two herbivores used, highlight the complexity of transgene expression at the agroecological level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12302-023-00815-3.

Neuronal SNCA transcription during Lewy body formation

Misfolded α-synuclein (α-syn) is believed to contribute to neurodegeneration in Lewy body disease (LBD) based on considerable evidence including a gene-dosage effect observed in relation to point mutations and multiplication of SNCA in familial Parkinson's disease. A contradictory concept proposes early loss of the physiological α-syn as the major driver of neurodegeneration. There is a paucity of data on SNCA transcripts in various α-syn immunoreactive cytopathologies. Here, the total cell body, nuclear, and cytoplasmic area density of SNCA transcripts in neurons without and with various α-syn immunoreactive cytopathologies in the substantia nigra and amygdala in autopsy cases of LBD (n = 5) were evaluated using RNAscope combined with immunofluorescence for disease-associated α-syn. Single-nucleus RNA sequencing was performed to elucidate cell-type specific SNCA expression in non-diseased frontal cortex (n = 3). SNCA transcripts were observed in the neuronal nucleus and cytoplasm in neurons without α-syn, those containing punctate α-syn immunoreactivity, irregular-shaped compact inclusion, and brainstem-type and cortical-type LBs. However, SNCA transcripts were only rarely found in the α-syn immunoreactive LB areas. The total cell body SNCA transcript area densities in neurons with punctate α-syn immunoreactivity were preserved but were significantly reduced in neurons with compact α-syn inclusions both in the substantia nigra and amygdala. This reduction was also observed in the cytoplasm but not in the nucleus. Only single SNCA transcripts were detected in astrocytes with or without disease-associated α-syn immunoreactivity in the amygdala. Single-nucleus RNA sequencing revealed that excitatory and inhibitory neurons, oligodendrocyte progenitor cells, oligodendrocytes, and homeostatic microglia expressed SNCA transcripts, while expression was largely absent in astrocytes and microglia. The preserved cellular SNCA expression in the more abundant non-Lewy body type α-syn cytopathologies might provide a pool for local protein production that can aggregate and serve as a seed for misfolded α-syn. Successful segregation of disease-associated α-syn is associated with the exhaustion of SNCA production in the terminal cytopathology, the Lewy body. Our observations inform therapy development focusing on targeting SNCA transcription in LBD.

3'-tRF-CysGCA overexpression in HEK-293 cells alters the global expression profile and modulates cellular processes and pathways

tRNA fragments (tRFs) are small non-coding RNAs generated through specific cleavage of tRNAs and involved in various biological processes. Among the different types of tRFs, the 3'-tRFs have attracted scientific interest due to their regulatory role in gene expression. In this study, we investigated the role of 3'-tRF-CysGCA, a tRF deriving from cleavage in the T-loop of tRNACysGCA, in the regulation of gene expression in HEK-293 cells. Previous studies have shown that 3'-tRF-CysGCA is incorporated into the RISC complex and interacts with Argonaute proteins, suggesting its involvement in the regulation of gene expression. However, the general role and effect of the deregulation of 3'-tRF-CysGCA levels in human cells have not been investigated so far. To fill this gap, we stably overexpressed 3'-tRF-CysGCA in HEK-293 cells and performed transcriptomic and proteomic analyses. Moreover, we validated the interaction of this tRF with putative targets, the levels of which were found to be affected by 3'-tRF-CysGCA overexpression. Lastly, we investigated the implication of 3'-tRF-CysGCA in various pathways using extensive bioinformatics analysis. Our results indicate that 3'-tRF-CysGCA overexpression led to changes in the global gene expression profile of HEK-293 cells and that multiple cellular pathways were affected by the deregulation of the levels of this tRF. Additionally, we demonstrated that 3'-tRF-CysGCA directly interacts with thymopoietin (TMPO) transcript variant 1 (also known as LAP2α), leading to modulation of its levels. In conclusion, our findings suggest that 3'-tRF-CysGCA plays a significant role in gene expression regulation and highlight the importance of this tRF in cellular processes.

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.

Collagen type XIV is proportionally lower in the lung tissue of patients with IPF

Abnormal deposition of extracellular matrix (ECM) in lung tissue is a characteristic of idiopathic pulmonary fibrosis (IPF). Increased collagen deposition is also accompanied by altered collagen organization. Collagen type XIV, a fibril-associated collagen, supports collagen fibril organization. Its status in IPF has not been described at the protein level yet. In this study, we utilized publicly available datasets for single-cell RNA-sequencing for characterizing collagen type XIV expression at the gene level. For protein level comparison, we applied immunohistochemical staining for collagen type XIV on lung tissue sections from IPF patients and compared it to lung tissue sections from never smoking and ex-smoking donors. Analyzing the relative amounts of collagen type XIV at the whole tissue level, as well as in parenchyma, airway wall and bronchial epithelium, we found consistently lower proportions of collagen type XIV in all lung tissue compartments across IPF samples. Our study suggests proportionally lower collagen type XIV in IPF lung tissues may have implications for the assembly of the ECM fibers potentially contributing to progression of fibrosis.

Extracellular RNAs released by plant-associated fungi: from fundamental mechanisms to biotechnological applications

Extracellular RNAs are an emerging research topic in fungal-plant interactions. Fungal plant pathogens and symbionts release small RNAs that enter host cells to manipulate plant physiology and immunity. This communication via extracellular RNAs between fungi and plants is bidirectional. On the one hand, plants release RNAs encapsulated inside extracellular vesicles as a defense response as well as for intercellular and inter-organismal communication. On the other hand, recent reports suggest that also full-length mRNAs are transported within fungal EVs into plants, and these fungal mRNAs might get translated inside host cells. In this review article, we summarize the current views and fundamental concepts of extracellular RNAs released by plant-associated fungi, and we discuss new strategies to apply extracellular RNAs in crop protection against fungal pathogens. KEY POINTS: • Extracellular RNAs are an emerging topic in plant-fungal communication. • Fungi utilize RNAs to manipulate host plants for colonization. • Extracellular RNAs can be engineered to protect plants against fungal pathogens.

Members of the CUGBP Elav-like family of RNA-binding proteins are expressed in distinct populations of primary sensory neurons

Primary sensory dorsal root ganglia (DRG) neurons are diverse, with distinct populations that respond to specific stimuli. Previously, we observed that functionally distinct populations of DRG neurons express mRNA transcript variants with different 3' untranslated regions (3'UTRs). 3'UTRs harbor binding sites for interaction with RNA-binding proteins (RBPs) for transporting mRNAs to subcellular domains, modulating transcript stability, and regulating the rate of translation. In the current study, analysis of publicly available single-cell RNA-sequencing data generated from adult mice revealed that 17 3'UTR-binding RBPs were enriched in specific populations of DRG neurons. This included four members of the CUG triplet repeat (CUGBP) Elav-like family (CELF): CELF2 and CELF4 were enriched in peptidergic, CELF6 in both peptidergic and nonpeptidergic, and CELF3 in tyrosine hydroxylase-expressing neurons. Immunofluorescence studies confirmed that 60% of CELF4+ neurons are small-diameter C fibers and 33% medium-diameter myelinated (likely Aδ) fibers and showed that CELF4 is distributed to peripheral termini. Coexpression analyses using transcriptomic data and immunofluorescence revealed that CELF4 is enriched in nociceptive neurons that express GFRA3, CGRP, and the capsaicin receptor TRPV1. Reanalysis of published transcriptomic data from macaque DRG revealed a highly similar distribution of CELF members, and reanalysis of single-nucleus RNA-sequencing data derived from mouse and rat DRG after sciatic injury revealed differential expression of CELFs in specific populations of sensory neurons. We propose that CELF RBPs may regulate the fate of mRNAs in populations of nociceptors, and may play a role in pain and/or neuronal regeneration following nerve injury.

Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast

Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3.6%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.

Highlights

At the level of individual genes, the abundance of transcripts and proteins is weakly correlated within a species ( ρ = 0.165). While the proteome is not imprinted by population structure, co-expression patterns recapitulate the cellular functional landscapeWild populations exhibit a higher abundance of respiration-related proteins compared to domesticated populationsLoci that influence protein abundance differ from those that impact transcript levels, likely because of protein turnover.