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Resistance training is used to combat skeletal muscle function decline in older adults. Few studies have been designed specific for females, resulting in very limited treatment options for skeletal muscle atrophy in aging women. Here, we analyzed the gene expression profiles of skeletal muscle samples from sedentary young women, sedentary older women, and resistance-trained older women, using microarray data from public database. A total of 45 genes that were differentially expressed during female muscle aging and reversed by resistance training were identified. Functional and pathway enrichment analysis, protein–protein interaction network analysis, and receiver operating characteristic analysis were performed to reveal the key genes and pathways involved in the effects of resistance training on female muscle aging. The collagen genes COL1A1, COL3A1, and COL4A1 were identified important regulators of female muscle aging and resistance training, by modulating multiple signaling pathways, such as PI3 kinase-Akt signaling, focal adhesions, extracellular matrix-receptor interactions, and relaxin signaling. Interestingly, the expression of CDKN1A and TP63 were increased during aging, and further upregulated by resistance training in older women, suggesting they may negatively affect resistance training outcomes. Our findings provide novel insights into the molecular mechanisms of resistance training on female muscle aging and identify potential biomarkers and targets for clinical intervention. [ABSTRACT FROM AUTHOR]

Intragenic translational heterogeneity describes the variation in translation at the level of transcripts for an individual gene. A factor that contributes to this source of variation is the mRNA structure. Both the composition of the thermodynamic ensemble, i.e., the stationary distribution of mRNA structures, and the switching dynamics between those play a role. The effect of the switching dynamics on intragenic translational heterogeneity remains poorly understood. We present a stochastic translation model that accounts for mRNA structure switching and is derived from a Markov model via approximate stochastic filtering. We assess the approximation on various timescales and provide a method to quantify how mRNA structure dynamics contributes to translational heterogeneity. With our approach, we allow quantitative information on mRNA switching from biophysical experiments or coarse-grain molecular dynamics simulations of mRNA structures to be included in gene regulatory chemical reaction network models without an increase in the number of species. Thereby, our model bridges a gap between mRNA structure kinetics and gene expression models, which we hope will further improve our understanding of gene regulatory networks and facilitate genetic circuit design. [ABSTRACT FROM AUTHOR]

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p 0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.

We created a 2-week, dual-module summer course introducing high school students to environmental toxicology by teaching them quantitative polymerase chain reaction (qPCR) as a way to quantify gene expression of chemical defense proteins in response to exposure to environmental pollutants. During the course, students are guided through the various stages of a successful qPCR experiment: in silico primer design and quality control, total RNA extraction and isolation, cDNA conversion, primer test PCR, and evaluation of results via agarose gel electrophoresis or UV/Vis spectra. The course combines lectures, discussions, and demonstrations with dry and wet laboratory sections to give students a thorough understanding of the scope, utility, and chemical principles of qPCR. At the end of the course, the students are taught how to analyze qPCR data and are encouraged to discuss their findings with other classmates to evaluate their hypotheses and assess possible sources of error. This course was designed to be easily adaptable to multiple test species, chemical exposures, and genes of interest. To explore both terrestrial and aquatic toxicology, the students use honey bees (Apis mellifera) and mosquitofish (Gambusia affinis) as test organisms, as well as ABC-type efflux transporters, antioxidant enzymes, and cytochrome P450 enzymes as endpoints for assessing gene expression. We share this course setup and applied protocols to encourage others to design and offer similar courses that give high school students a hands-on introduction to a broad swath of environmental toxicology research and an opportunity to develop scientific skills necessary for university-level research.

Aposematic organisms rely on their conspicuous appearance to signal that they are defended and unpalatable. Such phenotypes are strongly tied to survival and reproduction. Aposematic colors and patterns are highly variable; however, the genetic, biochemical, and physiological mechanisms producing this conspicuous coloration remain largely unidentified. Here, we identify genes potentially affecting color variation in two color morphs of Ranitomeya imitator: the orange-banded Sauce and the redheaded Varadero morphs. We examine gene expression in black and orange skin patches from the Sauce morph and black and red skin patches from the Varadero morph. We identified genes differentially expressed between skin patches, including those that are involved in melanin synthesis (e.g. mlana, pmel, tyrp1), iridophore development (e.g. paics, ppat, ak1), pteridine synthesis (e.g. gch1, pax3-a, xdh), and carotenoid metabolism (e.g. dgat2, rbp1, scarb2). In addition, using weighted correlation network analysis, we identified the top 50 genes with high connectivity from the most significant network associated with gene expression differences between color morphs. Of these 50 genes, 13 were known to be related to color production (gch1, gmps, gpr143, impdh1, mc1r, pax3-a, pax7, ppat, rab27a, rlbp1, tfec, trpm1, xdh).

BACKGROUND: Sex-differential biology may contribute to the consistently male-biased prevalence of autism spectrum disorder (ASD). Gene expression differences between males and females in the brain can indicate possible molecular and cellular mechanisms involved, although transcriptomic sex differences during human prenatal cortical development have been incompletely characterized, primarily due to small sample sizes. METHODS: We performed a meta-analysis of sex-differential expression and co-expression network analysis in 2 independent bulk RNA sequencing datasets generated from cortex of 273 prenatal donors without known neuropsychiatric disorders. To assess the intersection between neurotypical sex differences and neuropsychiatric disorder biology, we tested for enrichment of ASD-associated risk genes and expression changes, neuropsychiatric disorder risk genes, and cell type markers within identified sex-differentially expressed genes (sex-DEGs) and sex-differential co-expression modules. RESULTS: We identified 101 significant sex-DEGs, including Y-chromosome genes, genes impacted by X-chromosome inactivation, and autosomal genes. Known ASD risk genes, implicated by either common or rare variants, did not preferentially overlap with sex-DEGs. We identified 1 male-specific co-expression module enriched for immune signaling that is unique to 1 input dataset. CONCLUSIONS: Sex-differential gene expression is limited in prenatal human cortex tissue, although meta-analysis of large datasets allows for the identification of sex-DEGs, including autosomal genes that encode proteins involved in neural development. Lack of sex-DEG overlap with ASD risk genes in the prenatal cortex suggests that sex-differential modulation of ASD symptoms may occur in other brain regions, at other developmental stages, or in specific cell types, or may involve mechanisms that act downstream from mutation-carrying genes.

Extrachromosomal DNA is a common cause of oncogene amplification in cancer. The non-chromosomal inheritance of ecDNA enables tumors to rapidly evolve, contributing to treatment resistance and poor outcome for patients. The transcriptional context in which ecDNAs arise and progress, including chromosomally-driven transcription, is incompletely understood. We examined gene expression patterns of 870 tumors of varied histological types, to identify transcriptional correlates of ecDNA. Here, we show that ecDNA-containing tumors impact four major biological processes. Specifically, ecDNA-containing tumors up-regulate DNA damage and repair, cell cycle control, and mitotic processes, but down-regulate global immune regulation pathways. Taken together, these results suggest profound alterations in gene regulation in ecDNA-containing tumors, shedding light on molecular processes that give rise to their development and progression.

The cellular components of tumors and their microenvironment play pivotal roles in tumor progression, patient survival, and the response to cancer treatments. Unveiling a comprehensive cellular profile within bulk tumors via single-cell RNA sequencing (scRNA-seq) data is crucial, as it unveils intrinsic tumor cellular traits that elude identification through conventional cancer subtyping methods. Our contribution, scBeacon, is a tool that derives cell-type signatures by integrating and clustering multiple scRNA-seq datasets to extract signatures for deconvolving unrelated tumor datasets on bulk samples. Through the employment of scBeacon on the The Cancer Genome Atlas (TCGA) cohort, we find cellular and molecular attributes within specific tumor categories, many with patient outcome relevance. We developed a tumor cell-type map to visually depict the relationships among TCGA samples based on the cell-type inferences.

Quantitative susceptibility mapping (QSM) is an MRI modality used to non-invasively measure iron content in the brain. Iron exhibits a specific anatomically varying pattern of accumulation in the brain across individuals. The highest regions of accumulation are the deep grey nuclei, where iron is stored in paramagnetic molecule ferritin. This form of iron is considered to be what largely contributes to the signal measured by QSM in the deep grey nuclei. It is also known that QSM is affected by diamagnetic myelin contents. Here, we investigate spatial gene expression of iron and myelin related genes, as measured by the Allen Human Brain Atlas, in relation to QSM images of age-matched subjects. We performed multiple linear regressions between gene expression and the average QSM signal within 34 distinct deep grey nuclei regions. Our results show a positive correlation (p

In this study, we obtain an exact time-dependent solution of the chemical master equation (CME) of an extension of the two-state telegraph model describing bursty or non-bursty protein expression in the presence of positive or negative autoregulation. Using the method of spectral decomposition, we show that the eigenfunctions of the generating function solution of the CME are Heun functions, while the eigenvalues can be determined by solving a continued fraction equation. Our solution generalizes and corrects a previous time-dependent solution for the CME of a gene circuit describing non-bursty protein expression in the presence of negative autoregulation [Ramos et al., Phys. Rev. E 83, 062902 (2011)]. In particular, we clarify that the eigenvalues are generally not real as previously claimed. We also investigate the relationship between different types of dynamic behavior and the type of feedback, the protein burst size, and the gene switching rate. [ABSTRACT FROM AUTHOR]

Within the confines of a densely populated cell nucleus, chromatin undergoes intricate folding, forming loops, domains, and compartments under the governance of topological constraints and phase separation. This coordinated process inevitably introduces interference between different folding strategies. In this study, we model interphase chromatins as block copolymers with hetero-hierarchical loops within a confined system. Employing dissipative particle dynamics simulations and scaling analysis, we aim to explain how the structure and distribution of loop domains modulate the microphase separation of chromatins. Our results highlight the correlation between the microphase separation of the copolymer and the length, heterogeneity, and hierarchically nested levels of the loop domains. This correlation arises from steric repulsion intrinsic to loop domains. The steric repulsion induces variations in chain stiffness (including local orientation correlations and the persistence length), thereby influencing the degree of phase separation. Through simulations of block copolymers with distinct groups of hetero-hierarchical loop anchors, we successfully reproduce changes in phase separation across diverse cell lines, under fixed interaction parameters. These findings, in qualitative alignment with Hi-C data, suggest that the variations of loop constraints alone possess the capacity to regulate higher-order structures and the gene expressions of interphase chromatins. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the inhibitory effect of a PRG Barrier Coat on biofilm formation and structure by Streptococcus mutans and propose an effective method for preventing dental caries. Materials and Methods: Streptococcus mutans MT8148 biofilms were obtained from hydroxyapatite disks with and without a PRG Barrier Coat. Scanning electron microscopy (SEM) was used to observe the 12- and 24-h-cultured biofilms, while reverse-transcription polymerase chain reaction (qRT-PCR) was used to quantify caries-related genes. Biofilm adhesion assessments were performed on glass. Statistical analysis was performed using a two-sample t-test. Results: A statistically significant difference in Streptococcus mutans biofilm adhesion rate was observed between the control and PRG Barrier Coat-coated samples (p < 0.01). However, there was no statistically significant difference in total bacterial count or biofilm volume (p > 0.05). SEM revealed that the PRG Barrier Coat inhibited biofilm formation by Streptococcus mutans. Real-time RT-PCR revealed that the material restricted the expression of genes associated with caries-related biofilm formation. However, the suppression of gtfD and dexB differed from that of other genes. Conclusion: PRG Barrier Coat suppressed biofilm formation by Streptococcus mutans by inhibiting the expression of insoluble glucan synthase, which is associated with primary biofilm formation. The material also affected gene expression and altered the biofilm structure. Tooth surface-coating materials, such as PRG Barrier Coat, may improve caries prevention in dental practice. [ABSTRACT FROM AUTHOR]

Purpose: To screen for the cisplatin resistance-related prognostic signature in oral squamous cell carcinoma (OSCC) and assess its correlation with the immune microenvironment. Materials and Methods: The gene expression data associated with OSCC and cisplatin-resistance were downloaded from TCGA and GEO databases. Cisplatin-resistant genes were selected through taking the intersection of differentially expressed genes (DEGs) between tumor and control groups as well as between cisplatin-resistant samples and parental samples. Then, prognosis-related cisplatin-resistant genes were further selected by univariate Cox regression and LASSO regression analyses to construct a survival prognosis model. A GSEA (gene set enrichment analysis) between two risk groups was conducted with the MSigDB v7.1 database. Finally, the immune landscape of the sample was studied using CIBERSORT. The IC50 values of 57 drugs were predicted using pRRophetic 0.5. Results: A total 230 candidate genes were obtained. Then 7 drug-resistant genes were selected for prognostic risk-score (RS) signature construction using LASSO regression analysis, including STC2, TBC1D2, ADM, NDRG1, OLR1, PDGFA and ANO1. RS was an independent prognostic factor. Additionally, a nomogram model was established to predict the 1-, 2-, and 3-year survival rates of samples. The GSEA identified several differential pathways between two risk groups, such as EMT, hypoxia, and oxidative phosphorylation. Fifteen immune cells were statistically significantly different in infiltration level between the two groups, such as macrophages M2, and resting NK cells. A total of 57 drugs had statistically significantly different IC50 values between two risk groups. Conclusion: These model genes and immune cells may play a role in predicting the prognosis and chemoresistance in OSCC. [ABSTRACT FROM AUTHOR]

The classical three-stage model of stochastic gene expression predicts the statistics of single cell mRNA and protein number fluctuations as a function of the rates of promoter switching, transcription, translation, degradation and dilution. While this model is easily simulated, its analytical solution remains an unsolved problem. Here we modify this model to explicitly include cell-cycle dynamics and then derive an exact solution for the time-dependent joint distribution of mRNA and protein numbers. We show large differences between this model and the classical model which captures cell-cycle effects implicitly via effective first-order dilution reactions. In particular we find that the Fano factor of protein numbers calculated from a population snapshot measurement are underestimated by the classical model whereas the correlation between mRNA and protein can be either over- or underestimated, depending on the timescales of mRNA degradation and promoter switching relative to the mean cell-cycle duration time. [ABSTRACT FROM AUTHOR]

The presence of HIV in sequestered reservoirs is a central impediment to a functional cure, allowing HIV to persist despite life-long antiretroviral therapy (ART), and driving a variety of comorbid conditions. Our understanding of the latent HIV reservoir in the central nervous system is incomplete, because of difficulties in accessing human central nervous system tissues. Microglia contribute to HIV reservoirs, but the molecular phenotype of HIV-infected microglia is poorly understood. We leveraged the unique "Last Gift" rapid autopsy program, in which people with HIV are closely followed until days or even hours before death. Microglial populations were heterogeneous regarding their gene expression profiles but showed similar chromatin accessibility landscapes. Despite ART, we detected occasional microglia containing cell-associated HIV RNA and HIV DNA integrated into open regions of the host's genome (∼0.005%). Microglia with detectable HIV RNA showed an inflammatory phenotype. These results demonstrate a distinct myeloid cell reservoir in the brains of people with HIV despite suppressive ART. Strategies for curing HIV and neurocognitive impairment will need to consider the myeloid compartment to be successful.

Genes from ancient families are sometimes involved in the convergent evolutionary origins of similar traits, even across vast phylogenetic distances. Sulfotransferases are an ancient family of enzymes that transfer sulfate from a donor to a wide variety of substrates, including probable roles in some bioluminescence systems. Here, we demonstrate multiple sulfotransferases, highly expressed in light organs of the bioluminescent ostracod Vargula tsujii, transfer sulfate in vitro to the luciferin substrate, vargulin. We find luciferin sulfotransferases (LSTs) of ostracods are not orthologous to known LSTs of fireflies or sea pansies; animals with distinct and convergently evolved bioluminescence systems compared to ostracods. Therefore, distantly related sulfotransferases were independently recruited at least three times, leading to parallel evolution of luciferin metabolism in three highly diverged organisms. Reuse of homologous genes is surprising in these bioluminescence systems because the other components, including luciferins and luciferases, are completely distinct. Whether convergently evolved traits incorporate ancient genes with similar functions or instead use distinct, often newer, genes may be constrained by how many genetic solutions exist for a particular function. When fewer solutions exist, as in genetic sulfation of small molecules, evolution may be more constrained to use the same genes time and again.

Imaging scaffolds composed of designed protein cages fused to designed ankyrin repeat proteins (DARPins) have enabled the structure determination of small proteins by cryogenic electron microscopy (cryo-EM). One particularly well characterized scaffold type is a symmetric tetrahedral assembly composed of 24 subunits, 12 A and 12 B, which has three cargo-binding DARPins positioned on each vertex. Here, the X-ray crystal structure of a representative tetrahedral scaffold in the apo state is reported at 3.8 Å resolution. The X-ray crystal structure complements recent cryo-EM findings on a closely related scaffold, while also suggesting potential utility for crystallographic investigations. As observed in this crystal structure, one of the three DARPins, which serve as modular adaptors for binding diverse `cargo proteins, present on each of the vertices is oriented towards a large solvent channel. The crystal lattice is unusually porous, suggesting that it may be possible to soak crystals of the scaffold with small (≤30 kDa) protein cargo ligands and subsequently determine cage-cargo structures via X-ray crystallography. The results suggest the possibility that cryo-EM scaffolds may be repurposed for structure determination by X-ray crystallography, thus extending the utility of electron-microscopy scaffold designs for alternative structural biology applications.

In animal models, Nipbl deficiency phenocopies gene expression changes and birth defects seen in Cornelia de Lange syndrome, the most common cause of which is Nipbl haploinsufficiency. Previous studies in Nipbl+/- mice suggested that heart development is abnormal as soon as cardiogenic tissue is formed. To investigate this, we performed single-cell RNA sequencing on wild-type and Nipbl+/- mouse embryos at gastrulation and early cardiac crescent stages. Nipbl+/- embryos had fewer mesoderm cells than wild-type and altered proportions of mesodermal cell subpopulations. These findings were associated with underexpression of genes implicated in driving specific mesodermal lineages. In addition, Nanog was found to be overexpressed in all germ layers, and many gene expression changes observed in Nipbl+/- embryos could be attributed to Nanog overexpression. These findings establish a link between Nipbl deficiency, Nanog overexpression, and gene expression dysregulation/lineage misallocation, which ultimately manifest as birth defects in Nipbl+/- animals and Cornelia de Lange syndrome.

DNA deformability and differential hydration are crucial determinants of biological processes ranging from genetic material packaging to gene expression; their associative details, however, remain inadequately understood. Herein, we report investigations of the dynamic and thermodynamic responses of the local hydration of a variety of base pair sequences. Leveraging in silico sampling and our in-house analyses, we first report the local conformational propensity of sequences that are either predisposed toward the canonical A- or B-conformations or are restrained to potential transitory pathways. It is observed that the transition from the unrestrained A-form to the B-form leads to lengthwise structural deformation. The insertion of intermittent -(CG)- base pairs in otherwise homogeneous -(AT)- sequences bears dynamical consequences for the vicinal hydration layer. Calculation of the excess (pair) entropy suggests substantially higher values of hydration water surrounding A conformations over the B- conformations. Applying the Rosenfeld approximation, we project that the diffusivity of water molecules proximal to canonical B conformation is least for the minor groove of the canonical B-conformation. We determine that structure, composition, and conformation specific groove dimension together influence the local hydration characteristics and, therefore, are expected to be important determinants of biological processes. [ABSTRACT FROM AUTHOR]

A new in vitro system called Rec-Seq sheds light on how mRNA molecules compete for the machinery that translates their genetic sequence into proteins.

In some patients with myeloproliferative neoplasms (MPN), two genetic mutations are often found: JAK2 V617F and one in the TET2 gene. Whether one mutation is present influences how the other subsequent mutation will affect the regulation of gene expression. In other words, when a patient carries both mutations, the order of when they first arose has been shown to influence disease progression and prognosis. We propose a nonlinear ordinary differential equation, the Moran process, and Markov chain models to explain the non-additive and non-commutative mutation effects on recent clinical observations of gene expression patterns, proportions of cells with different mutations, and ages at diagnosis of MPN. Combined, these observations are used to shape our modeling framework. Our key proposal is that bistability in gene expression provides a natural explanation for many observed order-of-mutation effects. We also propose potential experimental measurements that can be used to confirm or refute predictions of our models.

A self-cleaving ribozyme that maps to an intron of the cytoplasmic polyadenylation element-binding protein 3 (Cpeb3) gene is thought to play a role in human episodic memory, but the underlying mechanisms mediating this effect are not known. We tested the activity of the murine sequence and found that the ribozymes self-scission half-life matches the time it takes an RNA polymerase to reach the immediate downstream exon, suggesting that the ribozyme-dependent intron cleavage is tuned to co-transcriptional splicing of the Cpeb3 mRNA. Our studies also reveal that the murine ribozyme modulates maturation of its harboring mRNA in both cultured cortical neurons and the hippocampus: inhibition of the ribozyme using an antisense oligonucleotide leads to increased CPEB3 protein expression, which enhances polyadenylation and translation of localized plasticity-related target mRNAs, and subsequently strengthens hippocampal-dependent long-term memory. These findings reveal a previously unknown role for self-cleaving ribozyme activity in regulating experience-induced co-transcriptional and local translational processes required for learning and memory.

Genome-wide association studies (GWASs) have uncovered susceptibility loci associated with psychiatric disorders such as bipolar disorder (BP) and schizophrenia (SCZ). However, most of these loci are in non-coding regions of the genome, and the causal mechanisms of the link between genetic variation and disease risk is unknown. Expression quantitative trait locus (eQTL) analysis of bulk tissue is a common approach used for deciphering underlying mechanisms, although this can obscure cell-type-specific signals and thus mask trait-relevant mechanisms. Although single-cell sequencing can be prohibitively expensive in large cohorts, computationally inferred cell-type proportions and cell-type gene expression estimates have the potential to overcome these problems and advance mechanistic studies. Using bulk RNA-seq from 1,730 samples derived from whole blood in a cohort ascertained from individuals with BP and SCZ, this study estimated cell-type proportions and their relation with disease status and medication. For each cell type, we found between 2,875 and 4,629 eGenes (genes with an associated eQTL), including 1,211 that are not found on the basis of bulk expression alone. We performed a colocalization test between cell-type eQTLs and various traits and identified hundreds of associations that occur between cell-type eQTLs and GWASs but that are not detected in bulk eQTLs. Finally, we investigated the effects of lithium use on the regulation of cell-type expression loci and found examples of genes that are differentially regulated according to lithium use. Our study suggests that applying computational methods to large bulk RNA-seq datasets of non-brain tissue can identify disease-relevant, cell-type-specific biology of psychiatric disorders and psychiatric medication.

Generalist microbes have adapted to a multitude of environmental stresses through their integrated stress response system. Individual stress responses have been quantified by E. coli metabolism and expression (ME) models under thermal, oxidative and acid stress, respectively. However, the systematic quantification of cross-stress & cross-talk among these stress responses remains lacking. Here, we present StressME: the unified stress response model of E. coli combining thermal (FoldME), oxidative (OxidizeME) and acid (AcidifyME) stress responses. StressME is the most up to date ME model for E. coli and it reproduces all published single-stress ME models. Additionally, it includes refined rate constants to improve prediction accuracy for wild-type and stress-evolved strains. StressME revealed certain optimal proteome allocation strategies associated with cross-stress and cross-talk responses. These stress-optimal proteomes were shaped by trade-offs between protective vs. metabolic enzymes; cytoplasmic vs. periplasmic chaperones; and expression of stress-specific proteins. As StressME is tuned to compute metabolic and gene expression responses under mild acid, oxidative, and thermal stresses, it is useful for engineering and health applications. The modular design of our open-source package also facilitates model expansion (e.g., to new stress mechanisms) by the computational biology community.

Small-molecule control of gene expression underlies the function of numerous engineered gene circuits that are capable of environmental sensing, computation, and memory. While many recently developed inducible promoters have been tailor-made for bacteria or mammalian cells, relatively few new systems have been built for Saccharomyces cerevisiae, limiting the scale of synthetic biology work that can be done in yeast. To address this, we created the yeast Tunable Expression Systems Toolkit (yTEST), which contains a set of five extensively characterized inducible promoter systems regulated by the small-molecules doxycycline (Dox), abscisic acid (ABA), danoprevir (DNV), 1-naphthaleneacetic acid (NAA), and 5-phenyl-indole-3-acetic acid (5-Ph-IAA). Assembly was made to be compatible with the modular cloning yeast toolkit (MoClo-YTK) to enhance the ease of use and provide a framework to benchmark and standardize each system. Using this approach, we built multiple systems with maximal expression levels greater than those of the strong constitutive TDH3 promoter. Furthermore, each of the five classes of systems could be induced at least 60-fold after a 6 h induction and the highest fold change observed was approximately 300. Thus, yTEST provides a reliable, diverse, and customizable set of inducible promoters to modulate gene expression in yeast for applications in synthetic biology, metabolic engineering, and basic research.

BACKGROUND: How novel phenotypes originate from conserved genes, processes, and tissues remains a major question in biology. Research that sets out to answer this question often focuses on the conserved genes and processes involved, an approach that explicitly excludes the impact of genetic elements that may be classified as clade-specific, even though many of these genes are known to be important for many novel, or clade-restricted, phenotypes. This is especially true for understudied phyla such as mollusks, where limited genomic and functional biology resources for members of this phylum have long hindered assessments of genetic homology and function. To address this gap, we constructed a chromosome-level genome for the gastropod Berghia stephanieae (Valdés, 2005) to investigate the expression of clade-specific genes across both novel and conserved tissue types in this species. RESULTS: The final assembled and filtered Berghia genome is comparable to other high-quality mollusk genomes in terms of size (1.05 Gb) and number of predicted genes (24,960 genes) and is highly contiguous. The proportion of upregulated, clade-specific genes varied across tissues, but with no clear trend between the proportion of clade-specific genes and the novelty of the tissue. However, more complex tissue like the brain had the highest total number of upregulated, clade-specific genes, though the ratio of upregulated clade-specific genes to the total number of upregulated genes was low. CONCLUSIONS: Our results, when combined with previous research on the impact of novel genes on phenotypic evolution, highlight the fact that the complexity of the novel tissue or behavior, the type of novelty, and the developmental timing of evolutionary modifications will all influence how novel and conserved genes interact to generate diversity.

BackgroundStatins lower circulating low-density lipoprotein cholesterol (LDLC) levels and reduce cardiovascular disease risk. Though highly efficacious in general, there is considerable inter-individual variation in statin efficacy that remains largely unexplained.MethodsTo identify novel genes that may modulate statin-induced LDLC lowering, we used RNA-sequencing data from 426 control- and 2 µM simvastatin-treated lymphoblastoid cell lines (LCLs) derived from European and African American ancestry participants of the Cholesterol and Pharmacogenetics (CAP) 40 mg/day 6-week simvastatin clinical trial (ClinicalTrials.gov Identifier: NCT00451828). We correlated statin-induced changes in LCL gene expression with plasma LDLC statin response in the corresponding CAP participants. For the most correlated gene identified (ZNF335), we followed up in vivo by comparing plasma cholesterol levels, lipoprotein profiles, and lipid statin response between wild-type mice and carriers of a hypomorphic (partial loss of function) missense mutation in Zfp335 (the mouse homolog of ZNF335).ResultsThe statin-induced expression changes of 147 human LCL genes were significantly correlated to the plasma LDLC statin responses of the corresponding CAP participants in vivo (FDR = 5%). The two genes with the strongest correlations were zinc finger protein 335 (ZNF335 aka NIF-1, rho = 0.237, FDR-adj p = 0.0085) and CCR4-NOT transcription complex subunit 3 (CNOT3, rho = 0.233, FDR-adj p = 0.0085). Chow-fed mice carrying a hypomorphic missense (R1092W; aka bloto) mutation in Zfp335 had significantly lower non-HDL cholesterol levels than wild-type C57BL/6J mice in a sex combined model (p = 0.04). Furthermore, male (but not female) mice carrying the Zfp335R1092W allele had significantly lower total and HDL cholesterol levels than wild-type mice. In a separate experiment, wild-type mice fed a control diet for 4 weeks and a matched simvastatin diet for an additional 4 weeks had significant statin-induced reductions in non-HDLC (-43 ± 18% and -23 ± 19% for males and females, respectively). Wild-type male (but not female) mice experienced significant reductions in plasma LDL particle concentrations, while male mice carrying Zfp335R1092W allele(s) exhibited a significantly blunted LDL statin response.ConclusionsOur in vitro and in vivo studies identified ZNF335 as a novel modulator of plasma cholesterol levels and statin response, suggesting that variation in ZNF335 activity could contribute to inter-individual differences in statin clinical efficacy.

Friedreichs ataxia is a neurodegenerative disorder caused by reduced frataxin levels. It leads to motor and sensory impairments and has a median life expectancy of around 35 years. As the most common inherited form of ataxia, Friedreichs ataxia lacks reliable, non-invasive biomarkers, prolonging and inflating the cost of clinical trials. This study proposes TUG1, a long non-coding RNA, as a promising blood-based biomarker for Friedreichs ataxia, which is known to regulate various cellular processes. In a previous study using a frataxin knockdown mouse model, we observed several hallmark Friedreichs ataxia symptoms. Building on this, we hypothesized that a dual-source approach-comparing the data from peripheral blood samples from Friedreichs ataxia patients with tissue samples from affected areas in Friedreichs ataxia knockdown mice, tissues usually unattainable from patients-would effectively identify robust biomarkers. A comprehensive reanalysis was conducted on gene expression data from 183 age- and sex-matched peripheral blood samples of Friedreichs ataxia patients, carriers and controls and 192 tissue data sets from Friedreichs ataxia knockdown mice. Blood and tissue samples underwent RNA isolation and quantitative reverse transcription polymerase chain reaction, and frataxin knockdown was confirmed through enzyme-linked immunosorbent assays. Tug1 RNA interaction was explored via RNA pull-down assays. Validation was performed in serum samples on an independent set of 45 controls and 45 Friedreichs ataxia patients and in blood samples from 66 heterozygous carriers and 72 Friedreichs ataxia patients. Tug1 and Slc40a1 emerged as potential blood-based biomarkers, confirmed in the Friedreichs ataxia knockdown mouse model (one-way ANOVA, P ≤ 0.05). Tug1 was consistently downregulated after Fxn knockdown and correlated strongly with Fxn levels (R 2 = 0.71 during depletion, R 2 = 0.74 during rescue). Slc40a1 showed a similar but tissue-specific pattern. Further validation of Tug1s downstream targets strengthened its biomarker candidacy. In additional human samples, TUG1 levels were significantly downregulated in both whole blood and serum of Friedreichs ataxia patients compared with controls (Wilcoxon signed-rank test, P < 0.05). Regression analyses revealed a negative correlation between TUG1 fold-change and disease onset (P < 0.0037) and positive correlations with disease duration and functional disability stage score (P < 0.04). This suggests that elevated TUG1 levels correlate with earlier onset and more severe cases. This study identifies TUG1 as a potential blood-based biomarker for Friedreichs ataxia, showing consistent expression variance in human and mouse tissues related to disease severity and key Friedreichs ataxia pathways. It correlates with frataxin levels, indicating its promise as an early, non-invasive marker. TUG1 holds potential for Friedreichs ataxia monitoring and therapeutic development, meriting additional research.

BackgroundStructural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence.ResultsWe present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies.ConclusionsThis SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.

Plant growth requires the integration of internal and external cues, perceived and transduced into a developmental programme of cell division, elongation and wall thickening. Mechanical forces contribute to this regulation, and thigmomorphogenesis typically includes reducing stem height, increasing stem diameter, and a canonical transcriptomic response. We present data on a bZIP transcription factor involved in this process in grasses. Brachypodium distachyon SECONDARY WALL INTERACTING bZIP (SWIZ) protein translocated into the nucleus following mechanostimulation. Classical touch-responsive genes were upregulated in B. distachyon roots following touch, including significant induction of the glycoside hydrolase 17 family, which may be unique to grass thigmomorphogenesis. SWIZ protein binding to an E-box variant in exons and introns was associated with immediate activation followed by repression of gene expression. SWIZ overexpression resulted in plants with reduced stem and root elongation. These data further define plant touch-responsive transcriptomics and physiology, offering insights into grass mechanotranduction dynamics.

Spatially resolved transcriptomics technologies have opened new avenues for understanding gene expression heterogeneity in spatial contexts. However, existing methods for identifying spatially variable genes often focus solely on statistical significance, limiting their ability to capture continuous expression patterns and integrate spot-level covariates. To address these challenges, we introduce spVC, a statistical method based on a generalized Poisson model. spVC seamlessly integrates constant and spatially varying effects of covariates, facilitating comprehensive exploration of gene expression variability and enhancing interpretability. Simulation and real data applications confirm spVC's accuracy in these tasks, highlighting its versatility in spatial transcriptomics analysis.

The ability to independently control gene expression in two different tissues in the same animal is emerging as a major need, especially in the context of inter-organ communication studies. This type of study is made possible by technologies combining the GAL4/UAS and a second binary expression system such as the LexA system or QF system. Here, we describe a resource of reagents that facilitate combined use of the GAL4/UAS and a second binary system in various Drosophila tissues. Focusing on genes with well-characterized GAL4 expression patterns, we generated a set of more than 40 LexA-GAD and QF2 insertions by CRISPR knock-in and verified their tissue specificity in larvae. We also built constructs that encode QF2 and LexA-GAD transcription factors in a single vector. Following successful integration of this construct into the fly genome, FLP/FRT recombination is used to isolate fly lines that express only QF2 or LexA-GAD. Finally, using new compatible shRNA vectors, we evaluated both LexA and QF systems for in vivo gene knockdown and are generating a library of such RNAi fly lines as a community resource. Together, these LexA and QF system vectors and fly lines will provide a new set of tools for researchers who need to activate or repress two different genes in an orthogonal manner in the same animal.

BackgroundGene expression may be regulated by the DNA methylation of regulatory elements in cis, distal, and trans regions. One method to evaluate the relationship between DNA methylation and gene expression is the mapping of expression quantitative trait methylation (eQTM) loci (also called expression associated CpG loci, eCpG). However, no open-source tools are available to provide eQTM mapping. In addition, eQTM mapping can involve a large number of comparisons which may prevent the analyses due to limitations of computational resources. Here, we describe Torch-eCpG, an open-source tool to perform eQTM mapping that includes an optimized implementation that can use the graphical processing unit (GPU) to reduce runtime.ResultsWe demonstrate the analyses using the tool are reproducible, up to 18 × faster using the GPU, and scale linearly with increasing methylation loci.ConclusionsTorch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg .

Aging and cellular senescence are increasingly recognized as key contributors to pulmonary fibrosis. However, our understanding in the context of scleroderma-associated interstitial lung disease (SSc-ILD) is limited. To investigate, we leveraged previously established lung aging- and cell-specific senescence signatures to determine their presence and potential relevance to SSc-ILD. We performed a gene expression meta-analysis of lung tissues from 38 SSc-ILD and 18 healthy controls and found that markers (GDF15, COMP, and CDKN2A) and pathways (p53) of senescence were significantly increased in SSc-ILD. When probing the established aging and cellular senescence signatures, we found that epithelial and fibroblast senescence signatures had a 3.6- and 3.7-fold enrichment, respectively, in the lung tissue of SSc-ILD and that lung aging genes (CDKN2A, FRZB, PDE1A, and NAPI12) were increased in SSc-ILD. These signatures were also enriched in SSc skin and associated with degree of skin involvement (limited vs. diffuse cutaneous). To further support these findings, we examined telomere length (TL), a surrogate for aging, in the lung tissue and found that, independent of age, SSc-ILD had significantly shorter telomeres than controls in type II alveolar cells in the lung. TL in SSc-ILD was comparable to idiopathic pulmonary fibrosis, a disease of known aberrant aging. Taken together, this study provides novel insight into the possible mechanistic effects of accelerated aging and aberrant cellular senescence in SSc-ILD pathogenesis.

Aging-related memory impairment and pathological memory disorders such as Alzheimers disease differ between males and females, and yet little is known about how aging-related changes in the transcriptome and chromatin environment differ between sexes in the hippocampus. To investigate this question, we compared the chromatin accessibility landscape and gene expression/alternative splicing pattern of young adult and aged mouse hippocampus in both males and females using ATAC-seq and RNA-seq. We detected significant aging-dependent changes in the expression of genes involved in immune response and synaptic function and aging-dependent changes in the alternative splicing of myelin sheath genes. We found significant sex-bias in the expression and alternative splicing of hundreds of genes, including aging-dependent female-biased expression of myelin sheath genes and aging-dependent male-biased expression of genes involved in synaptic function. Aging was associated with increased chromatin accessibility in both male and female hippocampus, especially in repetitive elements, and with an increase in LINE-1 transcription. We detected significant sex-bias in chromatin accessibility in both autosomes and the X chromosome, with male-biased accessibility enriched at promoters and CpG-rich regions. Sex differences in gene expression and chromatin accessibility were amplified with aging, findings that may shed light on sex differences in aging-related and pathological memory loss.

BackgroundCost-effective production of biofuels from lignocellulose requires the fermentation of D-xylose. Many yeast species within and closely related to the genera Spathaspora and Scheffersomyces (both of the order Serinales) natively assimilate and ferment xylose. Other species consume xylose inefficiently, leading to extracellular accumulation of xylitol. Xylitol excretion is thought to be due to the different cofactor requirements of the first two steps of xylose metabolism. Xylose reductase (XR) generally uses NADPH to reduce xylose to xylitol, while xylitol dehydrogenase (XDH) generally uses NAD+ to oxidize xylitol to xylulose, creating an imbalanced redox pathway. This imbalance is thought to be particularly consequential in hypoxic or anoxic environments.ResultsWe screened the growth of xylose-fermenting yeast species in high and moderate aeration and identified both ethanol producers and xylitol producers. Selected species were further characterized for their XR and XDH cofactor preferences by enzyme assays and gene expression patterns by RNA-Seq. Our data revealed that xylose metabolism is more redox balanced in some species, but it is strongly affected by oxygen levels. Under high aeration, most species switched from ethanol production to xylitol accumulation, despite the availability of ample oxygen to accept electrons from NADH. This switch was followed by decreases in enzyme activity and the expression of genes related to xylose metabolism, suggesting that bottlenecks in xylose fermentation are not always due to cofactor preferences. Finally, we expressed XYL genes from multiple Scheffersomyces species in a strain of Saccharomyces cerevisiae. Recombinant S. cerevisiae expressing XYL1 from Scheffersomyces xylosifermentans, which encodes an XR without a cofactor preference, showed improved anaerobic growth on xylose as the primary carbon source compared to S. cerevisiae strain expressing XYL genes from Scheffersomyces stipitis.ConclusionCollectively, our data do not support the hypothesis that xylitol accumulation occurs primarily due to differences in cofactor preferences between xylose reductase and xylitol dehydrogenase; instead, gene expression plays a major role in response to oxygen levels. We have also identified the yeast Sc. xylosifermentans as a potential source for genes that can be engineered into S. cerevisiae to improve xylose fermentation and biofuel production.

BACKGROUND: Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles. METHODS: The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses. RESULTS: Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires. CONCLUSIONS: Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Endogenous retroviruses (ERVs) are remnants of ancient parasitic infections and comprise sizable portions of most genomes. Although epigenetic mechanisms silence most ERVs by generating a repressive environment that prevents their expression (heterochromatin), little is known about mechanisms silencing ERVs residing in open regions of the genome (euchromatin). This is particularly important during embryonic development, where induction and repression of distinct classes of ERVs occur in short temporal windows. Here, we demonstrate that transcription-associated RNA degradation by the nuclear RNA exosome and Integrator is a regulatory mechanism that controls the productive transcription of most genes and many ERVs involved in preimplantation development. Disrupting nuclear RNA catabolism promotes dedifferentiation to a totipotent-like state characterized by defects in RNAPII elongation and decreased expression of long genes (gene-length asymmetry). Our results indicate that RNA catabolism is a core regulatory module of gene networks that safeguards RNAPII activity, ERV expression, cell identity, and developmental potency.

Anxiety disorders are among the most prevalent psychiatric disorders, causing significant suffering and disability. Relative to other psychiatric disorders, anxiety disorders tend to emerge early in life, supporting the importance of developmental mechanisms in their emergence and maintenance. Behavioral inhibition (BI) is a temperament that emerges early in life and, when stable and extreme, is linked to an increased risk for the later development of anxiety disorders and other stress-related psychopathology. Understanding the neural systems and molecular mechanisms underlying this dispositional risk could provide insight into treatment targets for anxiety disorders. Nonhuman primates (NHPs) have an anxiety-related temperament, called anxious temperament (AT), that is remarkably similar to BI in humans, facilitating the design of highly translational models for studying the early risk for stress-related psychopathology. Because of the recent evolutionary divergence between humans and NHPs, many of the anxiety-related brain regions that contribute to psychopathology are highly similar in terms of their structure and function, particularly with respect to the prefrontal cortex. The orbitofrontal cortex plays a critical role in the flexible encoding and regulation of threat responses, in part through connections with subcortical structures like the amygdala. Here, we explore individual differences in the transcriptional profile of cells within the region, using laser capture microdissection and single nuclear sequencing, providing insight into the molecules underlying individual differences in AT-related function of the pOFC, with a particular focus on previously implicated cellular systems, including neurotrophins and glucocorticoid signaling.

IntroductionThe regeneration of pulp tissue is crucial for true regenerative endodontic treatment, which requires a reduction in osteogenic differentiation. Garcinol, a histone acetyltransferase inhibitor, is a natural regulator that is known to suppress the osteogenic differentiation of dental pulp stem cells. In this study, the inhibitory effect of garcinol on the osteogenic differentiation of human dental pulp stem cells (hDPSCs) was evaluated using three-dimensional culture under in vitro and in vivo conditions.MethodshDPSCs were obtained from caries-free third molars and cultured with 10 μM garcinol for 7 days in an ultra-low attachment plate. The cell stemness and expression of osteogenic differentiation-related genes were analyzed using reverse transcription-polymerase chain reaction and single-cell analysis. A transplantation experiment was performed in mice to investigate whether garcinol-treated hDPSCs showed restrained osteogenic differentiation.ResultshDPSCs cultured in the U-shaped ultra-low attachment plate showed the highest expression of stemness-related genes. Garcinol-treated hDPSCs demonstrated downregulation of osteogenic differentiation, with lower expression of bone sialoprotein, which is related to bone formation, and higher expression of dentin sialophosphoprotein, which is related to dentin formation. However, the garcinol-treated hDPSCs did not show any alterations in their stemness. Consistent results were observed in the transplantation experiment in mice.ConclusionsGarcinol reduced the osteogenic differentiation of hDPSCs, which can contribute to true regenerative endodontic treatment.

Caenorhabditis elegans is a valuable model to study organ, tissue, and cell-type responses to external cues. However, the nematode comprises multiple syncytial tissues with spatial coordinates corresponding to distinct nuclear transcriptomes. Here, we present a single-nucleus RNA sequencing (snRNA-seq) protocol that aims to overcome difficulties encountered with single-cell RNA sequencing in C. elegans. We describe steps for isolating C. elegans nuclei for downstream applications including snRNA-seq applied to the context of alcohol exposure. For complete details on the use and execution of this protocol, please refer to Truong et al. (2023).1.

Dispatching rules are one of the most widely applied methods for solving Dynamic Job Shop Scheduling problems (DJSSP) in real-world manufacturing systems. Hence, the automated design of effective rules has been an important subject in the scheduling literature for the past several years. High computational requirements and difficulty in interpreting generated rules are limitations of literature methods. Also, feature selection approaches in the field of automated design of scheduling policies have been developed for the tree-based GP approach only. Therefore, the aim of this study is to propose a feature selection approach for the Gene Expression Programming (GEP) algorithm to evolve high-quality rules in simple structures with an affordable computational budget. This integration speeds up the search process by restricting the GP search space using the linear representation of the GEP algorithm and creates concise rules with only meaningful features using the feature selection approach. The proposed algorithm is compared with five algorithms and 30 rules from the literature under different processing conditions. Three performance measures are considered including total weighted tardiness, mean tardiness, and mean flow time. The results show that the proposed algorithm can generate smaller rules with high interpretability in a much shorter training time. [ABSTRACT FROM AUTHOR]

• Silent Alzheimer's disease impacts hypothalamus and hippocampus transcriptome. • AppNL-G-F mice show change in several biomarkers prior to cognitive decline. • Leptin levels are decreased during silent phase of Alzheimer's in AppNL-G-F mice. • Inflammatory mediators are increased during silent phase in AppNL-G-F mice. • Transcriptome changes during the silent phase persists during active disease phase. The progression of Alzheimer's disease (AD) has a silent phase that predates characteristic cognitive decline and eventually leads to active cognitive deficits. Metabolism, diet, and obesity have been correlated to the development of AD but is poorly understood. The hypothalamus is a brain region that exerts homeostatic control on food intake and metabolism and has been noted to be impacted during the active phase of Alzheimer's disease. This study, in using an amyloid overexpression AppNL-G-F mouse model under normal metabolic conditions, examines blood markers in young and old male AppNL-G-F mice (n = 5) that corresponds to the silent and active phases of AD, and bulk gene expression changes in the hypothalamus and the hippocampus. The results show a large panel of inflammatory mediators, leptin, and other proteins that may be involved in weakening the blood brain barrier, to be increased in the young AppNL-G-F mice but not in the old AppNL-G-F mice. There were also several differentially expressed genes in both the hypothalamus and the hippocampus in the young AppNL-G-F mice prior to amyloid plaque formation and cognitive decline that persisted in the old AppNL-G-F mice, including GABRa2 receptor, Wdfy1, and several pseudogenes with unknown function. These results suggests that a larger panel of inflammatory mediators may be used as blood markers to detect silent AD, and that a change in leptin and gene expression in the hypothalamus exist prior to cognitive effects, suggesting a coupling of metabolism with amyloid plaque induced cognitive decline. [ABSTRACT FROM AUTHOR]

AbstractBackgroundAimMethodsResultsConclusionEsophageal cancer is the eighth most common cause of cancer-related deaths worldwide. There are two main histological subtypes of esophageal cancer: adenocarcinoma and squamous cell carcinoma. Among the factors associated with the development of esophageal cancer, estrogen receptor beta (ERβ) has been found to have a clinical significance.To investigate the relationship between ERβ expression and esophageal cancer.English Medical literature searches were conducted for ERβ expression in patients with esophageal cancer versus healthy controls. Searches were performed up to August 31, 2023, using MEDLINE, PubMed, Embase and Google Scholar. Meta-analysis was performed by using Comprehensive meta-analysis software (Version 4, Biostat Inc., Englewood, NJ, USA). Pooled odds ratios (ORs) and 95% confidence intervals (95%CIs) were calculated. Heterogeneity was evaluated using Cochrane Q-test, and it was considered present if the Q-test P value was less than 0.10. I2 statistic was used to measure the proportion of inconsistency in individual studies, with I2 > 50% representing heterogeneity. We also calculated a potential publication bias.Ten studies representing 11 substudies were selected according to the inclusion criteria. The odds ratio of ERβ expression in fixed effect analysis was 0.448, 95% CI: 0.237 to 0.846, 55.2% lower in esophageal cancer than in normal mucosa. Heterogeneity and inconsistency were low, and no publication bias was demonstrated.This meta-analysis showed that ERβ expression is lower in esophageal cancer biopsy specimens than in healthy controls, this finding may have a significant effect on survival and can lead to new therapeutic avenues. [ABSTRACT FROM AUTHOR]

Background: Scopoletin and umbelliferone belong to coumarins, which are plant specialized metabolites with potent and wide biological activities, the accumulation of which is induced by various environmental stresses. Coumarins have been detected in various plant species, including medicinal plants and the model organism Arabidopsis thaliana. In recent years, key role of coumarins in maintaining iron (Fe) homeostasis in plants has been demonstrated, as well as their significant impact on the rhizosphere microbiome through exudates secreted into the soil environment. Several mechanisms underlying these processes require clarification. Previously, we demonstrated that Arabidopsis is an excellent model for studying genetic variation and molecular basis of coumarin accumulation in plants. Results: Here, through targeted metabolic profiling and gene expression analysis, the gene-metabolite network of scopoletin and umbelliferone accumulation was examined in more detail in selected Arabidopsis accessions (Col-0, Est-1, Tsu-1) undergoing different culture conditions and characterized by variation in coumarin content. The highest accumulation of coumarins was detected in roots grown in vitro liquid culture. The expression of 10 phenylpropanoid genes (4CL1, 4CL2, 4CL3, CCoAOMT1, C3'H, HCT, F6'H1, F6'H2,CCR1 and CCR2) was assessed by qPCR in three genetic backgrounds, cultured in vitro and in soil, and in two types of tissues (leaves and roots). We not only detected the expected variability in gene expression and coumarin accumulation among Arabidopsis accessions, but also found interesting polymorphisms in the coding sequences of the selected genes through in silico analysis and resequencing. Conclusions: To the best of our knowledge, this is the first study comparing accumulation of simple coumarins and expression of phenylpropanoid-related genes in Arabidopsis accessions grown in soil and in liquid cultures. The large variations we detected in the content of coumarins and gene expression are genetically determined, but also tissue and culture dependent. It is particularly important considering that growing plants in liquid media is a widely used technology that provides a large amount of root tissue suitable for metabolomics. Research on differential accumulation of coumarins and related gene expression will be useful in future studies aimed at better understanding the physiological role of coumarins in roots and the surrounding environments. [ABSTRACT FROM AUTHOR]

Aim Methodology Results Conclusion The aim of this study is to investigate the expression of inflammatory biomarkers (TNF‐α, IL‐10, IL‐1β) and the pulpitis‐associated miRNA (miR‐30a‐5p and miR‐128‐3p) in pulp tissue samples from unrestored teeth with a vital normal pulp (NP), teeth with symptomatic irreversible pulpitis (IP) and in unrestored teeth with periodontal disease, unresponsive to periodontal therapy, and a vital pulp (EP).Thirty patients were included in this observational study (10 teeth with NP, 10 teeth with IP, 10 teeth with EP). Dental pulp tissues samples were collected from patients during root canal treatment (RCT). RNA was extracted and qRT‐PCR of target genes (tumour necrosis factor [TNF]‐α, interleukin [IL]‐1β, IL‐10) and miRNAs (has‐miR‐30a‐5p, has‐miR‐128‐3p) performed to assess the expression profile. Fold‐change in expression was calculated using the formula 2−(ΔCt(Exp)−ΔCt(Ctrl)). One‐way anova with post‐hoc Tukey's was used to determine significant differences between groups. The significance level was set at 5% (p < .05). All teeth were also followed up clinically for 1 year and evaluated for a range of endodontic and periodontal‐related outcomes.All investigated genes significantly increased in expression and miRNAs significantly decreased in expression in the IP and EP groups compared with the NP group (p < .05). With regards to TNF‐α and IL‐1β there were no significant differences in expression between the IP and EP groups (p > .05), whereas IL‐10 expression levels were significantly reduced in the EP compared with the IP group (p < .05). Both miR‐30a‐5p and miR‐128‐3p showed significantly reduced expression in both IP and EP lesions, compared with NP (p < .05); however, no significant differences in miRNA expression were observed between IP and EP groups (p > .05). One year after root canal treatment and periodontal maintenance, tooth mobility and probing depth were significantly reduced in the EP group (p < .05).Pulp tissues from teeth with IP and EP presented similar levels of altered inflammatory markers compared with NP. TNF‐α, IL‐10, IL‐1β cytokines and miRNAs (miR‐30a‐5p and miR‐128‐3p) are potential objective biomarkers to indicate pulpal inflammatory status, aiding diagnosis and directing clinical decision‐making. RCT may be beneficial to improve stage III periodontitis unresponsive to non‐surgical periodontal treatment, but further research is required. [ABSTRACT FROM AUTHOR]

Phantom tooth pain (PTP) is one type of non-odontogenic neuropathic toothache, which rarely occurs after appropriate pulpectomy or tooth extraction. The cause of PTP is unknown. We investigated pain-related genetic factors that are associated with PTP. Four pain-associated genes, including G protein-coupled receptor 158 (GPR158) and phosphoribosyl transferase domain containing 1 (PRTFDC1), are adjacent to each other on the human genome. Some of these four genes or their genomic region may be related to PTP. We statistically analyzed associations between single-nucleotide polymorphisms (SNPs) in the genomic region and PTP in patients with PTP (PTP group), other orofacial pain (OFP group), and healthy control subjects. We then performed a database search of expression quantitative trait loci (eQTLs). For the seven SNPs that were significantly associated with PTP even after Bonferroni correction, we focused on the rs12411980 tag SNP (p = 9.42 × 10−4). Statistical analyses of the PTP group and healthy subject groups (group labels: NOC and TD) revealed that the rate of the GG genotype of the rs12411980 SNP was significantly higher in the PTP group than in the healthy subject groups (PTP group vs. NOC group: p = 2.92 × 10−4, PTP group vs. TD group: p = 5.46 × 10−4; percentage of GG: 30% in PTP group, 12% in NOC group, 11% in TD group). These results suggest that the GG genotype of the rs12411980 SNP is more susceptible to PTP. The rs2765697 SNP that is in strong linkage disequilibrium with the rs12411980 SNP is an eQTL that is associated with higher PRTFDC1 expression in the minor allele homozygotes in the healthy subject groups of the rs2765697 SNP. Thus, PRTFDC1 expression similarly increases in the minor allele homozygotes (GG genotype) in the healthy subject groups of the rs12411980 SNP, which would lead to greater susceptibility to PTP. [ABSTRACT FROM AUTHOR]

Introduction: This study presents a Mammalian Linear Expression System (MLES), a linear covalently closed (LCC) vector based on pVAX-1. The purpose of this system was to improve gene expression in mammalian cells and to test the efficacy of MLES in transient transfection and transgene expression using in vitro and in vivo models. Additionally, we aimed to evaluate potential inflammatory responses in vivo. Materials and methods: MLES was developed by modifying pVAX-1, and the construct was confirmed by gel electrophoresis. Lipofectamine®2000 was used to assess the transfection efficiency and expression of MLES in various cell lines. In vivo studies were conducted in mice injected with MLES/EGFP, and the resulting transfection efficiency, gene expression, and inflammatory responses were analyzed. Results: MLES exhibited higher transfection efficiency and expression levels compared to pVAX-1 when tested on HEK-293, CHO-K1, and NIH-3T3 cells. When tested in vivo, MLES/EGFP showed elevated expression in the heart, kidney, liver, and spleen compared with pVAX-1/EGFP. Minimal changes are observed in the lungs. Additionally, MLES induced a reduced inflammatory response in mice compared with pVAX-1/EGFP. Conclusions: MLES offer improved transfection efficiency and reduced inflammation, representing a significant advancement in gene therapy and recombinant protein production. Further research on MLES-mediated gene expression and immune modulation will enhance gene therapy strategies. [ABSTRACT FROM AUTHOR]

The early detection of cancer is of paramount importance in the medical field, as it can lead to more precise and effective interventions for successful cancer treatments. Cancer datasets typically contain numerous gene expression levels as features but with a limited number of samples. Thus, feature selection is a crucial initial step to streamline prediction algorithms. These selected features, or genes, play a pivotal role in cancer identification, treatment selection, and variation analysis among different techniques. To address this challenge, present two novel methodologies, by combining Cuckoo Search (CS) and Spider Monkey Optimization (SMO), referred to as SMOCS (Cuckoo Search followed by Spider Monkey Optimization) and CSSMO (Spider Monkey Optimization followed by Cuckoo Search). These approaches are designed for harnessing the strengths of both metaheuristic algorithms to identify a subset of genes that aid in early-stage cancer prediction. Additionally, to enhance the accuracy of the both algorithms, we employ a gene expression reduction method known as minimum Redundancy Maximum Relevance (mRMR) to reduce redundancy in cancer datasets. Subsequently, these gene subsets are classified using Deep Learning (DL) to identify distinct groups or classes associated with specific cancer types. We evaluate the performance of our proposed approaches using six different cancer datasets, assessing cancer sample classification and prediction through metrics such as Recall, Precision, F1-Score, and confusion matrix analysis. Our gene selection methods, in conjunction with DL, achieves significantly improved prediction accuracy when applied to large gene expression datasets compared to existing Deep Learning (DL) and Machine learning models. Experimental results shows that both SMOCS and CSSMO tend to classify cancer with high prediction accuracy, but SMOCS algorithm gives higher prediction accuracy for all the six datasets used with a maximum accuracy of 100%. [ABSTRACT FROM AUTHOR]