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PubMed2004

Genomic and proteomic profiling for biomarkers and signature profiles of toxicity.

Toxicity profiling measures and compares all gene expression changes among biological samples after toxicant exposure. Toxicity profiling with DNA microarrays to measure all mRNA transcripts (transcriptomics), or by global separation and identification of proteins (proteomics), has led to the discovery of better descriptors of toxicity, toxicant classification and exposure monitoring than current indicators. A shared goal in transcript and proteomic profiling is the development of biomarkers and signatures of chemical toxicity. In this review, biomarkers and signature profiles are described for specific chemical toxicants that affect target organs such as liver, kidney, neural tissues, gastrointestinal tract and skeletal muscle, for specific disease models such as cancer and inflammation, and for unique chemical-protein adducts underlying cell injury. The recent introduction of toxicogenomics databases support researchers in sharing, analyzing, visualizing and mining expression data, assist the integration of transcriptomics, proteomics and toxicology datasets, and eventually will permit in silico biomarker and signature pattern discovery.

Animals↗

PubMed2004

Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium.

BACKGROUND: Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. RESULTS: Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using tissue microarrays to demonstrate a significant association between downregulated protein expression and tumorigenesis, a process that is the reverse of what is seen in the presence of Selenium. CONCLUSIONS: Thus the outlined process demonstrates similar baseline and selenium induced gene expression profiles between rat and human prostate cancers, and provides a method for identifying testable functional pathways for the action of Selenium's chemopreventive properties in prostate cancer.

Adenocarcinoma↗

PubMed2005

Arabidopsis thaliana full genome longmer microarrays: a powerful gene discovery tool for agriculture and forestry.

Sequenced plant genomes provide a large reservoir of known genes with potential for use in crop and tree improvement, but assignment of specific functions to annotated genes in sequenced plant genomes remains a challenge. Furthermore, most plant genes belong to families encoding proteins with related but distinct functions. In this commentary, we discuss our development of Arabidopsis spotted whole genome longmer oligonucleotide microarrays, and their use in global transcription profiling. We show that longmer array based transcriptome analysis in Arabidopsis can be used as an efficient and effective gene discovery and functional genomics tool, particularly for functional analyses of members of large gene families. We discuss experiments that focus on gene families involved in phenylpropanoid natural product biosynthesis and fiber differentiation. These analyses have helped to elucidate functions of individual gene family members, and have identified new candidate genes involved in fiber development and differentiation. Results obtained by these studies in Arabidopsis can be used as the basis for gene discovery in commercially important plants, and we have focused our attention on Populus trichocarpa (poplar), a species important in forestry and agroforestry for which complete genome sequence information is available.

Agriculture↗

PubMed2002

Microarray analysis of bacterial pathogenicity.

The DNA microarray, a surface that contains an ordered arrangement of each identified open reading frame of a sequenced genome, is the engine of functional genomics. Its output, the expression profile, provides a genome wide snap-shot of the transcriptome. Refined by array-specific statistical instruments and data-mined by clustering algorithms and metabolic pathway databases, the expression profile discloses, at the transcriptional level, how the microbe adapts to new conditions of growth--the regulatory networks that govern the adaptive response and the metabolic and biosynthetic pathways that effect the new phenotype. Adaptation to host microenvironments underlies the capacity of infectious agents to persist in and damage host tissues. While monitoring the whole genome transcriptional response of bacterial pathogens within infected tissues has not been achieved, it is likely that the complex, tissue-specific response is but the sum of individual responses of the bacteria to specific physicochemical features that characterize the host milieu. These are amenable to experimentation in vitro and whole-genome expression studies of this kind have defined the transcriptional response to iron starvation, low oxygen, acid pH, quorum-sensing pheromones and reactive oxygen intermediates. These have disclosed new information about even well-studied processes and provide a portrait of the adapting bacterium as a 'system', rather than the product of a few genes or even a few regulons. Amongst the regulated genes that compose this adaptive system are transcription factors. Expression profiling experiments of transcription factor mutants delineate the corresponding regulatory cascade. The genetic basis for pathogenicity can also be studied by using microarray-based comparative genomics to characterize and quantify the extent of genetic variability within natural populations at the gene level of resolution. Also identified are differences between pathogen and commensal that point to possible virulence determinants or disclose evolutionary history. The host vigorously engages the pathogen; expression studies using host genome microarrays and bacterially infected cell cultures show that the initial host reaction is dominated by the innate immune response. However, within the complex expression profile of the host cell are components mediated by pathogen-specific determinants. In the future, the combined use of bacterial and host microarrays to study the same infected tissue will reveal the dialogue between pathogen and host in a gene-by-gene and site- and time-specific manner. Translating this conversation will not be easy and will probably require a combination of powerful bioinformatic tools and traditional experimental approaches--and considerable effort and time.

Animals↗

PubMed2004

Transcriptome of 3D7 and its gametocyte-less derivative F12 Plasmodium falciparum clones during erythrocytic development using a gene-specific microarray assigned to gene regulation, cell cycle and transcription factors.

During the complex life cycle of Plasmodium falciparum, through mosquito and human, the erythrocytic cycle is responsible for malarial disease and transmission. The regulation of events that occur during parasite development, such as proliferation and differentiation, implies a fine control of transcriptional activities that in turn governs the expression profiles of sets of genes. Pathways that underline gametocyte commitment are yet poorly understood even though kinases and transcription factors have been assumed to play a crucial role in this event. In order to understand the molecular mechanisms controlling the variation of gene expression profiles that might participate in early gametocytogenesis, the transcriptome of two clones, 3D7 and its gametocyte-less derivative F12, was compared at five time points of the erythrocytic asexual development. We have used a thematic DNA microarray containing 150 PCR fragments, representative of P. falciparum genes involved in signal transduction, cell cycle and transcriptional regulation. We identified several genes eliciting different expression profiles among which some implicated in gene regulation or encoding putative transcription factors. The differential expression of transcription factor and kinase transcripts observed in the two clones may enlighten genes that might have a role in impairment of the early gametocytogenesis of the F12 clone.

Animals↗

PubMed2002

Profiling alternative splicing on fiber-optic arrays.

The human transcriptome is marked by extensive alternative mRNA splicing and the expression of many closely related genes, which may be difficult to distinguish using standard microarray techniques. Here we describe a sensitive and specific assay for parallel analysis of mRNA isoforms on a fiber-optic microarray platform. The method permits analysis of mRNA transcripts without prior RNA purification or cDNA synthesis. Using an endogenously expressed viral transcript as a model, we demonstrated that the assay readily detects mRNA isoforms from as little as 10-100 pg of total cellular RNA or directly from a few cells. Multiplexed analysis of human cancer cell lines revealed differences in mRNA splicing and suggested a potential autocrine mechanism in the development of choriocarcinomas. Our approach may be useful in the large-scale analysis of the role of alternative splicing in development and disease.

Alternative Splicing↗

PubMed2026

Time-resolved mapping in calves reveals bovine herpesvirus 1 shift from mucosal replication to trigeminal ganglion neuroinvasion with promyelocytic leukemia protein-centered host-virus antagonism.

Although bovine herpesvirus 1 (BoHV-1) causes massive losses of cattle, the transition from mucosal replication to neuroinvasion remains poorly understood. Using a controlled calf model, we integrated quantitative virology and transcriptomics to map its pathogenesis and define the role of promyelocytic leukemia protein (PML). Calves inoculated intranasally and ocularly (1.4 × 106 plaque-forming units/head) were sampled daily (1-14 days post-infection, dpi) for glycoprotein B (gB) qPCR. Tissues were analyzed at 4 and 14 dpi to measure viral DNA via gB-specific qPCR, and for mRNA-seq of trigeminal ganglia (TG). Shedding peaked at 3-6 dpi, being highest in nasal samples, lower in ocular samples, and substantially lower in rectal samples, and declined by 10-14 dpi. At 4 dpi, among the tissues sampled, the tonsils exhibited the highest viral burden. TG exhibited low viral levels at 4 dpi, although they remained detectable at 14 dpi, indicating neuroinvasion. The TG program shifted from early proteostasis priming (4 dpi) to immune/extracellular matrix activation with synaptic repression (14 dpi). In MDBK/Vero cells, IFN-α resulted in higher bovine PML (bPML) levels and enlarged PML nuclear bodies (PML-NBs), reducing very early viral DNA levels, whereas BoHV-1 disrupted PML-NB integrity. The different bPML isoforms exerted different effects on viral infection. STRING analysis revealed a conserved PML-SUMO1-UBE2I-DAXX-SP100 core. These findings delineate the mucosal-to-neuronal trajectory, establish PML as both an effector and viral target in complementary in vitro systems, and identify SUMO/ubiquitin-linked proteostasis as a tractable target for antiviral intervention.IMPORTANCEAlthough bovine herpesvirus 1 (BoHV-1) remains a major challenge to cattle health, the early transition from mucosal replication to trigeminal neuroinvasion has not been clearly mapped in natural-host calves. By integrating daily shedding kinetics, tissue viral DNA profiling, and time-resolved trigeminal ganglion transcriptomics, we delineate when and how BoHV-1 reaches the sensory neurons. Promyelocytic leukemia protein (PML) is identified as a key intrinsic antiviral factor that is upregulated by IFN-α and restricts very early viral genome accumulation, while viral BoHV-1-encoded infected cell protein 0 actively dismantles PML nuclear bodies. The discovery of opposing isoform-specific PML functions and a conserved PML-SUMO proteostasis hub provides mechanistic insight into BoHV-1 immune evasion. These findings refine our understanding of the mucosal-to-neuronal trajectory of infection and highlight proteostasis-linked antiviral pathways as promising targets for intervention.

Animals↗

PubMed2026

Selective saccular plasticity under microgravity links peripheral transcriptomic remodeling to postflight vestibular dysfunction.

Long-duration exposure to microgravity disrupts human balance and spatial orientation, yet the molecular mechanisms underlying vestibular adaptation to spaceflight remain poorly understood. Here, we tested the hypothesis that the saccule, the primary gravity-sensing otolith organ, undergoes selective remodeling during spaceflight and contributes to transient postflight postural instability. Using a cross-species approach, we combined transcriptomic analysis of mouse otolith organs with physiological assessments in astronauts. Laser microdissection-based RNA sequencing of mouse otolith sensory epithelia after a 35-d spaceflight revealed pronounced, organ-specific transcriptomic remodeling in the saccule, whereas the utricle remained stable. Principal component and clustering analyses demonstrated that the saccular transcriptome shifted toward an utricle-like profile under microgravity, accompanied by changes in genes related to synaptic and neuronal function. Promoter motif analysis identified NFAT-associated transcriptional networks, suggesting Ca2+-dependent regulation of synaptic plasticity as a potential molecular substrate of gravity-dependent adaptation. In parallel, vestibular testing in astronauts following long-duration missions (157 to 328 d) revealed selective attenuation of saccule-mediated cervical vestibular-evoked myogenic potentials and increased postural sway immediately after return to Earth, while utricle-mediated responses and semicircular canal function were preserved. Both saccular function and postural stability recovered within approximately 10 d. Notably, early postflight postural instability was partially mitigated by noisy galvanic vestibular stimulation, consistent with stochastic resonance-mediated sensory enhancement. Together, these findings identify the saccule as a plastic gravity sensor and establish a mechanistic link between peripheral molecular remodeling and functional balance deficits after spaceflight, providing a framework for developing countermeasures to facilitate vestibular readaptation during human space exploration.

Animals↗

PubMed2025

Next-generation sequencing in breast cancer: current clinical applications and future directions.

INTRODUCTION: Breast cancer is a heterogeneous disease that claims 670,000 lives by 2022. Omic technologies, particularly next generation sequencing (NGS) offers promising avenues for precision medicine. American Society of Clinical Oncology (ASCO) outlines genomic testing's utility, emphasizing prognostic and diagnostic potential. OBJECTIVES: This review succinctly explores NGS's evolution and clinical applications of NGS in breast cancer, thereby guiding future research to enhance patient care. METHODS: Comprehensive literature searches were conducted using databases such as PubMed, Google Scholar, and ResearchGate, focusing on keywords including breast cancer, HER-2 low breast cancer, circulating tumour DNA, single-cell RNA sequencing, and next-generation sequencing. Peer-reviewed, high-quality articles published in English were selected for inclusion. RESULTS: Previous studies have explored the evolution of NGS technology and its clinical applications in breast cancer, including genomic and transcriptomic characterization, treatment guidance, and resistance prediction. Molecular profiling of challenging entities such as early-onset breast cancer and HER-2 low tumours was summarized, with key findings highlighted. This review also discusses emerging technologies, including circulating DNA and single-cell sequencing, as promising avenues for discovery. CONCLUSION: NGS has revealed the genomic and transcriptomic diversity of breast cancer, identifying actionable alterations associated with chemotherapy response and resistance to therapies such as trastuzumab, TKIs, and CDK4/6 inhibitors. Circulating tumour DNA (ctDNA) shows potential for diagnosis, prediction, prognosis, and monitoring, despite tumour heterogeneity. Single-cell analysis enables exploration of individual cell transcriptomes, though high costs and low throughput remain barriers to widespread adoption. HER2-low tumours continue to pose significant research challenges.

Humans↗

PubMed2002

Genome-wide transcriptional profiling of the Bacillus subtilis cold-shock response.

The transcriptome of Bacillus subtilis was analysed at different time points (30, 60 and 90 min) after a temperature downshift from 37 to 18 degrees C using DNA macroarrays. This approach allowed the identification of around 50 genes exhibiting an increased mRNA level and around 50 genes exhibiting a decreased mRNA level under cold-shock conditions. Many of the repressed genes encode enzymes involved in the biosynthesis of amino acids, nucleotides and coenzymes, indicating metabolic adaptation of the cells to the decreased growth rate at the lower temperature. The strongest cold-inducible gene encodes fatty acid desaturase, which forms unsaturated fatty acids from saturated phospholipid precursors, thereby increasing membrane fluidity. The cold-shock-induced increase of mRNA levels of the classical cold-shock genes cspB, cspC and cspD could be verified. Furthermore, besides many genes encoding proteins of unknown function, some genes encoding ribosomal proteins were transcriptionally up-regulated, which points to an adaptive reprogramming of the ribosomes under cold-shock conditions. Interestingly, the amount of mRNA specified by the operon ptb-bcd-buk-lpd-bkdA1-bkdA2-bkdB, which encodes enzymes involved in degradation of branched-chain amino acids, also increases after a temperature downshift. As cells utilize the isoleucine and valine degradation intermediates alpha-methylbutyryl-CoA and isobutyryl-CoA for synthesis of branched-chain fatty acids, this finding reflects the adaptation of membrane lipid composition, ensuring the maintenance of appropriate membrane fluidity at low temperatures. The results of the DNA array analyses were verified for several selected genes by RNA slot-blot analysis and compared with two-dimensional PAGE analyses.

Bacillus subtilis↗

PubMed2003

Integration of proteomics and genomics in platelets: a profile of platelet proteins and platelet-specific genes.

Platelets, while anucleate, contain RNA, some of which is translated into protein upon activation. Hypothesising that the platelet proteome is reflected in the transcriptome, we identified 82 proteins secreted from activated platelets and compared these, as well as published proteomic data, to the transcriptional profile. We also compared the transcriptome of platelets to other tissues to identify platelet-specific genes and used ontology to determine gene categories over-represented in platelets. RNA was isolated from highly pure platelet preparations for hybridization to Affymetrix oligonucleotide arrays. We identified 2,928 distinct messages as being present in platelets. The platelet transcriptome was compared with the proteome by relating both to UniGene clusters. Platelet proteomic data correlated well with the transcriptome, with 69% of secreted proteins detectable at the mRNA level, and similar concordance was obtained using two published datasets. While many of the most abundant mRNAs are for known platelet proteins, messages were detected for proteins not previously reported in platelets. Some of these may represent residual megakaryocyte messages; however, proteomic analysis confirmed the expression of many previously unreported genes in platelets. Transcripts for well-described platelet proteins are among the most platelet-specific messages. Ontological categories related to signal transduction, receptors, ion channels, and membranes are over-represented in platelets, while categories involved in protein synthesis are depleted. Despite the absence of gene transcription, the platelet proteome is mirrored in the transcriptome. Conversely, transcriptional analysis predicts the presence of novel proteins in the platelet. Transcriptional analysis is relevant to platelet biology, providing insights into platelet function and the mechanisms of platelet disorders.

Blood Platelets↗

PubMed2026

Distinct cell morphotypes of Aureobasidium melanogenum ZN exhibit differential functional profiles in promoting maize growth.

Black yeast-like fungi of the genus Aureobasidium exhibit morphological plasticity, but whether distinct cellular states within the same genetic background are associated with different plant growth-promoting functions remains unclear. Here, yeast-like cells (YL), swollen cells (SC), and chlamydospores (CH) of Aureobasidium melanogenum ZN were characterized. YL was associated mainly with siderophore production and laccase activity, SC with extracellular polysaccharide accumulation, and CH with phosphate mobilization and higher ammonia and IAA production. Whole-genome and comparative genomic analyses revealed a shared repertoire related to nutrient acquisition, auxin-associated metabolism, extracellular oxidation, and carbohydrate remodeling, with expansions in nutrient- and cell-surface-related gene families. Transcriptomic and metabolomic analyses showed distinct deployment of these capacities, with CH exhibiting broad reprogramming of tryptophan-associated, nitrogen, phosphate, central-carbon, and amino-acid metabolism. In maize, CH at the optimal inoculation concentration of 105 CFU·mL-1 produced the strongest growth promotion, increasing plant height, dry biomass, root length, root surface area, and root volume by 58.6%, 365.1%, 191.0%, 194.3%, and 222.4%, respectively. Consistent with this pronounced growth phenotype, maize root transcriptomics showed coordinated CH-induced responses involving root development, nutrient transport, redox regulation, and root-interface remodeling. Root-zone tracking showed greater short-term stability and persistence of CH. These findings identify cellular state as an important functional dimension of Aureobasidium-plant interactions and provide a basis for developing fungal inoculants with defined beneficial cellular states.

Zea mays↗

PubMed2026

Ten quick tips for spatial transcriptomics analysis.

Spatial transcriptomics (ST) enables genome-wide gene expression profiling while retaining spatial context within tissue sections. Since the foundational work by Ståhl et al. in 2016, the field has expanded rapidly, with diverse platforms now spanning sequencing-based (e.g., Visium, Visium HD, Slide-seq, Stereo-seq, and Seq-Scope) and imaging-based (e.g., MERFISH, Xenium, and CosMx SMI) approaches. The breadth of platforms, data structures, and computational tools, however, can be daunting for newcomers. Here, we present ten quick tips spanning the entire ST research workflow: whether ST suits a given biological question, how to select a platform aligned with study objectives, how to understand and process ST data, and which software tools to employ for analysis and visualization. We further discuss interpreting spatial patterns in biological context, integrating complementary modalities such as single-cell RNA sequencing and spatial proteomics, and leveraging public datasets and sharing results. Finally, we highlight current limitations of ST, particularly the challenge of reconstructing three-dimensional tissue architecture from serial tissue sections. This review provides biologists, bioinformaticians, and clinician-scientists with a concise, platform-neutral roadmap for incorporating ST into research, from experimental design to biological discovery.

Spatial Transcriptomics↗

PubMed2025

Integrative multi-omics profiling deciphers tumor microenvironment heterogeneity and immunotherapy vulnerabilities in lung neuroendocrine carcinomas.

INTRODUCTION: Lung neuroendocrine carcinomas (Lu-NECs) are rare, highly aggressive lung tumors with poor prognosis and limited therapeutic options. Understanding the tumor immune microenvironment (TIME) is crucial towards personalized therapeutic strategies. OBJECTIVES: This study aims to systematically characterize the heterogeneity and complexity of the TIME in Lu-NECs by integrating proteomic, transcriptomic, and genomic data. METHODS: We performed comprehensive immune-proteomic profiling of 76 Lu-NECs across diverse histopathological subtypes to elucidate intra-tumoral TIME heterogeneity at the proteomic level. Validation was conducted in multiple independent cohorts, including 112 Lu-NECs using immunohistochemistry, 147 Lu-NECs, and 17 small cell lung carcinoma samples using transcriptomics. We integrated proteomic, transcriptomic, genomic, and clinical data to assess molecular, immunological, and clinical features, as well as therapeutic vulnerabilities across different immune subtypes. RESULTS: We delineated the immuno-proteomic landscape of Lu-NECs and identified two major immuno-proteomic clusters with distinct immunological, molecular, and clinical characteristics. IPC1 was characterized by high immune cell infiltration, while IPC2 exhibited sparse immune cell presence. Genomic analysis revealed distinct mutational patterns, with IPC1 showing a higher incidence of APOBEC-associated mutation signatures and IPC2 being enriched for mutations associated with defective DNA mismatch repair and tobacco-related mutagens. Functional analyses indicated that IPC1 was related to immune and oncogenic signaling activity, whereas IPC2 was associated with cancer stemness and proliferation-related features. Furthermore, IPC1 and IPC2 demonstrated histological subtype-specific clinical benefits from postoperative chemotherapy. Finally, we developed a machine learning model (iPROM) to predict Lu-NECs immune classification and improve risk stratification, which was validated across multiple independent cohorts. CONCLUSIONS: This study advances the understanding of the tumor immune microenvironment in Lu-NECs through multi-omics characterization and highlights potential personalized therapeutic vulnerabilities tailored to the specific immune landscapes of Lu-NECs.

Humans↗

PubMed2026

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering.

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcriptomics, delineating higher-order anatomical structures is critical for understanding how cellular organization affects function. However, the reliability of current benchmarks of spatially aware clustering (SAC) methods is undermined by their narrow focus on Visium and brain tissue datasets and the incorrect interpretation of manual annotation as ground truth. Here we present SACCELERATOR, a community-driven, extensible framework that standardizes data formatting, method integration and metric evaluation, enabling rapid inclusion of new methods and datasets. Our analysis revealed substantial limitations in the generalizability and reproducibility of SAC methods and shows that anatomical labels commonly used as ground truths are often biased, error prone and unsuitable for benchmarking. Rather than ranking methods, we propose a consensus-guided workflow where descriptive spatial metrics highlight high-entropy regions of method disagreement, enabling targeted feedback for tissue experts. Applied to brain and cancer datasets, this approach uncovered biologically meaningful patterns overlooked by individual SAC methods and manual annotations, highlighting the need for iterative, expert-in-the-loop evaluation.

Benchmarking↗

PubMed2026

Identification of compounds that repress DUX4 expression in facioscapulohumeral muscular dystrophy.

Facioscapulohumeral muscular dystrophy (FSHD) is caused by epigenetic dysregulation of the disease locus, leading to pathogenic misexpression of DUX4 in skeletal muscle. Thus, most FSHD therapeutic approaches target DUX4. Our previous study identified the chromatin remodeling factor BAZ1A (bromodomain adjacent to zinc finger domain protein 1A) as a promising target for therapeutic development. Here we used an artificial intelligence-based screening pipeline to identify molecules predicted to bind the BAZ1A bromodomain, and validated hit compounds using FSHD-specific assays in FSHD myocytes. One compound, termed C06, emerged as a potent repressor of DUX4 and DUX4 target gene expression. Interestingly, while C06 exhibited binding to BAZ1A in vitro, it can also inhibit multiple kinases, including p38α, an upstream activator of DUX4. Despite this, at low doses C06 was an equally effective and more specific repressor of DUX4 than losmapimod, which is a robust and specific p38 inhibitor. At low concentrations, C06 returns the DUX4 gene expression signature to a healthier profile without major effects on the muscle transcriptome. Thus, C06 is a useful tool for potent and specific DUX4 suppression, and a viable candidate for further development. Our results highlight both the utility and limitations of AI for targeted drug discovery, and the importance of using an FSHD-specific functional screening strategy for selecting relevant candidates.

Muscular Dystrophy, Facioscapulohumeral↗

PubMed2006

Proteomic methods in nutrition.

PURPOSE OF REVIEW: Proteomics, the comprehensive analysis of a protein complement in a cell, tissue or biological fluid at a given time, is a key player in the family of -omic disciplines, which encompass genomics (gene analysis), transcriptomics (gene expression analysis) and metabolomics (metabolite profiling). This review summarizes the state of the art of proteomics technology and puts it into perspective for food-related research. Learning from proteomic experiences in the pharmaceutical context, this article may help to translate proteomics into nutrition and health. RECENT FINDINGS: Mass spectrometric technology has progressed enormously with regard to mass accuracy, resolution and peptide sequencing power. Likewise, upstream separation, depletion and enrichment techniques now allow us to deal with the large complexity and wide dynamic range of proteomic samples more efficiently. Consequently, proteomic studies now provide a broader, but still far from complete, coverage of a given proteome. SUMMARY: Proteomics adapted and applied to the context of nutrition and health has the potential to deliver biomarkers for health and comfort, reveal early indicators of disease disposition, assist in differentiating dietary responders from non-responders, and, last but not least, discover bioactive, beneficial food components.

Biomarkers↗

PubMed2002

The Chlamydomonas reinhardtii organellar genomes respond transcriptionally and post-transcriptionally to abiotic stimuli.

The Chlamydomonas reinhardtii plastid and mitochondrial transcriptomes were surveyed for changes in RNA profiles resulting from growth in 12 culture conditions representing 8 abiotic stimuli. Organellar RNA abundance exhibited marked changes during nutrient stress and exposure to UV light, as revealed by both RNA gel blot and DNA microarray analyses. Of particular note were large increases in tufA and clpP transcript abundance during nutrient limitation. Phosphate and sulfur limitation resulted in the most global, yet opposite, effects on organellar RNA abundance, changes that were dissected further using run-on transcription assays. Removal of sulfate from the culture medium, which is known to reduce photosynthesis, resulted in 2-fold to 10-fold decreases in transcription rates, which were reflected in lower RNA abundance. The decrease in transcriptional activity was completely reversible and recovered to twice the control level after sulfate replenishment. Conversely, phosphate limitation resulted in a twofold to threefold increase in RNA abundance that was found to be a post-transcriptional effect, because it could be accounted for by increased RNA stability. This finding is consistent with the known metabolic slowdown under phosphate stress. Additionally, inhibitor studies suggested that unlike those in higher plants, Chlamydomonas chloroplasts lack a nucleus-encoded plastid RNA polymerase. The apparently single type of polymerase could contribute to the rapid and genome-wide transcriptional responses observed within the chloroplast.

Animals↗