Expression Of Various Genes Research Articles

CXCL5/CXCL8 induces neutrophilic inflammation in peri-implantitis.

This research aimed to examine the role of C-X-C motif chemokine ligand 5 (CXCL5) and C-X-C motif chemokine ligand 8 (CXCL8; also known as IL-8) in neutrophilic inflammation triggered by peri-implantitis and to shed light on the underlying mechanisms that link them to the development of this condition. This study included 40 patients who visited the Department of Periodontology at Kyungpook University Dental Hospital. They were divided into two groups based on their condition: healthy implant (HI) group (n = 20) and peri-implantitis (PI) group (n = 20). Biopsy samples of PI tissue were collected from the patients under local anesthesia. HI tissue was obtained using the same method during the second implant surgery. To construct libraries for control and test RNAs, the QuantSeq 3' mRNA-Seq Library Prep Kit (Lexogen, Inc., Austria) was used according to the manufacturer's instructions. Samples were pooled based on representative cytokines obtained from RNA sequencing results and subjected to Reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Hematoxylin and eosin staining, and immunohistochemistry (IHC) analysis were performed to visually assess expression levels and analyze tissue histology. Student's t-test was employed to conduct statistical analyses. Initially, heatmaps were used to examine gene expression variations between the HI and PI groups based on the results of RNA sequencing. Notably, among various cytokines, CXCL5 and CXCL8 had the highest expression levels in the PI group compared with the HI group, and they are known to be associated with inflammatory responses. In the gingival tissues, the expression of genes encoding cytokines such as interleukin (IL)-1β, tumor necrosis factor-alpha (TNF)-α, interleukin (IL)-6, and CXCL5/CXCL8 was assessed via RT-qPCR. The mRNA expression level of CXCL5/CXCL8 significantly increased in the PI group compared with the HI group (p < .045). Contrarily, the mRNA expression level of interleukin 36 receptor antagonist (IL36RN) significantly decreased (p < .008). IHC enabled examination of the distribution and intensity of CXCL5/CXCL8 protein expression within the tissue samples. Specifically, increased levels of CXCL5/CXCL8 promote inflammatory responses, cellular proliferation, migration, and invasion within the peri-implant tissues. These effects are mediated through the activation of the PI3K/Akt/NF-κB signaling pathway. This study found that the PI sites had higher gene expression level of CXCL8/CXCL5 in the soft tissue than HI sites, which could help achieve more accurate diagnosis and treatment planning.

Abstract PO3-13-10: Proteogenomic characterization of primary invasive breast tumors from young women compared to matched tumors from older women

Abstract Introduction: Breast cancer (BC) in women &amp;lt; 40 years old accounts for ~5% of BC diagnosed in the U.S. However, young women have more aggressive tumors and worse outcomes, including higher rates of recurrence and lower disease-free and overall survival, compared to older women. To better understand mechanisms for these disparities, an integrated proteogenomic study of tumors from young (&amp;lt; 40) and older (≥ 60) women was performed through the Applied Proteogenomics OrganizationaL Learning and Outcomes (APOLLO) program. Methods: 34 pairs of retrospectively collected, untreated primary breast tumors from young and older women, matched by immunohistochemistry (IHC) subtype and race, were selected from the Clinical Breast Care Project. Median patient follow-up was 7 years. Tumor cells were enriched by laser microdissection and analyzed using RNA sequencing, whole genome sequencing, global proteomics, phosphoproteomics, and reverse phase protein array (RPPA). Molecular and clinical data from tumors from young and old patients in the TCGA-BC and METABRIC studies, matched by IHC subtype and race, were used to corroborate findings from our cohort. Results are presented comparing young women and their tumors to their older counterparts. Results: Young women have worse clinical outcome measured by progression-free interval. Despite matching for IHC subtypes, tumors from young women are enriched for intrinsic basal-like subtype, BRCA1/2 germline mutations, and had fewer invasive lobular BCs. Differentially enriched molecules and pathways: A number of significantly differentially expressed genes (DEGs) and proteins were detected, which were able to separate luminal subtypes of BC by patient age. IRS1 and IRS2 were enriched at both transcript and protein levels; IRS1 has been reported to promote tamoxifen resistance. We observed limited overlap of DEGs between the APOLLO, TCGA, and METABRIC datasets. In contrast, 14 of the 28 significantly upregulated Cancer Hallmark pathways were also enriched in TCGA-BC and METABRIC datasets; suggesting targeting pathways, vs genes, may be more effective for therapeutic intervention. Integrated pathway/network analysis: Integrated pathway analysis of RNA and protein levels identified 5 Hallmark pathways upregulated in younger women, including ER response and proliferative pathways, and 6 downregulated immune-response pathways; 10 of the 11 were supported by the public datasets. Immune scores were also lower. Kinase substrate enrichment analysis identified 4 kinases with increased activity in tumors from young women. ESR1/ER: We identified for the first time a significant reduction of ER protein expression while confirming previously reported lower ESR1 gene expression and copy number variations. Surprisingly, integrated pathway analysis identified elevation of early and late estrogen responses in young women. ER activation, indicated by phosphorylated ER (pS118) normalized to total ER protein, was elevated in LumA tumors from young women. Conclusions: This first-ever integrated proteogenomic study shows that BC in young women is enriched for more aggressive molecular subtypes and for genes that promote tamoxifen resistance, exhibits lower immune pathways and immune scores, and shows enhanced ER responses despite lower gene and protein expression of ER. These findings may contribute to the understanding of the molecular mechanisms underlying worse outcomes of BC in young women, and offer new insight to therapeutic strategies. Disclaimer: The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions or policies of USUHS, HJF, the DoD or the Departments of the Army, Navy or Air Force. Mention of trade names, commercial products, or organizations does not imply endorsement by the U.S. Government. Citation Format: Praveen Kumar Raj Kumar, Jianfang Liu, Anthony Soltis, Nicholas Bateman, Qingrong Chen, Lori Sturtz, Brenda Deyarmin, Mariaelena Pierobon, Tamara Abulez, Anupama Praveen-Kumar, Xijun Zhang, Trinh Nguyen, Chunhua Yan, Ying Hu, Kate Guion, Jeffrey Hooke, Albert Kovatich, Leigh Fantacone-Campbell, Brad Mostoller, Leonid Kvecher, Stella Somiari, Patricia Steeg, Sheila Rajagopal, Kathleen Darcy, Jerry Lee, Clifton Dalgard, Thomas Conrads, Emanuel Petricoin, Daoud Meerzaman, Matthew Wilkerson, APOLLO Research Network, Xiaoying Lin, Craig Shriver, Stanley Lipkowitz, Hai Hu. Proteogenomic characterization of primary invasive breast tumors from young women compared to matched tumors from older women [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-13-10.

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

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

Bioactivity and antibacterial effects of zinc-containing bioactive glass on the surface of zirconia abutments

ObjectivesThis study aimed to enhance gingival fibroblast function and to achieve antibacterial activity around the implant abutment by using a zinc (Zn)-containing bioactive glass (BG) coating. Methods45S5 BG containing 0, 5, and 10 wt.% Zn were coated on zirconia disks. The release of silica and Zn ions in physiological saline and their antibacterial effects were measured. The effects of BG coatings on human gingival fibroblasts (hGFs) were assessed using cytotoxicity assays and by analyzing the gene expression of various genes related to antioxidant enzymes, wound healing, and fibrosis. ResultsBG coatings are capable of continuous degradation and simultaneous ion release. The antibacterial effect of BG coatings increased with the addition of Zn, while the cytotoxicity remained unchanged compared to the group without coatings. BG coating enhances the expression of angiogenesis genes, while the Zn-containing BG enhances the expression of antioxidant genes at an early time point. BG coating enhances the expression of collagen genes at later time points. ConclusionsThe antibacterial effect of BG improved with the increase in Zn concentration, without inducing cytotoxicity. BG coating enhances the expression of angiogenesis genes, and Zn-containing BG enhances the expression of antioxidant genes at an early time point. BG coating enhances the expression of collagen genes at later time points. Clinical SignificanceAdding 10 wt% Zn to BG could enhance the environment around implant abutments by providing antibacterial, antioxidant, and anti-fibrotic effects, having potential for clinical use.

Timing of acute cold exposure determines thermoregulatory responses - possible interactions between the thermal environment and circadian clocks

Introduction: Shift workers are frequently exposed to the harsh combination of night work in a low-temperature environment. In this project, we aimed to determine if acute induction of thermoregulatory markers UCP1 and FGF21 by cold exposure depend on the timing of the exposure, and to investigate if the neural processing of thermal information has a potential role. Methods: Six groups of C57BI/J6 mice (N=8) were habituated for 2 months to a 12 h light/ 12 h dark regiment at thermoneutral temperature 27 °C (TN). After this period, groups were acutely exposed to an ambient temperature of 15 °C (COLD) or a continuation of TN temperature. Temperature exposures of groups were applied at three different time-points of the day lasting for 8 hours before tissues were harvested at ZT4, ZT12 or ZT20 (i.e. 4, 12 or 20 hours after the light is on, respectively). Thermoregulatory markers were measured in plasma, brown adipose tissue (BAT), liver and the peripheral somatosensory neurons in dorsal root ganglion (DRG) using RTPCR and immunodetection. Furthermore, behaviour testing was used to evaluate thermal preference. Results: UCP1 expression increased in BAT from COLD mice, as compared to TN mice. A higher induction of UCP1 was observed at ZT12 than the other time points. Plasma levels of FGF21 were induced acutely in COLD mice at ZT4 and ZT12, compared to the time-matched TN controls, but COLD mice at ZT20 did not display increase of FGF21 plasma levels. Cold exposure affected mRNA expression patterns of core circadian clock components in BAT (Bmal1, Clock, Per1/2/3, Cry1/2, Nr1d1/2), but in liver these transcripts were not affected. Behavior testing showed that COLD mice developed cold tolerance behaviors at ZT4 but less at ZT12. Analyses of gene expression in the somatosensory DRG neurons revealed circadian oscillations of core components and gene regulation due to cold exposure. Summary: In a nutshell, data suggest that the timing of cold exposure might impact physiological and behavioural adaptations to cold environments. This was associated with diurnal variations of gene expression in DRG neurons. Supported with an internal grant at STAMI. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Discrete placental gene expression signatures accompany diabetic disease classifications during pregnancy

Gestational diabetes mellitus (GDM) affects up to 10% of pregnancies and is classified into subtypes GDMA1 (managed by lifestyle modifications) and GDMA2 (requiring medication). However, whether these subtypes are distinct clinical entities or more reflective of an extended spectrum of normal pregnancy endocrine physiology remains unclear. Integrated bulk RNA-sequencing (RNA-seq), single-cell RNA-sequencing (scRNA-seq), and spatial transcriptomics harbors the potential to reveal disease gene signatures in subsets of cells and tissue microenvironments. We aimed to combine these high-resolution technologies with rigorous classification of diabetes subtypes in pregnancy. We hypothesized that differences between pre-existing Type 2 and gestational diabetes subtypes would be associated with altered gene expression profiles in specific placental cell populations. In a large case-cohort design, we compared validated cases of GDMA1, GDMA2, and type 2 diabetes (T2DM) to healthy controls by bulk RNA-seq (n=54). Quantitative analyses with RT-qPCR of presumptive genes of significant interest were undertaken in an independent and non-overlapping validation cohort of similarly well-characterized cases and controls (n=122). Additional integrated analyses of term placental single-cell, single-nuclei, and spatial transcriptomics data enabled us to determine the cellular subpopulations and niches that aligned with the GDMA1, GDMA2, and T2DM gene expression signatures at higher resolution and with greater confidence. Dimensional reduction of the bulk RNA-seq data revealed that the most common source of placental gene expression variation was the diabetic disease subtype. Relative to controls, we found 2,052 unique and significantly differentially expressed genes (-2<Log2(fold-change)>2 thresholds; q<0.05 Wald Test) among GDMA1 placental specimens, 267 among GDMA2, and 1,520 among T2DM. Several candidate marker genes (CSH1, PER1, PIK3CB, FOXO1, EGFR, IL2RB, SOD3, DOCK5, and SOGA1) were validated in an independent and non-overlapping validation cohort (q<0.05 Tukey). Functional enrichment revealed the pathways and genes most impacted for each diabetes subtype, and the degree of proximal similarity to other subclassifications. Surprisingly, GDMA1 and T2DM placental signatures were more alike by virtue of increased expression of chromatin remodeling and epigenetic regulation genes, while albumin was the top marker for GDMA2 with increased expression of placental genes in the wound healing pathway. Assessment of these gene signatures in single-cell, single-nuclei, and spatial transcriptomics data revealed high specificity and variability by placental cell and microarchitecture types. For example, at the cellular and spatial (e.g., microarchitectural) levels, distinguishing features were observed in extravillous trophoblasts (GDMA1) and macrophages (GDMA2). Lastly, we utilized these data to train and evaluate four machine learning models to estimate our confidence in predicting the control or diabetes status of placental transcriptome specimens with no available clinical metadata. Consistent with the distinct association of perinatal outcome risk, placentae from GDMA1, GDMA2, and T2DM-affected pregnancies harbor unique gene signatures that can be further distinguished by altered placental cellular subtypes and microarchitectural niches.

Predicting Cell Type-Specific Extracellular Vesicle Biology Using an Organism-Wide Single Cell Transcriptomic Atlas - Insights from the Tabula Muris

Background: Extracellular vesicles (EVs) like exosomes are functional nanoparticles traffcked between cells and found in every biofluid. An incomplete understanding of which cells, from which tissues, are traffcking EVs in vivo has limited our ability to use EVs as biomarkers and therapeutics. However, recent discoveries have linked EV secretion to expression of genes and proteins responsible for EV biogenesis and found as cargo, which suggests that emerging “cell atlas” datasets could be used to begin understanding EV biology at the level of the organism and possibly in rare cell populations. To explore this possibility, here we analyzed 67 genes that are directly implicated in EV biogenesis and secretion, or carried as cargo, in ~44,000 cells obtained from 117 cell populations of the Tabula Muris. Methods: We obtained normalized count (FPKM) data from 44,779 FACS-sorted cells described in the Tabula Muris. These data were freely obtained from the Tabula Muris web portal operated by the Chan-Zuckerberg Biohub. We selected 67 EV genes based on their direct role in the regulation of endosome biogenesis, protein sorting, secretion or cargo. These genes include the endosome sorting complexes required for transport (ESCRT), multiple Rab GTPases, tetraspanins and syndecans. To identify the most abundant EV genes, we plotted mean expression (FPKM) across all cells against the fraction of cells with gene expression &gt; 50 FPKM. To measure gene expression variance, we calculated %CV for each gene within each cell population and across all cell populations. For gene co-expression analysis, we performed linear regressions comparing selected EV genes (Cd9, Cd63, Cd81, Sdc4 and Sdcbp) to all other genes, within each cell population. Results: We found that the most abundant EV cargo proteins (tetraspanins (Cd9, Cd63 and Cd81) and syndecans (Sdc4 and Sdcbp)) are also the most abundant EV genes expressed across all cell populations. However, the expression of these genes varied greatly among cell populations. For example, Cd81 is most abundant in brain glial populations and multiple endothelial cell populations. By contrast, Cd9 expression is highest in "barrier" cells that support innate immunity while Cd63, a classic marker of exosomes, is most abundantly expressed by stem cells. Expression variance analysis was used to compare the transcriptional behavior of these abundant EV genes (Cd9, Cd63, Cd81, Sdc4 and Sdcbp). We found that Cd63 is the most dynamic EV gene while others are more constitutively expressed. This finding may help explain why Cd63 is typically found either within the cytoplasm or outside of the cell on EVs, whereas Cd9 and Cd81 are abundant both on the cell surface and on EVs. Finally, we used EV gene co-expression analysis to define cell population-specific transcriptional networks. We discovered that EV gene co-expression networks are heavily dependent on the EV cargo gene examined with different cell populations driving clustering. Conclusions: Our analysis has provided at least four independent observations which advance our understanding of EV biology. These are that: 1) abundant EV cargo genes are differentially expressed among cell populations, 2) skeletal muscle stem cells display the highest expression of both Cd63 and Sdc4, 3) Cd81 may be a primary EV cargo traffcked in the brain whiand 4) that rare cell populations can secrete EVs and thereby influence tissue biology. This analysis is the first, to our knowledge, to predict tissue- and cell type-specific EV biology at the level of the organism. As such, we expect this resource to be the first of many valuable tools for predicting the endogenous impact of specific cell populations on EV function in health and disease. National Institutes on Aging (R01AG078859). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Subacromial bursa in patients with rotator cuff tear with or without adhesive capsulitis exhibits a differential transcriptome with potential molecular biomarkers

BackgroundAlthough adhesive capsulitis (AC) is a common condition, the pathological mechanisms remain understudied. The purpose of our research was to evaluate variations in gene expression across the entire genome in the subacromial bursa tissue of individuals with rotator cuff tears (RCT), with or without AC, and to explore the factors that may influence the occurrence and progression of AC. MethodsTranscription profiles of subacromial bursa samples from 12 RCT patients, of whom 6 had also AC, were evaluated. Data were generated using RNA-seq. DESeq2 was utilized to identify the differentially expressed genes (DEGs) in both groups. In order to conduct a more in-depth examination of the DEGs, we performed Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A network of interactions between proteins was built, and the central genes were determined using Cytoscape. The hub genes were confirmed through qRT-PCR and immunohistochemistry. Results324 of the 16,251 detected genes were identified as DEGs. Analysis of GO functional enrichment showed that the DEGs were enriched in domains of biological process, molecule function and cellular component. Analysis of KEGG pathways revealed enrichment of DEGs in pathways like IL-17 signaling and ECM-receptor interaction. We verified that the association between AC and the increase in expression of the PPI network hub genes. ConclusionThis study investigated the transcriptome differences of subacromial bursa in RCT patients with or without AC. Using bioinformatics technology, we identified the DEGs and screened out the hub genes. The research enhanced the data on gene expression profiles of DEGs in the subacromial bursa tissue of patients with RCT, offering fresh perspectives on the regulation of gene transcription.

Revealing gene expression heterogeneity in a clonal population of Tetrahymena thermophila through single-cell RNA sequencing

We performed single-cell RNA sequencing (scRNA-seq) on a population of 5,000 Tetrahymena thermophila, using the 10x Genomics 3′ gene expression analysis, to investigate gene expression variability within this clonal population. Initially, we estimated the 3ʹ-untranslated regions (3′ UTRs), which were absent in existing annotation files but are crucial for the 10x Genomics 3′ gene expression analysis, using the peaks2utr method. This allowed us to create a modified annotation file, which was then utilized in our scRNA-seq analysis. Our analysis revealed significant gene expression variability within the population, even after removing the effect of cell phase-related features. This variability predominantly appeared in six distinct clusters. Through gene ontology and KEGG pathway enrichment analyses, we identified that these were primarily associated with ribosomal proteins, proteins specific to mitochondria, proteins involved in peroxisome-specific carbon metabolism, cytoskeletal proteins, motor proteins, and immobilized antigens.

Sequence basis of transcription initiation in the human genome.

Transcription initiation is a process that is essential to ensuring the proper function of any gene, yet we still lack a unified understanding of sequence patterns and rules that explain most transcription start sites in the human genome. By predicting transcription initiation at base-pair resolution from sequences with a deep learning-inspired explainable model called Puffin, we show that a small set of simple rules can explain transcription initiation at most human promoters. We identify key sequence patterns that contribute to human promoter activity, each activating transcription with distinct position-specific effects. Furthermore, we explain the sequence basis of bidirectional transcription at promoters, identify the links between promoter sequence and gene expression variation across cell types, and explore the conservation of sequence determinants of transcription initiation across mammalian species.

Transcriptional variations at perilesional site in vitiligo patients: probably a fight for cell-survival.

Exploration of gene expression variations is a potential source to unravel biological pathways involved in pathological changes in body and understand the mechanism underneath. Vitiligo patients were explored for gene expression changes transcriptionally at perilesional site in comparison to normal site of same patients for melanogenesis pathway (TYR, DCT & TYRP1) cell adhesion (MMPs & TIMP1), cell survival (BCL2 & BAX1) as well as proliferation, migration & development (SOX9, SOX10 & MITF) regulatory system, using skin biopsy samples. Results were also compared with changes in gene expression for melanocytes under stress after hydrogen peroxide treatment in-vitro. Gene amplification was carried out via real time PCR. We found increased expression of proliferation, migration & development regulatory genes as well as melanogenesis pathway genes at perilesional site of patients. In-vitro study also supports induced MITF expression and disturbed melanogenesis in melanocytes under stress. Expression level ratio of cell survival regulatory genes' (BCL2/BAX1) as well as cell adhesion regulatory genes (MMPs/TIMP1) was observed upregulated at patient's perilesional site however downregulated in hydrogen peroxide treated melanocytes in-vitro. Observed upregulated gene expression at perilesional site of patients may be via positive feedback loop in response to stress to increase cell tolerance power to survive against adverse conditions. Gene expression analysis suggests better cell survival and proliferation potential at perilesional site in vitiligo patients. It seems in-vivo conditions/growth factors supports cells to fight for survival to accommodate stressed conditions.

Unraveling the molecular basis of cannabidiolic acid methyl Ester's anti-depressive effects in a rat model of treatment-resistant depression

Major depressive disorder (MDD) stands as a significant cause of disability globally. Cannabidiolic Acid-Methyl Ester (CBDA-ME) (EPM-301, HU-580), a derivative of Cannabidiol, demonstrates immediate antidepressant-like effects, yet it has undergone only minimal evaluation in psychopharmacology. Our goal was to investigate the behavioral and potential molecular mechanisms associated with the chronic oral administration of this compound in the Wistar Kyoto (WKY) genetic model of treatment-resistant depression. Male WKY rats were subjected to behavioral assessments before and after receiving chronic (14-day) oral doses of CBDA-ME (0.5 mg/kg), 15 mg/kg of imipramine or vehicle. At the end of the study, plasma corticosterone levels and mRNA expression of various genes in the medial Prefrontal Cortex and Hippocampus were measured. Behavioral outcomes from CBDA-ME treatment indicated an antidepressant-like effect similar to imipramine, as oral ingestion reduced immobility and increased swimming duration in the Forced Swim Test. Neither treatment influenced locomotion in the Open Field Test nor preference in the Saccharin Preference Test. The behavioral impact in WKY rats coincided with reduced corticosterone serum levels, upregulated mRNA expression of Cannabinoid receptor 1, Fatty Acid Amide Hydrolase, and Corticotropin-Releasing Hormone Receptor 1, alongside downregulation of the Serotonin Transporter in the hippocampus. Additionally, there was an upregulation of CB1 mRNA expression and downregulation of Brain-Derived Neurotrophic Factor in the mPFC. These findings contribute to our limited understanding of the antidepressant effects of CBDA-ME and shed light on its potential psychopharmacological mechanisms. This discovery opens up possibilities for utilizing cannabinoids in the treatment of major depressive disorder and related conditions.

Unraveling the dynamic transcriptomic changes during the dimorphic transition of Talaromyces marneffei through time-course analysis.

Systemic dimorphic fungi pose a significant public health challenge, causing over one million new infections annually. The dimorphic transition between saprophytic mycelia and pathogenic yeasts is strongly associated with the pathogenesis of dimorphic fungi. However, despite the dynamic nature of dimorphic transition, the current omics studies focused on dimorphic transition primarily employ static strategies, partly due to the lack of suitable dynamic analytical methods. We conducted time-course transcriptional profiling during the dimorphic transition of Talaromyces marneffei, a model organism for thermally dimorphic fungi. To capture non-uniform and nonlinear transcriptional changes, we developed DyGAM-NS (dynamic optimized generalized additive model with natural cubic smoothing). The performance of DyGAM-NS was evaluated by comparison with seven other commonly used time-course analysis methods. Based on dimorphic transition induced genes (DTIGs) identified by DyGAM-NS, cluster analysis was utilized to discern distinct gene expression patterns throughout dimorphic transitions of T. marneffei. Simultaneously, a gene expression regulatory network was constructed to probe pivotal regulatory elements governing the dimorphic transitions. By using DyGAM-NS, model, we identified 5,223 DTIGs of T. marneffei. Notably, the DyGAM-NS model showcases performance on par with or superior to other commonly used models, achieving the highest F1 score in our assessment. Moreover, the DyGAM-NS model also demonstrates potential in predicting gene expression levels throughout temporal processes. The cluster analysis of DTIGs suggests divergent gene expression patterns between mycelium-to-yeast and yeast-to-mycelium transitions, indicating the asymmetrical nature of two transition directions. Additionally, leveraging the identified DTIGs, we constructed a regulatory network for the dimorphic transition and identified two zinc finger-containing transcription factors that potentially regulate dimorphic transition in T. marneffei. Our study elucidates the dynamic transcriptional profile changes during the dimorphic transition of T. marneffei. Furthermore, it offers a novel perspective for unraveling the underlying mechanisms of fungal dimorphism, emphasizing the importance of dynamic analytical methods in understanding complex biological processes.

Polymeric Caffeic Acid Acts as an Antigen Delivery Carrier for Mucosal Vaccine Formulation by Forming a Complex with an Antigenic Protein.

The development of mucosal vaccines, which can generate antigen-specific immune responses in both the systemic and mucosal compartments, has been recognized as an effective strategy for combating infectious diseases caused by pathogenic microbes. Our recent research has focused on creating a nasal vaccine system in mice using enzymatically polymerized caffeic acid (pCA). However, we do not yet understand the molecular mechanisms by which pCA stimulates antigen-specific mucosal immune responses. In this study, we hypothesized that pCA might activate mucosal immunity at the site of administration based on our previous findings that pCA possesses immune-activating properties. However, contrary to our initial hypothesis, the intranasal administration of pCA did not enhance the expression of various genes involved in mucosal immune responses, including the enhancement of IgA responses. Therefore, we investigated whether pCA forms a complex with antigenic proteins and enhances antigen delivery to mucosal dendritic cells located in the lamina propria beneath the mucosal epithelial layer. Data from gel filtration chromatography indicated that pCA forms a complex with the antigenic protein ovalbumin (OVA). Furthermore, we examined the promotion of OVA delivery to nasal mucosal dendritic cells (mDCs) after the intranasal administration of pCA in combination with OVA and found that OVA uptake by mDCs was increased. Therefore, the data from gel filtration chromatography and flow cytometry imply that pCA enhances antigen-specific antibody production in both mucosal and systemic compartments by serving as an antigen-delivery vehicle.

A Principal Components Analysis and Functional Annotation of Differentially Expressed Genes in Brain Regions of Gray Rats Selected for Tame or Aggressive Behavior.

The process of domestication, despite its short duration as it compared with the time scale of the natural evolutionary process, has caused rapid and substantial changes in the phenotype of domestic animal species. Nonetheless, the genetic mechanisms underlying these changes remain poorly understood. The present study deals with an analysis of the transcriptomes from four brain regions of gray rats (Rattus norvegicus), serving as an experimental model object of domestication. We compared gene expression profiles in the hypothalamus, hippocampus, periaqueductal gray matter, and the midbrain tegmental region between tame domesticated and aggressive gray rats and revealed subdivisions of differentially expressed genes by principal components analysis that explain the main part of differentially gene expression variance. Functional analysis (in the DAVID (Database for Annotation, Visualization and Integrated Discovery) Bioinformatics Resources database) of the differentially expressed genes allowed us to identify and describe the key biological processes that can participate in the formation of the different behavioral patterns seen in the two groups of gray rats. Using the STRING- DB (search tool for recurring instances of neighboring genes) web service, we built a gene association network. The genes engaged in broad network interactions have been identified. Our study offers data on the genes whose expression levels change in response to artificial selection for behavior during animal domestication.

Modification of Seurat v4 for the Development of a Phase Assignment Tool Able to Distinguish between G2 and Mitotic Cells.

Single-cell RNA sequencing (scRNAseq) is a rapidly advancing field enabling the characterisation of heterogeneous gene expression profiles within a population. The cell cycle phase is a major contributor to gene expression variance between cells and computational analysis tools have been developed to assign cell cycle phases to cells within scRNAseq datasets. Whilst these tools can be extremely useful, all have the drawback that they classify cells as only G1, S or G2/M. Existing discrete cell phase assignment tools are unable to differentiate between G2 and M and continuous-phase-assignment tools are unable to identify a region corresponding specifically to mitosis in a pseudo-timeline for continuous assignment along the cell cycle. In this study, bulk RNA sequencing was used to identify differentially expressed genes between mitotic and interphase cells isolated based on phospho-histone H3 expression using fluorescence-activated cell sorting. These gene lists were used to develop a methodology which can distinguish G2 and M phase cells in scRNAseq datasets. The phase assignment tools present in Seurat were modified to allow for cell cycle phase assignment of all stages of the cell cycle to identify a mitotic-specific cell population.

Revealing the Complete Bispecific Phosphatase Genes (DUSPs) across the Genome and Investigating the Expression Patterns of GH_A11G3500 Resistance against Verticillium wilt.

DUSPs, a diverse group of protein phosphatases, play a pivotal role in orchestrating cellular growth and development through intricate signaling pathways. Notably, they actively participate in the MAPK pathway, which governs crucial aspects of plant physiology, including growth regulation, disease resistance, pest resistance, and stress response. DUSP is a key enzyme, and it is the enzyme that limits the rate of cell metabolism. At present, complete understanding of the DUSP gene family in cotton and its specific roles in resistance to Verticillium wilt (VW) remains elusive. To address this knowledge gap, we conducted a comprehensive identification and analysis of four key cotton species: Gossypium arboreum, Gossypium barbadense, Gossypium hirsutum, and Gossypium raimondii. The results revealed the identification of a total of 120 DUSP genes in the four cotton varieties, which were categorized into six subgroups and randomly distributed at both ends of 26 chromosomes, predominantly localized within the nucleus. Our analysis demonstrated that closely related DUSP genes exhibited similarities in terms of the conserved motif composition and gene structure. A promoter analysis performed on the GhDUSP gene promoter revealed the presence of several cis-acting elements, which are associated with abiotic and biotic stress responses, as well as hormone signaling. A tissue expression pattern analysis demonstrated significant variations in GhDUSP gene expression under different stress conditions, with roots exhibiting the highest levels, followed by stems and leaves. In terms of tissue-specific detection, petals, leaves, stems, stamens, and receptacles exhibited higher expression levels of the GhDUSP gene. The gene expression analysis results for GhDUSPs under stress suggest that DUSP genes may have a crucial role in the cotton response to stress in cotton. Through Virus-Induced Gene Silencing (VIGS) experiments, the silencing of the target gene significantly reduced the resistance efficiency of disease-resistant varieties against Verticillium wilt (VW). Consequently, we conclude that GH_A11G3500-mediated bispecific phosphorylated genes may serve as key regulators in the resistance of G. hirsutum to Verticillium wilt (VW). This study presents a comprehensive structure designed to provide an in-depth understanding of the potential biological functions of cotton, providing a strong foundation for further research into molecular breeding and resistance to plant pathogens.

Multi-Omics Integration for Liver Cancer Using Regression Analysis.

Genetic biomarkers have played a pivotal role in the classification, prognostication, and guidance of clinical cancer therapies. Large-scale and multi-dimensional analyses of entire cancer genomes, as exemplified by projects like The Cancer Genome Atlas (TCGA), have yielded an extensive repository of data that holds the potential to unveil the underlying biology of these malignancies. Mutations stand out as the principal catalysts of cellular transformation. Nonetheless, other global genomic processes, such as alterations in gene expression and chromosomal re-arrangements, also play crucial roles in conferring cellular immortality. The incorporation of multi-omics data specific to cancer has demonstrated the capacity to enhance our comprehension of the molecular mechanisms underpinning carcinogenesis. This report elucidates how the integration of comprehensive data on methylation, gene expression, and copy number variations can effectively facilitate the unsupervised clustering of cancer samples. We have identified regressors that can effectively classify tumor and normal samples with an optimal integration of RNA sequencing, DNA methylation, and copy number variation while also achieving significant p-values. Further, these regressors were trained using linear and logistic regression with k-means clustering. For comparison, we employed autoencoder- and stacking-based omics integration and computed silhouette scores to evaluate the clusters. The proof of concept is illustrated using liver cancer data. Our analysis serves to underscore the feasibility of unsupervised cancer classification by considering genetic markers beyond mutations, thereby emphasizing the clinical relevance of additional global cellular parameters that contribute to the transformative process in cells. This work is clinically relevant because changes in gene expression and genomic re-arrangements have been shown to be signatures of cellular transformation across cancers, as well as in liver cancers.

SpVC for the detection and interpretation of spatial gene expression variation

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.

Adaptation of the Mycobacterium tuberculosis transcriptome to biofilm growth.

Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis (TB), is a leading global cause of death from infectious disease. Biofilms are increasingly recognized as a relevant growth form during M. tb infection and may impede treatment by enabling bacterial drug and immune tolerance. M. tb has a complicated regulatory network that has been well-characterized for many relevant disease states, including dormancy and hypoxia. However, despite its importance, our knowledge of the genes and pathways involved in biofilm formation is limited. Here we characterize the biofilm transcriptomes of fully virulent clinical isolates and find that the regulatory systems underlying biofilm growth vary widely between strains and are also distinct from regulatory programs associated with other environmental cues. We used experimental evolution to investigate changes to the transcriptome during adaptation to biofilm growth and found that the application of a uniform selection pressure resulted in loss of strain-to-strain variation in gene expression, resulting in a more uniform biofilm transcriptome. The adaptive trajectories of transcriptomes were shaped by the genetic background of the M. tb population leading to convergence on a sub-lineage specific transcriptome. We identified widespread upregulation of non-coding RNA (ncRNA) as a common feature of the biofilm transcriptome and hypothesize that ncRNA function in genome-wide modulation of gene expression, thereby facilitating rapid regulatory responses to new environments. These results reveal a new facet of the M. tb regulatory system and provide valuable insight into how M. tb adapts to new environments.