Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation

Phenotypic Landscape of Immune Cells in Sepsis: Insights from High-Dimensional Mass Cytometry

Understanding the sepsis-induced immunological response can be facilitated by identifying phenotypic changes in immune cells at the single-cell level. Mass cytometry, a novel multiparametric single-cell analysis technique, offers considerable benefits in characterizing sepsis-induced phenotypic changes in peripheral blood mononuclear cells. Here, we analyzed peripheral blood mononuclear cells from 20 sepsis patients and 10 healthy donors using mass cytometry and employing 23 markers. Both manual gating and automated clustering approaches (PhenoGraph) were used for cell identification, complemented by uniform manifold approximation and projection (UMAP) for dimensionality reduction and visualization. Our study revealed that patients with sepsis exhibited a unique immune cell profile, marked by an increased presence of monocytes, B cells, and dendritic cells, alongside a reduction in natural killer (NK) cells and CD4/CD8 T cells. Notably, significant changes in the distributions of monocytes and B and CD4 T cells were observed. Clustering with PhenoGraph unveiled the subsets of each cell type and identified elevated CCR6 expression in sepsis patients' monocyte subset (PG#5), while further PhenoGraph clustering on manually gated T and B cells discovered sepsis-specific CD4 T cell subsets (CCR4low CD20low CD38low) and B cell subsets (HLA-DRlow CCR7low CCR6high), which could potentially serve as novel diagnostic markers for sepsis.

Targeting miR-181a/b in retinitis pigmentosa: implications for disease progression and therapy

BACKGROUND

Retinitis pigmentosa (RP) is a genetically heterogeneous group of degenerative disorders causing progressive vision loss due to photoreceptor death. RP affects other retinal cells, including the retinal pigment epithelium (RPE). MicroRNAs (miRs) are implicated in RP pathogenesis, and downregulating miR-181a/b has shown therapeutic benefit in RP mouse models by improving mitochondrial function. This study investigates the expression profile of miR-181a/b in RPE cells and the neural retina during RP disease progression. We also evaluate how miR-181a/b downregulation, by knocking out miR-181a/b-1 cluster in RPE cells, confers therapeutic efficacy in an RP mouse model and explore the mechanisms underlying this process.

RESULTS

Our findings reveal distinct expression profiles, with downregulated miR-181a/b in RPE cells suggesting a protective response and upregulated miR-181a/b in the neural retina indicating a role in disease progression. We found that miR-181a/b-2, encoded in a separate genomic cluster, compensates for miR-181a/b-1 ablation in RPE cells at late time points. The transient downregulation of miR-181a/b in RPE cells at post-natal week 6 (PW6) led to improved RPE morphology, retarded photoreceptor degeneration and decreased RPE aerobic glycolysis.

CONCLUSIONS

Our study elucidates the underlying mechanisms associated with the therapeutic modulation of miR-181a/b, providing insights into the metabolic processes linked to its RPE-specific downregulation. Our data further highlights the impact of compensatory regulation between miR clusters with implications for the development of miR-based therapeutics.

Harnessing the power of proteomics in precision diabetes medicine

Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.

DESP demixes cell-state profiles from dynamic bulk molecular measurements

Understanding the dynamic expression of proteins and other key molecules driving phenotypic remodeling in development and pathobiology has garnered widespread interest, yet the exploration of these systems at the foundational resolution of the underlying cell states has been significantly limited by technical constraints. Here, we present DESP, an algorithm designed to leverage independent estimates of cell-state proportions, such as from single-cell RNA sequencing, to resolve the relative contributions of cell states to bulk molecular measurements, most notably quantitative proteomics, recorded in parallel. We applied DESP to an in vitro model of the epithelial-to-mesenchymal transition and demonstrated its ability to accurately reconstruct cell-state signatures from bulk-level measurements of both the proteome and transcriptome, providing insights into transient regulatory mechanisms. DESP provides a generalizable computational framework for modeling the relationship between bulk and single-cell molecular measurements, enabling the study of proteomes and other molecular profiles at the cell-state level using established bulk-level workflows.

Comparative analysis of diisononyl phthalate and di(isononyl)cyclohexane-1,2 dicarboxylate plasticizers in regulation of lipid metabolism in 3T3-L1 cells

Diisononyl phthalate (DINP) and di(isononyl)cyclohexane-1,2-dicarboxylate (DINCH) are plasticizers introduced to replace previously used phthalate plasticizers in polymeric products. Exposure to DINP and DINCH has been shown to impact lipid metabolism. However, there are limited studies that address the mechanisms of toxicity of these two plasticizers. Here, a comparative toxicity analysis has been performed to evaluate the impacts of DINP and DINCH on 3T3-L1 cells. The preadipocyte 3T3-L1 cells were exposed to 1, 10, and 100 μM of DINP or DINCH for 10 days and assessed for lipid accumulation, gene expression, and protein analysis. Lipid staining showed that higher concentrations of DINP and DINCH can induce adipogenesis. The gene expression analysis demonstrated that both DINP and DINCH could alter the expression of lipid-related genes involved in adipogenesis. DINP and DINCH upregulated Pparγ, Pparα, C/EBPα Fabp4, and Fabp5, while both compounds significantly downregulated Fasn and Gata2. Protein analysis showed that both DINP and DINCH repressed the expression of FASN. Additionally, we analyzed an independent transcriptome dataset encompassing temporal data on lipid differentiation within 3T3-L1 cells. Subsequently, we derived a gene set that accurately portrays significant pathways involved in lipid differentiation, which we subsequently subjected to experimental validation through quantitative polymerase chain reaction. In addition, we extended our analysis to encompass a thorough assessment of the expression profiles of this identical gene set across 40 discrete transcriptome datasets that have linked to diverse pathological conditions to foreseen any potential association with DINP and DINCH exposure. Comparative analysis indicated that DINP could be more effective in regulating lipid metabolism.

Gene expression flux analysis reveals specific regulatory modalities of gene expression

The level of a given protein is determined by the synthesis and degradation rates of its mRNA and protein. While several studies have quantified the contribution of different gene expression steps in regulating protein levels, these are limited by using equilibrium approximations in out-of-equilibrium biological systems. Here, we introduce gene expression flux analysis to quantitatively dissect the dynamics of the expression level for specific proteins and use it to analyze published transcriptomics and proteomics datasets. Our analysis reveals distinct regulatory modalities shared by sets of genes with clear functional signatures. We also find that protein degradation plays a stronger role than expected in the adaptation of protein levels. These findings suggest that shared regulatory strategies can lead to versatile responses at the protein level and highlight the importance of going beyond equilibrium approximations to dissect the quantitative contribution of different steps of gene expression to protein dynamics.

The RNA binding proteins ZFP36L1 and ZFP36L2 are dysregulated in airway epithelium in human and a murine model of asthma

Introduction: Asthma is the most common chronic inflammatory disease of the airways. The airway epithelium is a key driver of the disease, and numerous studies have established genome-wide differences in mRNA expression between health and asthma. However, the underlying molecular mechanisms for such differences remain poorly understood. The human TTP family is comprised of ZFP36, ZFP36L1 and ZFP36L2, and has essential roles in immune regulation by determining the stability and translation of myriad mRNAs encoding for inflammatory mediators. We investigated the expression and possible role of the tristetraprolin (TTP) family of RNA binding proteins (RBPs), poorly understood in asthma. Methods: We analysed the levels of ZFP36, ZFP36L1 and ZFP36L2 mRNA in several publicly available asthma datasets, including single cell RNA-sequencing. We also interrogated the expression of known targets of these RBPs in asthma. We assessed the lung mRNA expression and cellular localization of Zfp36l1 and Zfp36l2 in precision cut lung slices in murine asthma models. Finally, we determined the expression in airway epithelium of ZFP36L1 and ZFP36L2 in human bronchial biopsies and performed rescue experiments in primary bronchial epithelium from patients with severe asthma. Results: We found ZFP36L1 and ZFP36L2 mRNA levels significantly downregulated in the airway epithelium of patients with very severe asthma in different cohorts (5 healthy vs. 8 severe asthma; 36 moderate asthma vs. 37 severe asthma on inhaled steroids vs. 26 severe asthma on oral corticoids). Integrating several datasets allowed us to infer that mRNAs potentially targeted by these RBPs are increased in severe asthma. Zfp36l1 was downregulated in the lung of a mouse model of asthma, and immunostaining of ex vivo lung slices with a dual antibody demonstrated that Zfp36l1/l2 nuclear localization was increased in the airway epithelium of an acute asthma mouse model, which was further enhanced in a chronic model. Immunostaining of human bronchial biopsies showed that airway epithelial cell staining of ZFP36L1 was decreased in severe asthma as compared with mild, while ZFP36L2 was upregulated. Restoring the levels of ZFP36L1 and ZFP36L2 in primary bronchial epithelial cells from patients with severe asthma decreased the mRNA expression of IL6, IL8 and CSF2. Discussion: We propose that the dysregulation of ZFP36L1/L2 levels as well as their subcellular mislocalization contributes to changes in mRNA expression and cytoplasmic fate in asthma.

De novo network analysis reveals autism causal genes and developmental links to co-occurring traits

Autism is a complex neurodevelopmental condition that manifests in various ways. Autism is often accompanied by other conditions, such as attention-deficit/hyperactivity disorder and schizophrenia, which can complicate diagnosis and management. Although research has investigated the role of specific genes in autism, their relationship with co-occurring traits is not fully understood. To address this, we conducted a two-sample Mendelian randomisation analysis and identified four genes located at the 17q21.31 locus that are putatively causal for autism in fetal cortical tissue (LINC02210, LRRC37A4P, RP11-259G18.1, and RP11-798G7.6). LINC02210 was also identified as putatively causal for autism in adult cortical tissue. By integrating data from expression quantitative trait loci, genes and protein interactions, we identified that the 17q21.31 locus contributes to the intersection between autism and other neurological traits in fetal cortical tissue. We also identified a distinct cluster of co-occurring traits, including cognition and worry, linked to the genetic loci at 3p21.1. Our findings provide insights into the relationship between autism and co-occurring traits, which could be used to develop predictive models for more accurate diagnosis and better clinical management.

Substrate-specific effects of natural genetic variation on proteasome activity

Protein degradation is an essential biological process that regulates protein abundance and removes misfolded and damaged proteins from cells. In eukaryotes, most protein degradation occurs through the stepwise actions of two functionally distinct entities, the ubiquitin system and the proteasome. Ubiquitin system enzymes attach ubiquitin to cellular proteins, targeting them for degradation. The proteasome then selectively binds and degrades ubiquitinated substrate proteins. Genetic variation in ubiquitin system genes creates heritable differences in the degradation of their substrates. However, the challenges of measuring the degradative activity of the proteasome independently of the ubiquitin system in large samples have limited our understanding of genetic influences on the proteasome. Here, using the yeast Saccharomyces cerevisiae, we built and characterized reporters that provide high-throughput, ubiquitin system-independent measurements of proteasome activity. Using single-cell measurements of proteasome activity from millions of genetically diverse yeast cells, we mapped 15 loci across the genome that influence proteasomal protein degradation. Twelve of these 15 loci exerted specific effects on the degradation of two distinct proteasome substrates, revealing a high degree of substrate-specificity in the genetics of proteasome activity. Using CRISPR-Cas9-based allelic engineering, we resolved a locus to a causal variant in the promoter of RPT6, a gene that encodes a subunit of the proteasome's 19S regulatory particle. The variant increases RPT6 expression, which we show results in increased proteasome activity. Our results reveal the complex genetic architecture of proteasome activity and suggest that genetic influences on the proteasome may be an important source of variation in the many cellular and organismal traits shaped by protein degradation.

Tumor heterogeneity in VHL drives metastasis in clear cell renal cell carcinoma

Loss of function of the von Hippel-Lindau (VHL) tumor suppressor gene is a hallmark of clear cell renal cell carcinoma (ccRCC). The importance of heterogeneity in the loss of this tumor suppressor has been under reported. To study the impact of intratumoral VHL heterogeneity observed in human ccRCC, we engineered VHL gene deletion in four RCC models, including a new primary tumor cell line derived from an aggressive metastatic case. The VHL gene-deleted (VHL-KO) cells underwent epithelial-to-mesenchymal transition (EMT) and exhibited increased motility but diminished proliferation and tumorigenicity compared to the parental VHL-expressing (VHL+) cells. Renal tumors with either VHL+ or VHL-KO cells alone exhibit minimal metastatic potential. Combined tumors displayed rampant lung metastases, highlighting a novel cooperative metastatic mechanism. The poorly proliferative VHL-KO cells stimulated the proliferation, EMT, and motility of neighboring VHL+ cells. Periostin (POSTN), a soluble protein overexpressed and secreted by VHL non-expressing (VHL-) cells, promoted metastasis by enhancing the motility of VHL-WT cells and facilitating tumor cell vascular escape. Genetic deletion or antibody blockade of POSTN dramatically suppressed lung metastases in our preclinical models. This work supports a new strategy to halt the progression of ccRCC by disrupting the critical metastatic crosstalk between heterogeneous cell populations within a tumor.

Transcriptome analysis reveals differences in cell cycle, growth and migration related genes that distinguish fibroblasts derived from pre-invasive and invasive breast cancer

Background/Introduction

As the most common form of pre-invasive breast cancer, ductal carcinoma in situ (DCIS) affects over 50,000 women in the US annually. Despite standardized treatment involving lumpectomy and radiation therapy, up to 25% of patients with DCIS experience disease recurrence often with invasive ductal carcinoma (IDC), indicating that a subset of patients may be under-treated. As most DCIS cases will not progress to invasion, many patients may experience over-treatment. By understanding the underlying processes associated with DCIS to IDC progression, we can identify new biomarkers to determine which DCIS cases may become invasive and improve treatment for patients. Accumulation of fibroblasts in IDC is associated with disease progression and reduced survival. While fibroblasts have been detected in DCIS, little is understood about their role in DCIS progression.

Goals

We sought to determine 1) whether DCIS fibroblasts were similar or distinct from normal and IDC fibroblasts at the transcriptome level, and 2) the contributions of DCIS fibroblasts to breast cancer progression.

Methods

Fibroblasts underwent transcriptome profiling and pathway analysis. Significant DCIS fibroblast-associated genes were further analyzed in existing breast cancer mRNA databases and through tissue array immunostaining. Using the sub-renal capsule graft model, fibroblasts from normal breast, DCIS and IDC tissues were co-transplanted with DCIS.com breast cancer cells.

Results

Through transcriptome profiling, we found that DCIS fibroblasts were characterized by unique alterations in cell cycle and motility related genes such as PKMYT1, TGF-α, SFRP1 and SFRP2, which predicted increased cell growth and invasion by Ingenuity Pathway Analysis. Immunostaining analysis revealed corresponding increases in expression of stromal derived PKMYT1, TGF-α and corresponding decreases in expression of SFRP1 and SFRP2 in DCIS and IDC tissues. Grafting studies in mice revealed that DCIS fibroblasts enhanced breast cancer growth and invasion associated with arginase-1+ cell recruitment.

Conclusion

DCIS fibroblasts are phenotypically distinct from normal breast and IDC fibroblasts, and play an important role in breast cancer growth, invasion, and recruitment of myeloid cells. These studies provide novel insight into the role of DCIS fibroblasts in breast cancer progression and identify some key biomarkers associated with DCIS progression to IDC, with important clinical implications.

Pharmacological Modulation of the MIP-1 Family and Their Receptors Reduces Neuropathic Pain Symptoms and Influences Morphine Analgesia: Evidence from a Mouse Model

Neuropathic pain pathophysiology is not fully understood, but it was recently shown that MIP-1 family members (CCL3, CCL4, and CCL9) have strong pronociceptive properties. Our goal was to examine how pharmacological modulation of these chemokines and their receptors (CCR1 and CCR5) influence hypersensitivity after nerve injury in Albino Swiss male mice. The spinal changes in the mRNA/protein levels of the abovementioned chemokines and their receptors were measured using RT-qPCR and ELISA/Western blot techniques in a mouse model of chronic constriction injury of the sciatic nerve. Behavioral studies were performed using the von Frey and cold plate tests after pharmacological treatment with neutralizing antibodies (nAbs) against chemokines or antagonists (CCR1-J113863, CCR5-TAK-220/AZD-5672) alone and in coadministration with morphine on Day 7, when the hypersensitivity was fully developed. Our results showed enhanced protein levels of CCL3 and CCL9 1 and 7 days after nerve injury. The single intrathecal administration of CCL3 or CCL9 nAb, J113863, TAK-220, or AZD-5672 diminished neuropathic pain symptoms and enhanced morphine analgesia. These findings highlight the important roles of CCL3 and CCL9 in neuropathic pain and additionally indicate that these chemokines play essential roles in opioid analgesia. The obtained results suggest CCR1 and CCR5 as new, interesting targets in neuropathy treatment.

Neuronal P2X4 receptor may contribute to peripheral inflammatory pain in rat spinal dorsal horn

Objective

Intense inflammation may result in pain, which manifests as spinal central sensitization. There is growing evidence that purinergic signaling plays a pivotal role in the orchestration of pain processing. Over the last decade the ionotropic P2X purino receptor 4 (P2X4) got into spotlight in neuropathic disorders, however its precise spinal expression was scantily characterized during inflammatory pain. Thus, we intended to analyze the receptor distribution within spinal dorsal horn and lumbar dorsal root ganglia (DRG) of rats suffering in inflammatory pain induced by complete Freund adjuvant (CFA).

Methods

CFA-induced peripheral inflammation was validated by mechanical and thermal behavioral tests. In order to ensure about the putative alteration of spinal P2X4 receptor gene expression qPCR reactions were designed, followed by immunoperoxidase and Western blot experiments to assess changes at a protein level. Colocalization of P2X4 with neuronal and glial markers was investigated by double immunofluorescent labelings, which were subsequently analyzed with IMARIS software. Transmission electronmicroscopy was applied to study the ultrastructural localization of the receptor. Concurrently, in lumbar DRG cells similar methodology has been carried out to complete our observations.

Results

The figures of mechanical and thermal behavioral tests proved the establishment of CFA-induced inflammatory pain. We observed significant enhancement of P2X4 transcript level within the spinal dorsal horn 3 days upon CFA administration. Elevation of P2X4 immunoreactivity within Rexed lamina I-II of the spinal gray matter was synchronous with mRNA expression, and confirmed by protein blotting. According to IMARIS analysis the robust protein increase was mainly detected on primary afferent axonterminals and GFAP-labelled astrocyte membrane compartments, but not on postsynaptic dendrites was also validated ultrastructurally within the spinal dorsal horn. Furthermore, lumbar DRG analysis demonstrated that peptidergic and non-peptidergic nociceptive subsets of ganglia cells were also abundantly positive for P2X4 receptor in CFA model.

Conclusion

Here we provide novel evidence about involvement of neuronal and glial P2X4 receptor in the establishment of inflammatory pain.

Anticancer Effects of Thymoquinone through the Antioxidant Activity, Upregulation of Nrf2, and Downregulation of PD-L1 in Triple-Negative Breast Cancer Cells

The variety of therapies available for treating and preventing triple-negative breast cancer (TNBC) is constrained by the absence of progesterone receptors, estrogen receptors, and human epidermal growth factor receptor 2. Nrf2 (nuclear factor-erythroid 2-related factor), and PD-L1 (program cell death ligand 1), a downstream signaling target, have a strong correlation to oxidative stress and inflammation, major factors in the development and progression of TNBC. In this study, the genetically distinct MDA-MB-231 and MDA-MB-468 TNBC cells were treated with the natural component thymoquinone (TQ). The results show that TQ exhibits considerable antioxidant activity and decreases the generation of H₂O₂, at the same time increasing catalase (CAT) activity, superoxide dismutase (SOD) enzyme, and glutathione (GSH). Additionally, the results show that TQ treatment increased the levels of the different genes involved in the oxidative stress-antioxidant defense system PRNP, NQO1, and GCLM in both cell lines with significant large-fold change in MDA-MB-468 cells (+157.65 vs. +1.7, +48.87 vs. +2.63 and +4.78 vs. +2.17), respectively. Nrf2 mRNA and protein expression were also significantly increased in TQ-treated TNBC cells despite being higher in MDA-MB-468 cells (6.67 vs. 4.06). Meanwhile, TQ administration increased mRNA levels while decreasing PD-L1 protein expression in both cell lines. In conclusion, TQ modifies the expression of multiple oxidative-stress-antioxidant system genes, ROS, antioxidant enzymes, Nrf2, and PD-L1 protein, pointing to the therapeutic potential and chemopreventive utilization of TQ in TNBC.

High-throughput approaches to functional characterization of genetic variation in yeast

Expansion of sequencing efforts to include thousands of genomes is providing a fundamental resource for determining the genetic diversity that exists in a population. Now, high-throughput approaches are necessary to begin to understand the role these genotypic changes play in affecting phenotypic variation. Saccharomyces cerevisiae maintains its position as an excellent model system to determine the function of unknown variants with its exceptional genetic diversity, phenotypic diversity, and reliable genetic manipulation tools. Here, we review strategies and techniques developed in yeast that scale classic approaches of assessing variant function. These approaches improve our ability to better map quantitative trait loci at a higher resolution, even for rare variants, and are already providing greater insight into the role that different types of mutations play in phenotypic variation and evolution not just in yeast but across taxa.

Pilot Study: Immune Checkpoints Polymorphisms in Greek Primary Breast Cancer Patients

Background: Breast cancer is the most prevalent and second leading cause of cancer-related death in women worldwide. Despite early detection and better treatment therapies, 30% of early-stage breast cancer patients still develop recurrent disease. Breast cancer is a heterogeneous disease comprising several molecular subtypes, commonly classified into clinical subtypes based on the hormone receptor status. These subtypes included luminal A and luminal B, which have different prognoses. Breast cancer development and progression involve many factors. Polymorphisms of PD-1, PD-L1, and PD-L2 genes have been previously associated with high risk and prognosis of cancer. However, no studies have associated PD-1, PD-L1, and PD-L2 polymorphisms with primary breast cancer subtypes. Hence, this study evaluated functional single nucleotide polymorphisms of PD-1, PD-L1, and PD-L2 with primary breast cancer subtypes, luminal A, and luminal B. In addition, we evaluated the PD-L1 protein expression in relation to primary breast cancer subtypes and stages. Results: There were no significant differences in the allele frequencies of PD-1 polymorphisms (rs2227981 G>A, rs7421861 A>G, and rs11568821 C>T) and PD-L1 polymorphisms (rs10815225 C>T and rs2282055 T>G) when compared with the general European population. However, a significant difference was detected in one of the PD-L2 polymorphisms (rs1009759 A>G), with the G allele higher in breast cancer patients than in the general European population. A higher prevalence of the T allele of PD-L1 polymorphism rs2282055 T>G was observed in luminal B breast cancer patients compared with luminal A. No significant difference was detected in other polymorphisms. We also observed that the PD-L1 rs2282055 TT genotype was more prevalent in luminal B breast cancer patients compared with luminal A. Our results found no association of the selected SNPs in the PDCD1 gene with breast cancer risk. Similarly, the protein expression data showed that PD-L1 and PD-L2 are associated with an aggressive phenotype, Luminal B, and advanced breast cancer stage. Conclusion: These findings suggest that immune checkpoint polymorphisms are associated with the risk and subtypes of breast cancer.

BPA Decreases PDCD4 in Bovine Granulosa Cells Independently of miR-21 Inhibition

microRNAs (miRNAs) are susceptible to environmental factors that might affect cellular function and impose negative effects on female reproduction. miR-21 is the most abundant miRNA in bovine granulosa cells and is widely reported as affected by Bisphenol A (BPA) exposure, yet the cause and consequences are not entirely elucidated. BPA is a synthetic endocrine disruptor associated with poor fertility. miR-21 function in bovine granulosa cells is investigated utilizing locked nucleic acid (LNA) oligonucleotides to suppress miR-21. Before measuring apoptosis and quantifying miR-21 apoptotic targets PDCD4 and PTEN, transfection was optimized and validated. BPA was introduced to see how it affects miR-21 regulation and which BPA-mediated effects are influenced by miR-21. miR-21 knockdown and specificity against additional miRNAs were confirmed. miR-21 was found to have antiapoptotic effects, which could be explained by its effect on the proapoptotic target PDCD4, but not PTEN. Previous findings of miR-21 overexpression were validated using BPA treatments, and the temporal influence of BPA on miR-21 levels was addressed. Finally, BPA effects on upstream regulators, such as VMP1 and STAT3, explain the BPA-dependent upregulation of miR-21 expression. Overall, this research enhances our understanding of miR-21 function in granulosa cells and the mechanisms of BPA-induced reproductive impairment.

Diverse impact of N-acetylcysteine or alpha-lipoic acid supplementation during high-fat diet regime on fatty acid transporters in visceral and subcutaneous adipose tissue

PURPOSE

Adipose tissue's (AT) structural changes accompanying obesity may alter lipid transport protein expression and, thus, the fatty acids (FAs) transport and lipid balance of the body. Metabolic abnormalities within AT contribute to the elevated production of reactive oxygen species and increased oxidative/nitrosative stress. Although compounds such as N-acetylcysteine (NAC) and α-lipoic acid (ALA), which restore redox homeostasis, may improve lipid metabolism in AT, the mechanism of action of these antioxidants on lipid metabolism in AT is still unknown. This study aimed to examine the impact of NAC and ALA on the level and FA composition of the lipid fractions, and the expression of FA transporters in the visceral and subcutaneous AT of high-fat diet-fed rats.

MATERIALS AND METHODS

Male Wistar rats were randomly divided into four groups. The mRNA levels and protein expression of FA transporters were assessed using real-time PCR and Western Blot analyses. The collected samples were subjected to histological evaluation. The level of lipids (FFA, DAG, and TAG) was measured using gas-liquid chromatography.

RESULTS

We found that antioxidants affect FA transporter expressions at both the transcript and protein levels, and, therefore, they promote changes in AT's lipid pools. One of the most remarkable findings of our research is that different antioxidant molecules may have a varying impact on AT phenotype.

CONCLUSION

NAC and ALA exert different influences on AT, which is reflected in histopathological images, FA transport proteins expression patterns, or even the lipid storage capacity of adipocytes.

Quantifying protein abundance on single cells using split-pool sequencing on DNA-barcoded antibodies for diagnostic applications

Proteins play critical roles across all facets of biology, with their abundance frequently used as markers of cell identity and state. The most popular method for detecting proteins on single cells, flow cytometry, is limited by considerations of fluorescent spectral overlap. While mass cytometry (CyTOF) allows for the detection of upwards of 40 epitopes simultaneously, it requires local access to specialized instrumentation not commonly accessible to many laboratories. To overcome these limitations, we independently developed a method to quantify multiple protein targets on single cells without the need for specialty equipment other than access to widely available next generation sequencing (NGS) services. We demonstrate that this combinatorial indexing method compares favorably to traditional flow-cytometry, and allows over two dozen target proteins to be assayed at a time on single cells. To showcase the potential of the technique, we analyzed peripheral blood and bone marrow aspirates from human clinical samples, and identified pathogenic cellular subsets with high fidelity. The ease of use of this technique makes it a promising technology for high-throughput proteomics and for interrogating complex samples such as those from patients with leukemia.

Multiple epistatic DNA variants in a single gene affect gene expression in trans

DNA variants that alter gene expression in trans are important sources of phenotypic variation. Nevertheless, the identity of trans-acting variants remains poorly understood. Single causal variants in several genes have been reported to affect the expression of numerous distant genes in trans. Whether these simple molecular architectures are representative of trans-acting variation is unknown. Here, we studied the large RAS signaling regulator gene IRA2, which contains variants with extensive trans-acting effects on gene expression in the yeast Saccharomyces cerevisiae. We used systematic CRISPR-based genome engineering and a sensitive phenotyping strategy to dissect causal variants to the nucleotide level. In contrast to the simple molecular architectures known so far, IRA2 contained at least seven causal nonsynonymous variants. The effects of these variants were modulated by nonadditive, epistatic interactions. Two variants at the 5'-end affected gene expression and growth only when combined with a third variant that also had no effect in isolation. Our findings indicate that the molecular basis of trans-acting genetic variation may be considerably more complex than previously appreciated.

Identification of Taxonomically Restricted Transcripts from Illumina RNA Sequencing Data

In order to perform a well-balanced comparative transcriptomic analysis, the reference genome and annotations for all species included in the comparison must be of a similar quality and completeness. Frequently, comparative transcriptomic analyses include non-model organisms whose annotations are not as well curated; this inequality can lead to biases.To avoid potential biases stemming from incomplete annotations, a comparative transcriptomic analysis can incorporate de novo transcriptome assemblies for each species, which reduces this disparity. This chapter covers all of the steps which are necessary to run a comparative transcriptomic analysis with de novo transcriptome assemblies, from the first step of the experimental design to the sequencing, and ultimately the bioinformatic analysis.

Multi-omics analysis reveals the genetic basis of rice fragrance mediated by betaine aldehyde dehydrogenase 2

INTRODUCTION

Fragrance is an important economic and quality trait in rice. The trait is controlled by the recessive gene betaine aldehyde dehydrogenase 2 (BADH2) via the production of 2-acetyl-1-pyrroline (2AP).

OBJECTIVES

Variation in BADH2 was evaluated at the population, genetic, transcriptional, and metabolic levels to obtain insights into fragrance regulation in rice.

METHODS

Whole-genome resequencing of the Korean World Rice Collection of 475 rice accessions, including 421 breeding lines and 54 wild accessions, was performed. Transcriptome analyses of a subset of 279 accessions, proteome analyses of 64 accessions, and volatile profiling of 421 breeding lines were also performed.

RESULTS

We identified over 3.1 million high-quality single nucleotide polymorphisms (SNPs) in Korean rice collection. Most SNPs were present in intergenic regions (79%), and 190,148 SNPs (6%) were located in the coding sequence, of which 53% were nonsynonymous. In total, 38 haplotypes were identified in the BADH2 coding region, including four novel haplotypes (one in cultivated and three in wild accessions). Tajima's D values suggested that BADH2 was under balancing selection in japonica rice. Furthermore, we identified 316 expression quantitative trait loci (eQTL), including 185 cis-eQTLs and 131 trans-eQTLs, involved in BADH2 regulation. A protein quantitative trait loci (pQTL) analysis revealed the presence of trans-pQTLs; 13 pQTLs were mapped 1 Mbp from the BADH2 region. Based on variable importance in projection (VIP) scores, 15 volatile compounds, including 2AP, discriminated haplotypes and were potential biomarkers for rice fragrance.

CONCLUSION

We generated a catalog of haplotypes based on a resequencing analysis of a large number of rice accessions. eQTLs and pQTLs associated with BADH2 gene expression and protein accumulation are likely involved in the regulation of 2AP variation in fragrant rice. These data improve our understanding of fragrance and provide valuable information for rice breeding.

The role of alternative splicing in adaptation and evolution

Regulation of gene expression plays a central role in adaptive divergence and evolution. Although the role of gene regulation in microevolutionary processes is gaining wide acceptance, most studies have only investigated the evolution of transcript levels, ignoring the potentially significant role of transcript structures. We argue that variation in alternative splicing plays an important and widely unexplored role in adaptation (e.g., by increasing transcriptome and/or proteome diversity, or buffering potentially deleterious genetic variation). New studies increasingly highlight the potential for independent evolution in alternative splicing and transcript level, providing alternative paths for selection to act upon. We propose that alternative splicing and transcript levels can provide contrasting, nonredundant mechanisms of equal importance for adaptive diversification of gene function and regulation.

Osteoprotegerin expression and serum values in obese women with type 2 diabetes mellitus

BACKGROUND

Obesity and diabetes prevalence are increasing worldwide. We aimed to detect the possible association of osteoprotegerin (OPG) gene expression with visceral adiposity indices and cardiometabolic risk factors among obese women.

METHODS AND RESULTS

The study enrolled 150 controls and 150 obese cases subdivided into two subgroups non-diabetic (n = 70) and 80 patients with type 2 diabetes mellitus (T2DM). Circulating OPG gene expression levels were figured out by real time PCR (Polymerase Chain Reaction). Serum OPG levels were assessed by Enzyme Linked Immunosorbent Assay. Our results explored that OPG serum levels were lower in the obese women compared to control group (p < 0.001) and obese diabetics had higher serum levels of OPG in comparison to obese non-diabetic patients (p < 0.001). Expression levels of OPG were higher in obese women than controls (p < 0.001). Moreover, the blood expression levels of OPG gene were higher in diabetic obese patients than non-diabetics. We found positive correlations between parameters of metabolic syndrome and obesity indices. After adjustment of the traditional risk factors, stepwise linear regression analysis test revealed that OPG expression levels were independently correlated with glycated hemoglobin, high-density lipoprotein-cholesterol, and waist-to-hip ratio.

CONCLUSIONS

OPG mRNA levels were associated with surrogate markers of insulin resistance in Egyptian obese women.

A genome-scale yeast library with inducible expression of individual genes

The ability to switch a gene from off to on and monitor dynamic changes provides a powerful approach for probing gene function and elucidating causal regulatory relationships. Here, we developed and characterized YETI (Yeast Estradiol strains with Titratable Induction), a collection in which > 5,600 yeast genes are engineered for transcriptional inducibility with single-gene precision at their native loci and without plasmids. Each strain contains SGA screening markers and a unique barcode, enabling high-throughput genetics. We characterized YETI using growth phenotyping and BAR-seq screens, and we used a YETI allele to identify the regulon of Rof1, showing that it acts to repress transcription. We observed that strains with inducible essential genes that have low native expression can often grow without inducer. Analysis of data from eukaryotic and prokaryotic systems shows that native expression is a variable that can bias promoter-perturbing screens, including CRISPRi. We engineered a second expression system, Z3 EB42, that gives lower expression than Z3 EV, a feature enabling conditional activation and repression of lowly expressed essential genes that grow without inducer in the YETI library.

Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation

Trans-acting DNA variants may specifically affect mRNA or protein levels of genes located throughout the genome. However, prior work compared trans-acting loci mapped in separate studies, many of which had limited statistical power. Here, we developed a CRISPR-based system for simultaneous quantification of mRNA and protein of a given gene via dual fluorescent reporters in single, live cells of the yeast Saccharomyces cerevisiae. In large populations of recombinant cells from a cross between two genetically divergent strains, we mapped 86 trans-acting loci affecting the expression of ten genes. Less than 20% of these loci had concordant effects on mRNA and protein of the same gene. Most loci influenced protein but not mRNA of a given gene. One locus harbored a premature stop variant in the YAK1 kinase gene that had specific effects on protein or mRNA of dozens of genes. These results demonstrate complex, post-transcriptional genetic effects on gene expression.

Systematic identification of cis-regulatory variants that cause gene expression differences in a yeast cross

Sequence variation in regulatory DNA alters gene expression and shapes genetically complex traits. However, the identification of individual, causal regulatory variants is challenging. Here, we used a massively parallel reporter assay to measure the cis-regulatory consequences of 5832 natural DNA variants in the promoters of 2503 genes in the yeast Saccharomyces cerevisiae. We identified 451 causal variants, which underlie genetic loci known to affect gene expression. Several promoters harbored multiple causal variants. In five promoters, pairs of variants showed non-additive, epistatic interactions. Causal variants were enriched at conserved nucleotides, tended to have low derived allele frequency, and were depleted from promoters of essential genes, which is consistent with the action of negative selection. Causal variants were also enriched for alterations in transcription factor binding sites. Models integrating these features provided modest, but statistically significant, ability to predict causal variants. This work revealed a complex molecular basis for cis-acting regulatory variation.