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At least 793 records · Page 44Linked to original sources
PubMed2006

Salt stress in Desulfovibrio vulgaris Hildenborough: an integrated genomics approach.

The ability of Desulfovibrio vulgaris Hildenborough to reduce, and therefore contain, toxic and radioactive metal waste has made all factors that affect the physiology of this organism of great interest. Increased salinity is an important and frequent fluctuation faced by D. vulgaris in its natural habitat. In liquid culture, exposure to excess salt resulted in striking elongation of D. vulgaris cells. Using data from transcriptomics, proteomics, metabolite assays, phospholipid fatty acid profiling, and electron microscopy, we used a systems approach to explore the effects of excess NaCl on D. vulgaris. In this study we demonstrated that import of osmoprotectants, such as glycine betaine and ectoine, is the primary mechanism used by D. vulgaris to counter hyperionic stress. Several efflux systems were also highly up-regulated, as was the ATP synthesis pathway. Increases in the levels of both RNA and DNA helicases suggested that salt stress affected the stability of nucleic acid base pairing. An overall increase in the level of branched fatty acids indicated that there were changes in cell wall fluidity. The immediate response to salt stress included up-regulation of chemotaxis genes, although flagellar biosynthesis was down-regulated. Other down-regulated systems included lactate uptake permeases and ABC transport systems. The results of an extensive NaCl stress analysis were compared with microarray data from a KCl stress analysis, and unlike many other bacteria, D. vulgaris responded similarly to the two stresses. Integration of data from multiple methods allowed us to develop a conceptual model for the salt stress response in D. vulgaris that can be compared to those in other microorganisms.

Bacterial Proteins↗
PubMedDate not supplied

The essential similarity of TGFbeta and activin receptor transcriptional responses in cancer cells.

The binding of activin and TGFbeta to their respective receptors initiates signals that are carried by common intermediates (Smad proteins) to induce transcriptional activation of downstream genes. Mutations in tumors indicate that both receptor types convey tumorsuppressive signals, among other biologic roles, but their respective sets of transcriptional targets (transcriptomes) and the shared degree of transcriptome similarity are not well explored in these cells. Transcriptome changes were analyzed by gene expression profiling after expression of constitutively active activin type I (ALK4m) and TGFbeta type I (ALK5m) receptors and by variation of Smad4 expression in cancer cells. Eleven of 15 previously reported TGFbeta downstream genes were confirmed to be responsive to TGFb and activin receptors in cancer cells. Expression profiling detected eight of these 11, as well as 13 new Smad4-dependent transcripts. Although Smad4-dependent CDKN1A/p21 induction represents the sole known effector of TGFbeta and activin tumor-suppressor effects, many downstream genes have not yet been evaluated for a suppressive role. A high similarity of TGFbeta and activin responses among the known and new transcriptional target genes indicated an essential redundancy of the two related inputs. This similarity helps relate the mutations seen in both receptor systems and their Smad mediators in human cancers.

Activin Receptors, Type I↗
PubMed2026

Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.

Rare diseases collectively affect 1 in 10 individuals, yet current genetic testing fails to identify a causal variant for most cases. At present, cytogenetic methods and/or sequencing approaches such as exome (ES) or short-read genome sequencing (srGS) represent the state-of-the-art for comprehensive clinical discovery of sequence and structural variants (SVs), including copy number variants, balanced SVs, complex SVs, and tandem repeats (TRs). Recently, long-read genome sequencing (lrGS), coupled with multiomics data, has presented great promise to resolve variation in genomic regions recalcitrant to characterization by srGS such as highly repetitive simple repeat sequences and segmental duplications. However, there are few guidelines to enable clinical interpretation of genetic variation in these highly repetitive genomic regions, and the enthusiasm of the field in adopting lrGS has made it difficult to assess the true added diagnostic yield of this technology due to widely variable and inconsistently applied analytic pipelines and variable degrees of pre-screening by ES or srGS. Here, we investigated the contribution of SVs to rare diseases using srGS as a front-line strategy when paired with highly sensitive SV discovery and evaluate the added diagnostic yield of incorporating lrGS for a subset of cases. Our srGS analysis encompassed 1,462 families (3,450 individuals) recruited through the Broad Institute Center for Mendelian Genetics and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) programs. Diagnostic SVs were identified in 5.4% of cases (79/1,462), of which 80% were uniquely detectable by srGS compared to standard cytogenetic techniques. For 96 families (including 10 families with a heterozygous variant observed in a known recessive gene of clinical relevance), we performed lrGS with methylation profiling, as well as long-read transcriptomic analyses in a subset of 20 trios. Analyses with lrGS yielded over 25,000 SVs per genome, 63% of which were not captured by srGS, along with an additional ~200 rare SNV/indels per genome not previously captured and 12 differentially methylated regions per genome. Among these, we identified only one diagnostic variant not interpreted by srGS, an apparently mosaic de novo SNV in CASK that was absent in the srGS callset due to allelic imbalance. No new diagnoses were supported by long-read transcriptomics or episignatures. In this well characterized rare disease cohort, the added diagnostic yield was thus 1.04% (1/96 families). Following a systematic literature review of prior lrGS studies, we find that most reported diagnoses were detectable by srGS and that our added diagnostic yield is consistent with those prior studies. These studies emphasize the significant impact of comprehensive SV discovery in rare disease cases and further demonstrate the power for increased discovery of novel genomic variation and episignatures from lrGS. Nonetheless, they also serve to temper expectations of dramatic diagnostic advances in rare disease patients until there is more extensive annotation of the functional and clinical impact of all coding and noncoding variation uniquely accessible to lrGS with extensive reference databases spanning highly repetitive genomic sequencing that could be enabled by this transformative technology.

Journal Article↗
PubMed2002

A quantitative and validated SAGE transcriptome reference for adult mouse heart.

Transcriptome comparisons facilitate the identification of developmental, aging, and disease-related genes. To quantify the functionally active genome of adult C57BL/6 mouse heart (AMH), we used serial analysis of gene expression (SAGE) to sequence a total of 88,860 tags or 23,941 unique tags. Over 66% of the unique tags matched either known genes or ESTs. Mitochondrial transcripts accounted for 18.7% of the total transcripts, whereas sarcomeric proteins accounted for 3.2% of all tags. After comparison of AMH expression profiles obtained by SAGE and cDNA arrays, we observed numerous quantitative discrepancies (for example: arrays, mt-Co1 > mt-Co2 > mt-Co3; SAGE, mt-Co1 >> mt-Co3 >or= mt-Co2). We carried out quantitative PCR analyses as an independent test of transcript abundance and determined that SAGE yielded quantitatively reliable data. These SAGE results thus represent the first quantitative expression profile of AMH and serve as a reliable transcriptome reference to identify dynamic changes in cardiac gene expression.

Animals↗
PubMed2006

Molecular basis of cell-biomaterial interaction: insights gained from transcriptomic and proteomic studies.

With the growing interest in clinical interventions that involve medical devices, the role for new biomaterials in modern medicine is currently expanding at a phenomenal rate. Failure of most implant materials stems from an inability to predict and control biological phenomena, such as protein adsorption and cell interaction, resulting in an inappropriate host response to the materials. Contemporary advances in biological investigation are starting to shift focus in the biomaterials field, in particular with the advent of high-throughput methodologies for gene and protein expression profiling. Here, we examine the role that emerging transcriptomic and proteomic technologies could play in relation to biomaterial development and usage. Moreover, a number of studies are highlighted which have utilized such approaches in order to try to create a deeper understanding of cell-biomaterial interactions and, hence, improve our ability to predict and control the biocompatibility of new materials.

Biocompatible Materials↗
PubMed2026

Transcriptomic signatures of mind-body transformations therapy in breast cancer: Downregulation of the interferon signaling pathway.

BACKGROUND: Growing evidence has shown that Mind-Body Transformations-Therapies (MBT-T) are able to modulate chronic inflammation, a well-known driver of cancer progression and drug resistance. In our previous work, we showed that a specific MBT-T protocol was able to reduce the release of various pro-inflammatory cytokines and chemokines in the sera of patients with breast cancer that completed adjuvant chemotherapy. Despite these clinical observations, the underlying molecular pathways through which this therapy exerts its effects remain unclear. This study aims to address this gap by characterizing genome-wide transcriptional profiles in patients undergoing a novel MBT-T protocol. METHODS: In this proof-of-concept study, patients with breast cancer were randomized into two groups: Group 1 (CTL), receiving standard follow-up care, and Group 2 (MBT-T), receiving standard follow-up plus biweekly MBT-T for 4 months. Blood samples were collected at different timepoints during the treatment. After RNA extraction from whole blood, gene expression was analyzed on twenty-one patients (CTL, n = 7; MBT-T, n = 14) using the nCounter® Human Inflammation Panel (249 genes). RESULTS: Patients undergoing MBT-T showed a significant global downregulation of inflammatory gene expression compared to the control group. The analysis revealed that the Interferon (IFN) signaling pathway was the most significantly suppressed, by downregulation of key genes such as IFIT1, IFIT3, IFI44, MX1 and OASL in the MBT-T group. CONCLUSIONS: MBT-T acts as a biological modulator capable of downregulating key inflammatory pathways at the transcriptional level. These findings provide a genomic basis for the clinical benefits of mind-body interventions in oncology.

Breast cancer↗
PubMed2004

A dual-genome Symbiosis Chip for coordinate study of signal exchange and development in a prokaryote-host interaction.

The soil-dwelling alpha-proteobacterium Sinorhizobium meliloti engages in a symbiosis with legumes: S. meliloti elicits the formation of plant root nodules where it converts dinitrogen to ammonia for use by the plant in exchange for plant photosynthate. To study the coordinate differentiation of S. meliloti and its legume partner during nodule development, we designed a custom Affymetrix GeneChip with the complete S. meliloti genome and approximately 10,000 probe sets for the plant host, Medicago truncatula. Expression profiling of free-living S. meliloti grown with the plant signal molecule luteolin in defined minimal and rich media or of strains altered in the expression of key regulatory proteins (NodD1, NodD3, and RpoN) confirms previous data and identifies previously undescribed regulatory targets. Analyses of root nodules show that this Symbiosis Chip allows the study of gene expression in both partners simultaneously. Our studies detail nearly 5,000 transcriptome changes in symbiosis and document complex transcriptional profiles of S. meliloti in different environments.

Bacterial Proteins↗
PubMed2025

Rhythm profiling using COFE reveals multi-omic circadian rhythms in human cancers in vivo.

The study of ubiquitous circadian rhythms in human physiology requires regular measurements across time. Repeated sampling of the different internal tissues that house circadian clocks is both practically and ethically infeasible. Here, we present a novel unsupervised machine learning approach (COFE) that can use single high-throughput omics samples (without time labels) from individuals to reconstruct circadian rhythms across cohorts. COFE can simultaneously assign time labels to samples and identify rhythmic data features used for temporal reconstruction, while also detecting invalid orderings. With COFE, we discovered widespread de novo circadian gene expression rhythms in 11 different human adenocarcinomas using data from The Cancer Genome Atlas (TCGA) database. The arrangement of peak times of core clock gene expression was conserved across cancers and resembled a healthy functional clock except for the mistiming of a few key genes. Moreover, rhythms in the transcriptome were strongly associated with the cancer-relevant proteome. The rhythmic genes and proteins common to all cancers were involved in metabolism and the cell cycle. Although these rhythms were synchronized with the cell cycle in many cancers, they were uncoupled with clocks in healthy matched tissue. The targets of most of FDA-approved and potential anti-cancer drugs were rhythmic in tumor tissue with different amplitudes and peak times. These findings emphasize the utility of considering "time" in cancer therapy, and suggest a focus on clocks in healthy tissue rather than free-running clocks in cancer tissue. Our approach thus creates new opportunities to repurpose data without time labels to study circadian rhythms.

Humans↗
PubMed2006

Global impact: elucidating plant responses to viral infection.

Viruses induce a variety of responses in host cells that are mediated by perturbation of different signaling pathways. Advances in our understanding of the functions of viral proteins, plant biology in general, as well as technologies for profiling gene expression have converged in recent years to provide new insight into the events occurring inside susceptible and resistant host cells in response to virus infection. These effects range from nonspecific changes in gene expression due to the general accumulation of viral proteins to those responses that are initiated by the specific interactions between virus and host proteins. Here, we discuss a variety of expression profiling methods and approaches that have been used to study the effects of viruses on host transcriptomes. These studies have identified distinct sets of genes that have altered expression profiles in response to viruses, including stress- and defense-related genes. The activities of viral RNA silencing suppressors and interference with hormone signaling or biogenesis also influence plant gene expression and lead to developmental abnormalities.

Gene Expression Profiling↗
PubMed2026

Decoding regional keratinization in human oral mucosa through high-resolution spatial transcriptomics.

Oral mucosa exhibits region-specific keratinization, essential for periodontal health, yet the spatial and molecular mechanisms driving these differences remain poorly understood. This study aimed to generate a high-resolution spatial transcriptomic atlas of the human oral mucosa around the mucogingival junction, to reveal stromal-epithelial interactions, that distinguish keratinized from non-keratinized programs. Formalin-fixed paraffin-embedded specimens from the mucogingival junction area of two healthy donors were analyzed with the 10 × Genomics Visium HD platform, yielding two keratinized and two non-keratinized regions. Spatial clustering, pseudotime trajectory inference, cell-type integration with a single-cell reference, and ligand-receptor network analysis were applied to delineate epithelial and stromal compartments. Sixteen reproducible clusters, recapitulating tissue architecture, were identified and revealed distinct transcriptional signatures, distinguishing gingiva from lining mucosa. Pseudotime analysis revealed bifurcating epithelial lineages, originating from a shared basal progenitor layer into keratinized and non-keratinized programs. Gingival keratinization was driven by stromal collagen ligands (COL1A1, COL1A2, COL6A1, COL6A2) engaging epithelial receptors (CD44, SDC1), further reinforced within the epithelium by desmosomal adhesion via DSG1-DSC2/3. Gingival keratinization emerges from integrated stromal collagen signaling and epithelial adhesion. This spatially resolved framework advances understanding of oral mucosal specialization and provides a foundation for biologically guided regenerative therapies.

Humans↗
PubMed2005

Synaptic and genomic responses to JNK and AP-1 signaling in Drosophila neurons.

BACKGROUND: The transcription factor AP-1 positively controls synaptic plasticity at the Drosophila neuromuscular junction. Although in motor neurons, JNK has been shown to activate AP-1, a positive regulator of growth and strength at the larval NMJ, the consequences of JNK activation are poorly studied. In addition, the downstream transcriptional targets of JNK and AP-1 signaling in the Drosophila nervous system have yet to be identified. Here, we further investigated the role of JNK signaling at this model synapse employing an activated form of JNK-kinase; and using Serial Analysis of Gene Expression and oligonucleotide microarrays, searched for candidate early targets of JNK or AP-1 dependent transcription in neurons. RESULTS: Temporally-controlled JNK induction in postembryonic motor neurons triggers synaptic growth at the NMJ indicating a role in developmental plasticity rather than synaptogenesis. An unexpected observation that JNK activation also causes a reduction in transmitter release is inconsistent with JNK functioning solely through AP-1 and suggests an additional, yet-unidentified pathway for JNK signaling in motor neurons. SAGE profiling of mRNA expression helps define the neural transcriptome in Drosophila. Though many putative AP-1 and JNK target genes arose from the genomic screens, few were confirmed in subsequent validation experiments. One potentially important neuronal AP-1 target discovered, CG6044, was previously implicated in olfactory associative memory. In addition, 5 mRNAs regulated by RU486, a steroid used to trigger conditional gene expression were identified. CONCLUSION: This study demonstrates a novel role for JNK signaling at the larval neuromuscular junction and provides a quantitative profile of gene transcription in Drosophila neurons. While identifying potential JNK/AP-1 targets it reveals the limitations of genome-wide analyses using complex tissues like the whole brain.

Animals↗
PubMed2006

Quantitative comparison of the HSV-1 and HSV-2 transcriptomes using DNA microarray analysis.

The genomes of human herpes virus type-1 and type-2 share a high degree of sequence identity; yet, they exhibit important differences in pathology in their natural human host as well as in animal host and cell cultures. Here, we report the comparative analysis of the time and relative abundance profiles of the transcription of each virus type (their transcriptomes) using parallel infections and microarray analysis using HSV-1 probes which hybridize with high efficiency to orthologous HSV-2 transcripts. We have confirmed that orthologous transcripts belong to the same kinetic class; however, the temporal pattern of accumulation of 4 transcripts (U(L)4, U(L)29, U(L)30, and U(L)31) differs in infections between the two virus types. Interestingly, the protein products of these transcripts are all involved in nuclear organization and viral DNA localization. We discuss the relevance of these findings and whether they may have potential roles in the pathological differences of HSV-1 and HSV-2.

Animals↗
PubMed2006

Monitoring the health to disease continuum with global metabolic profiling and systems biology.

Global metabolic profiling, which includes both metabolomics and metabonomics studies, is the latest 'omics' research platform that is being applied to understand the health and disease continuum. Metabolic profiling analyses have been demonstrated for the investigation of inborn errors of metabolism, organ transplant rejection, drug toxicity, disease diagnosis and prognosis, drug efficacy and nutritional status. Combining information generated from a metabolic profiling platform with that obtained based on genetics, transcriptomics and proteomics research paradigms will pave the way for a better understanding of the mechanisms of disease and toxicity. Metabolomics and nutrition will lay the groundwork for the application of personalized medicine in the 21st century.

Animals↗
PubMed2026

Longitudinal multiorgan transcriptomic atlas of salt-induced hypertension.

High dietary salt intake elevates blood pressure and drives multiorgan damage. However, the molecular programs underlying progressive organ injury remain poorly defined. Here, we present a longitudinal multiorgan transcriptomic atlas of salt-induced hypertensive injury. We profiled kidney cortex, kidney medulla, heart, and liver across 4 stages, spanning early hypertension to advanced pathology in Dahl salt-sensitive rats. We identified dynamic and tissue-specific molecular trajectories, including a shared early proliferative response that converges on proinflammatory and fibrotic remodeling. Notably, we uncovered compartment-specific renal responses, showing that the cortex and medulla, despite their proximity, follow distinct molecular trajectories during disease progression. We further identified 79 stage- and tissue-specific transcription factors that drive gene expression dynamics in salt-induced hypertensive injury. Integration with human genome-wide association studies revealed conserved pathways in endocrine signaling, ion transport, lipid metabolism, and detoxification, establishing cross-species relevance and highlighting mechanistic targets of clinical importance. Compound-transcriptome analysis revealed stage- and organ-specific therapeutic opportunities, prioritizing kinase and epigenetic modulators as candidates to rebalance maladaptive gene programs. Overall, this study provides a resource for understanding molecular mechanisms from early salt-induced hypertension to tissue-specific injury and underscores the need for precision interventions.

Animals↗
PubMed2006

Toxicogenomic response of Staphylococcus aureus to peracetic acid.

Staphylococcus aureus is responsible for many incidents of hospital-acquired infection, which causes 90,000 deaths and dollars 4.5 billion loss a year in the United States. Despite a wide use of disinfectants such as peracetic acid in health care environments, we certainly need better understanding of the effects of antimicrobial application on target pathogens to avert infection outbreaks. Consequently, herein, we explored for the first time the toxicogenomic response of S. aureus to a sublethal concentration of peracetic acid (1 mM) by using microarray-based transcriptome analysis. In particular, we investigated the dynamics of global gene expression profiles during its cellular response, which involved initial growth inhibition (10 min) and subsequent partial recovery (20 min). Further, we compared transcriptome responses to peracetic acid between S. aureus and Pseudomonas aeruginosa. Our findings show that (i) the regulation of membrane transport genes was significantly altered, (ii) DNA repair and replication genes were selectively induced, and (iii) primary metabolism-related genes were differently repressed between the two growth states. Most intriguingly, we revealed that many virulence factor genes were induced upon the exposure, which proposes a possibilitythatthe pathogenesis of S. aureus may be stimulated in response to peracetic acid.

Anti-Infective Agents↗
PubMed2026

Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.

Subcellular spatial transcriptomics can resolve tissue architecture at cellular scale, but sparse gene panels and limited detection sensitivity constrain downstream analysis. Existing enhancement methods often require tissue-matched single-cell RNA sequencing (scRNA-seq) references and dataset-specific retraining. Here we show that stPainter, a conditional generative model pretrained on a pan-cancer scRNA-seq atlas, can enhance spatial transcriptomics data without matched references or retraining. Using a latent diffusion architecture guided by Stochastic Differential Equations (SDE), stPainter reconstructs expanded expression profiles from sparse measurements and produces latent representations for clustering and cell-state analysis. When we apply stPainter upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers downstream biological analyses, including fine-grained subpopulation clustering and pathway enrichment. Comparison with spatially resolved proteomics (CODEX) provided independent support for regional agreement between imputed cellular compositions and protein-level tissue organization. These results establish stPainter as a scalable approach for analyzing tumor microenvironments without auxiliary sequencing data.

Spatial Transcriptomics↗
PubMed2006

Gene expression profiling of human macrophages at late time of infection with Mycobacterium tuberculosis.

Macrophages play an essential role in the immune response to Mycobacterium tuberculosis (Mtb). Previous transcriptome surveys, by means of micro- and macroarrays, investigated the cellular gene expression profile during the early phases of infection (within 48 hr). However, Mtb remains within the host macrophages for a longer period, continuing to influence the macrophage gene expression and, consequently, the environment in which it persists. Therefore, we studied the transcription patterns of human macrophages for up to 7 days after infection with Mtb. We used a macroarray approach to study 858 human genes involved in immunoregulation, and we confirmed by quantitative real-time reverse transcriptase polymerase chain reaction (q-rt RT-PCR) and by enzyme-linked immunosorbent assay the most relevant modulations. We constantly observed the up-regulation in infected macrophages versus uninfected, of the following genes: interleukin-1 beta and interleukin-8, macrophage inflammatory protein-1 alpha, growth-related oncogene-beta, epithelial cell-derived neutrophil-activating peptide-78, macrophage-derived chemokine, and matrix metalloproteinase-7; whereas macrophage colony-stimulating factor-receptor and CD4 were down-regulated in infected macrophages. Mtb is able to withstand this intense cytokine microenvironment and to survive inside the human macrophage. Therefore we simultaneously investigated by q-rt RT-PCR the modulation of five mycobacterial genes: the alternative sigma factors sigA, sigE and sigG, the alpha-crystallin (acr) and the superoxide dismutase C (sodC) involved in survival mechanisms. The identified host and mycobacterial genes that were expressed until 7 days after infection, could have a role in the interplay between the host immune defences and the bacterial escape mechanisms.

Cells, Cultured↗