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PubMed2026

Sympatric European white oaks species display contrasting epigenetic response to soil water availability.

In the context of climate change plants have to cope with adverse conditions, among which water scarcity is a major threat for their survival. They have developed diverse regulatory processes to face drought that may differ depending on their ecological niche. The two sympatric oaks species (Quercus robur L. and Quercus petraea (Matt.). Liebl) have different levels of drought tolerance. We have investigated their strategies to face drought stress by analysing the transcriptome, small RNAome and methylome dynamics of young plants grown under control and drought stress conditions. Data indicate that cell wall remodeling is most likely involved in the better tolerance Q. petraea than of Q. robur. Furthermore, major methylation differences were identified between both oak species that were in part associated to their difference in drought stress responses. Integration of the three datasets revealed genomic co-locations of potential importance for forest tree adaptation to drought stress. Our data are consistent with species-specific molecular responses of oak to drought stress related to their ecological niches.

Forest trees- Omics- ecological niche↗

PubMed2005

Changes of anti-oxidative enzymes and MDA content under soil water deficits among 10 wheat (Triticum aestivum L.) genotypes at maturation stage.

Drought is a world-spread problem seriously influencing grain production and quality, the loss of which is the total for other natural disasters, with increasing global climate change making the situation more serious. Wheat is the staple food for more than 35% of world population, so wheat anti-drought physiology study is of importance to wheat production and biological breeding for the sake of coping with abiotic and biotic conditions. Much research is involved in this hot topic, but the pace of progress is not so large because of drought resistance being a multiple-gene-control quantitative character and wheat genome being larger (16,000Mb). On the other hand, stress adaptive mechanisms are quite different, with stress degree, time course, materials, soil quality status and experimental plots, thus increasing the complexity of the issue in question. Additionally, a little study is related to the whole life circle of wheat, which cannot provide a comprehensive understanding of its anti-drought machinery. We selected 10 kinds of wheat genotypes as materials, which have potential to be applied in practice, and measured change of relative physiological indices through wheat whole growing-developmental circle (i.e. seedling, tillering and maturing). Here, we reported the anti-oxidative results of maturation stage (the results of seedling and tillering stage have been published) in terms of activities of POD, SOD, CAT and MDA content as follows: (1) 10 wheat genotypes can be grouped into three kinds (A-C, respectively) according to their changing trend of the measured indices; (2) A group performed better resistance drought under the condition of treatment level 1 (appropriate level), whose activities of anti-oxidative enzymes (POD, SOD, CAT) were higher and MDA lower; (3) B group exhibited stronger anti-drought under treatment level 2 (light-stress level), whose activities of anti-oxidative enzymes were higher and MDA lower; (4) C group expressed anti-drought to some extent under treatment level 3 (serious-stress level), whose activities of anti-oxidative enzymes were stronger, MDA lower; (5) these results demonstrated that different wheat genotypes have different physiological mechanisms to adapt themselves to changing drought stress, whose molecular basis is discrete gene expression profiling (transcriptom); (6) our results also showed that the concept and method accepted and adopted by most researchers [T.C. Hsiao, Plant response to water stress, Ann. Rev. Plant Physiol. 24 (1973) 519-570], that 75% FC is a proper supply for higher plants, was doubted, because this level could not reflect the true suitable level of different wheat genotypes. The study in this respect is the key to wheat anti-drought and biological-saving water agriculture; (7) our research can provide insights into physiological mechanisms of crop anti-drought and direct practical materials for wheat anti-drought breeding; (8) the physiological study of wheat is more urgent up-to-date and molecular aspects are needed, but cannot substitute this important part. The combination of both is an important strategy and a key and (9) POD, SOD and CAT activities and MDA content of different wheat genotypes had quite different changing trend at different stages and under different soil water stress conditions, which was linked with their origin of cultivation and individual soil water threshold.

Antioxidants↗

PubMed2006

Genome-wide differential gene expression in children exposed to air pollution in the Czech Republic.

The Teplice area in the Czech Republic is a mining district where elevated levels of air pollution including airborne carcinogens, have been demonstrated, especially during winter time. This environmental exposure can impact human health; in particular children may be more vulnerable. To study the impact of air pollution in children at the transcriptional level, peripheral blood cells were subjected to whole genome response analysis, in order to identify significantly modulated biological pathways and processes as a result of exposure. Using genome-wide oligonucleotide microarrays, we investigated differential gene expression in children from the Teplice area (n=23) and compared them with children from the rural control area of Prachatice (n=24). In an additional approach, individual gene expressions were correlated with individual peripheral blood lymphocyte micronuclei frequencies, in order to evaluate the linkage of individual gene expressions with an established biomarker of effect that is representative for increased genotoxic risk. Children from the Teplice area showed a significantly higher average micronuclei frequency than Prachatice children (p=0.023). For considerable numbers of genes, the expression differed significantly between the children from the two areas. Amongst these genes, considerable numbers of genes were observed to correlate significantly with the frequencies of micronuclei. The main biological process that appeared significantly affected overall was nucleosome assembly. This suggests an effect of air pollution on the primary structural unit of the condensed DNA. In addition, several other pathways were modulated. Based on the results of this study, we suggest that transcriptomic analysis represents a promising biomarker for environmental carcinogenesis.

Air Pollutants↗

PubMed2024

The Genetic Determinants and Genomic Consequences of Non-Leukemogenic Somatic Point Mutations.

Clonal hematopoiesis (CH) is defined by the expansion of a lineage of genetically identical cells in blood. Genetic lesions that confer a fitness advantage, such as point mutations or mosaic chromosomal alterations (mCAs) in genes associated with hematologic malignancy, are frequent mediators of CH. However, recent analyses of both single cell-derived colonies of hematopoietic cells and population sequencing cohorts have revealed CH frequently occurs in the absence of known driver genetic lesions. To characterize CH without known driver genetic lesions, we used 51,399 deeply sequenced whole genomes from the NHLBI TOPMed sequencing initiative to perform simultaneous germline and somatic mutation analyses among individuals without leukemogenic point mutations (LPM), which we term CH-LPMneg. We quantified CH by estimating the total mutation burden. Because estimating somatic mutation burden without a paired-tissue sample is challenging, we developed a novel statistical method, the Genomic and Epigenomic informed Mutation (GEM) rate, that uses external genomic and epigenomic data sources to distinguish artifactual signals from true somatic mutations. We performed a genome-wide association study of GEM to discover the germline determinants of CH-LPMneg. After fine-mapping and variant-to-gene analyses, we identified seven genes associated with CH-LPMneg (TCL1A, TERT, SMC4, NRIP1, PRDM16, MSRA, SCARB1), and one locus associated with a sex-associated mutation pathway (SRGAP2C). We performed a secondary analysis excluding individuals with mCAs, finding that the genetic architecture was largely unaffected by their inclusion. Functional analyses of SMC4 and NRIP1 implicated altered HSC self-renewal and proliferation as the primary mediator of mutation burden in blood. We then performed comprehensive multi-tissue transcriptomic analyses, finding that the expression levels of 404 genes are associated with GEM. Finally, we performed phenotypic association meta-analyses across four cohorts, finding that GEM is associated with increased white blood cell count and increased risk for incident peripheral artery disease, but is not significantly associated with incident stroke or coronary disease events. Overall, we develop GEM for quantifying mutation burden from WGS without a paired-tissue sample and use GEM to discover the genetic, genomic, and phenotypic correlates of CH-LPMneg.

Journal Article↗

PubMed2025

Stochastic epigenetic mutation profiles as biomarkers of clinical activity in juvenile idiopathic arthritis: a multi-omic machine learning approach for gene prioritization.

BACKGROUND: Juvenile idiopathic arthritis (JIA) is a rare autoimmune disease arising from a complex interplay between genetic and environmental factors. Epigenetic modifications such as DNA methylation (DNAm) have been described as potential mediators in gene-environment interactions, contributing to immune system dysregulation. Emerging evidence suggests that DNAm profiles also predict therapeutic responses in autoimmune diseases. This study aims to identify epigenetic biomarkers and epigenetic-driven gene expression changes associated with JIA clinical activity. METHODS: We reanalyzed a publicly available dataset of 44 JIA patients, with whole-genome DNAm and gene expression from CD4 + T cells measured at two points: at anti-TNF therapy withdrawal (T0) and eight months later (Tend). At Tend, 30 patients maintained inactive disease (ID) while 14 did not (NO ID). We investigated differences between ID and NO ID patients in the epigenetic mutation load and various epigenetic clocks through linear regression models, and prioritized genomic regions with significantly higher number of epimutations in NO ID patients through machine learning. RESULTS: We found a higher mutation load in NO ID than ID patients, both at T0 and at Tend, with the differences at Tend reaching statistical significance (p = 0.02). In contrast, we found no evidence of association between epigenetic clocks and JIA clinical activity. Using a multi-omic approach, we identified a List of candidate epigenetically-driven differentially expressed genes, 80 up-regulated and 77 down-regulated, in NO ID patients. Finally, comparing our candidate gene list with the Connectivity Map database, we identified new candidate potential therapeutic targets. Key findings were validated in independent datasets: DNAm profiles from CD4 + T cells (56 JIA patients, 57 controls) and transcriptomic data from PBMCs of JIA patients with active or inactive disease, confirming dysregulation of pathways such as TNF-α signaling via NF-kB and TGF-β signaling among others. CONCLUSIONS: We described a significant association of epigenetic mutations with JIA clinical activity, indicating that epigenetic changes might precede clinical symptoms and may serve as biomarkers for early disease monitoring. Further, our results shed light on biomolecular mechanisms of JIA, supporting the development of more effective treatments.

Humans↗

PubMed2006

Global transcriptional and physiological responses of Saccharomyces cerevisiae to ammonium, L-alanine, or L-glutamine limitation.

The yeast Saccharomyces cerevisiae encounters a range of nitrogen sources at various concentrations in its environment. The impact of these two parameters on transcription and metabolism was studied by growing S. cerevisiae in chemostat cultures with l-glutamine, l-alanine, or l-ammonium in limitation and by growing cells in an excess of ammonium. Cells grown in l-alanine-limited cultures had higher biomass yield per nitrogen mole (19%) than those from ammonium-limited cultures. Whole-genome transcript profiles were analyzed with a genome-scale metabolic model that suggested increased anabolic activity in l-alanine-limited cells. The changes in these cells were found to be focused around pyruvate, acetyl coenzyme A, glyoxylate, and alpha-ketoglutarate via increased levels of ALT1, DAL7, PYC1, GDH2, and ADH5 and decreased levels of GDH3, CIT2, and ACS1 transcripts. The transcript profiles were then clustered. Approximately 1,400 transcripts showed altered levels when amino acid-grown cells were compared to those from ammonium. Another 400 genes had low transcript levels when ammonium was in excess. Overrepresentation of the GATAAG element in their promoters suggests that nitrogen catabolite repression (NCR) may be responsible for this regulation. Ninety-one genes had transcript levels on both l-glutamine and ammonium that were decreased compared to those on l-alanine, independent of the concentration. The GATAAG element in these genes suggests two groups of NCR-responsive genes, those that respond to high levels of nitrogen and those that respond to levels below 30 muM. In conclusion, our results reveal that the nitrogen source has substantial influence on the transcriptome of yeasts and that transcriptional changes may be correlated to physiology via a metabolic model.

Alanine↗

PubMed2006

Bioinformatic screening of human ESTs for differentially expressed genes in normal and tumor tissues.

BACKGROUND: Owing to the explosion of information generated by human genomics, analysis of publicly available databases can help identify potential candidate genes relevant to the cancerous phenotype. The aim of this study was to scan for such genes by whole-genome in silico subtraction using Expressed Sequence Tag (EST) data. METHODS: Genes differentially expressed in normal versus tumor tissues were identified using a computer-based differential display strategy. Bcl-xL, an anti-apoptotic member of the Bcl-2 family, was selected for confirmation by western blot analysis. RESULTS: Our genome-wide expression analysis identified a set of genes whose differential expression may be attributed to the genetic alterations associated with tumor formation and malignant growth. We propose complete lists of genes that may serve as targets for projects seeking novel candidates for cancer diagnosis and therapy. Our validation result showed increased protein levels of Bcl-xL in two different liver cancer specimens compared to normal liver. Notably, our EST-based data mining procedure indicated that most of the changes in gene expression observed in cancer cells corresponded to gene inactivation patterns. Chromosomes and chromosomal regions most frequently associated with aberrant expression changes in cancer libraries were also determined. CONCLUSION: Through the description of several candidates (including genes encoding extracellular matrix and ribosomal components, cytoskeletal proteins, apoptotic regulators, and novel tissue-specific biomarkers), our study illustrates the utility of in silico transcriptomics to identify tumor cell signatures, tumor-related genes and chromosomal regions frequently associated with aberrant expression in cancer.

Algorithms↗

PubMed2006

A comparison of transcriptomic and metabonomic technologies for identifying biomarkers predictive of two-year rodent cancer bioassays.

Two-year rodent bioassays play a central role in evaluating the carcinogenic potential of both commercial products and environmental contaminants. The bioassays are expensive and time consuming, requiring years to complete and costing $2-4 million. In this study, we compare transcriptomic and metabonomic technologies for discovering biomarkers that can efficiently and economically identify chemical carcinogens without performing a standard two-year rodent bioassay. Animals were exposed subchronically to two chemicals (one genotoxic and one nongenotoxic) that were positive for lung and liver tumors in a standard two-year bioassay, two chemicals that were negative, and two control groups. Microarray analysis performed on liver and lung tissues identified multiple biomarkers in each tissue that could discriminate between carcinogenic and noncarcinogenic treatments. The discriminating biomarkers shared a common expression profile among carcinogenic treatments despite different genotoxicity categories and potential modes of action, suggesting that they reflect underlying cellular changes in the transition toward neoplasia. Statistical classification analysis exhibited 100% accuracy in both tissues when the number of genes was less than 5000. Additional genes reduced the predictive accuracy of the model. Serum samples were analyzed by 1H nuclear magnetic resonance (NMR) spectroscopy, and chemical-specific metabolites were removed from the spectra. The statistical classification analysis of the endogenous serum metabolites showed relatively low predictive accuracy with few metabolites in the model, but the accuracy increased to a maximum of 94% when all metabolites were added. These results suggest that individual endogenous metabolites are relatively poor biomarkers, but the metabolite profile as a whole is altered following carcinogen treatment.

Animals↗

PubMed2007

In silico whole-genome screening for cancer-related single-nucleotide polymorphisms located in human mRNA untranslated regions.

BACKGROUND: A promising application of the huge amounts of genetic data currently available lies in developing a better understanding of complex diseases, such as cancer. Analysis of publicly available databases can help identify potential candidates for genes or mutations specifically related to the cancer phenotype. In spite of their huge potential to affect gene function, no systematic attention has been paid so far to the changes that occur in untranslated regions of mRNA. RESULTS: In this study, we used Expressed Sequence Tag (EST) databases as a source for cancer-related sequence polymorphism discovery at the whole-genome level. Using a novel computational procedure, we focused on the identification of untranslated region (UTR)-localized non-coding Single Nucleotide Polymorphisms (UTR-SNPs) significantly associated with the tumoral state. To explore possible relationships between genetic mutation and phenotypic variation, bioinformatic tools were used to predict the potential impact of cancer-associated UTR-SNPs on mRNA secondary structure and UTR regulatory elements. We provide a comprehensive and unbiased description of cancer-associated UTR-SNPs that may be useful to define genotypic markers or to propose polymorphisms that can act to alter gene expression levels. Our results suggest that a fraction of cancer-associated UTR-SNPs may have functional consequences on mRNA stability and/or expression. CONCLUSION: We have undertaken a comprehensive effort to identify cancer-associated polymorphisms in untranslated regions of mRNA and to characterize putative functional UTR-SNPs. Alteration of translational control can change the expression of genes in tumor cells, causing an increase or decrease in the concentration of specific proteins. Through the description of testable candidates and the experimental validation of a number of UTR-SNPs discovered on the secreted protein acidic and rich in cysteine (SPARC) gene, this report illustrates the utility of a cross-talk between in silico transcriptomics and cancer genetics.

Computational Biology↗

PubMed2026

Exploring the Effect of Whole-Genome Duplication on Salmonid LincRNA Repertoire.

Long intergenic non-coding RNAs (lincRNAs) are key epigenetic regulators of genome function, yet their evolutionary dynamics following whole-genome duplication (WGD) events remain poorly understood. Salmonids, which underwent a lineage-specific autotetraploidization (salmonid-specific WGD, ~88-100 million years ago), provide an excellent model to investigate the retention, divergence, and functional potential of recently duplicated non-coding elements. LincRNA repertoires were compared across five genome-annotated salmonids (Oncorhynchus tshawytscha, O. kisutch, O. mykiss, Salmo salar, and S. trutta) and their closest non-duplicated relative, northern pike (Esox lucius). LincRNAs represented ~5-7% of annotated genes in all salmonids except S. salar (18%). Sequence conservation was low relative to coding genes, with only 11-68 highly similar (e-value < 1 × 10-30; similarity > 70% and alignments > 100 nucleotides) putative orthologues shared between salmonids and northern pike, and 161-338 among salmonids alone. Synteny conservation was modest in lincRNAs, with lower conservation in putative orthologues (8-16%) compared to putative ohnologues (8-33%). Secondary structure conservation was associated with sequence similarity (ρ = -0.45; p = 2.2 × 10-16), and the association was stronger among WGD ohnologues than orthologues. In S. salar and O. mykiss, lincRNA putative ohnologues showed weaker expression correlations than coding genes, suggesting widespread regulatory divergence, possibly through neo- and subfunctionalisation. Conserved salmonid lincRNAs showed enriched predicted interactions with miRNAs involved in tumour suppression, brain, bone, and muscle development (e.g., miR-455, miR-365, miR124, miR-133a, miR-140, and miR-9), a finding supported by limited transcriptomic data. Although salmonid WGD expanded lincRNA repertoires, lincRNAs have undergone rapid sequence and transcriptional divergence, with limited conservation across species based on sequence similarity, chromosomal position, synteny, and secondary structure. A subset of conserved lincRNAs retains structural features and regulatory signatures consistent with roles as miRNA sponges in brain, skeletal, and muscle development and tumour suppression, potentially acting within conserved regulatory networks. These findings provide new insights into lincRNA evolution following genome duplication and highlight the need for experimental validation of their regulatory functions.

Animals↗

PubMed2026

An Aspergillus luchuensis isolated from a patient with hemoptysis insights from a comprehensive genome-based analysis: Case report.

RATIONALE: Asp luchuensis, a member of the A niger group, is widely used in food fermentation and rarely causes invasive pulmonary aspergillosis (IPA) in humans. Clinical cases of IPA induced by this strain are extremely scarce, and its genomic characteristics, virulence profiles, and pathogenic mechanisms remain poorly understood, resulting in insufficient clinical recognition of its invasive infection potential. PATIENT CONCERNS: A 57-year-old immunocompetent non-neutropenic male patient with a long-term smoking and drinking history presented with unexplained severe cough and massive hemoptysis (approximately100 mL) without other typical infectious symptoms. DIAGNOSES: Combined with chest computed tomography (CT) inflammatory lesions, positive galactomannan test, fungal PCR and metagenomic next-generation sequencing results, the patient was definitively diagnosed with probable A luchuensis-induced IPA. Genomic and transcriptomic analyses confirmed the pathogen as a variant A luchuensis strain with 3 key hypervirulence genes, highly active mitochondrial energy metabolism, and no specific antifungal resistance genes. INTERVENTIONS: The patient received standardized intravenous antifungal combination therapy with voriconazole and amphotericin B after confirmed diagnosis. OUTCOMES: The patient's cough and hemoptysis were significantly relieved after 10 days of treatment, with stable vital signs and no adverse drug reactions or disease progression. LESSONS: A luchuensis possesses strong invasive pathogenicity and can trigger IPA even in non-neutropenic immunocompetent individuals. Negative conventional microbial tests cannot exclude its infection, and mNGS is a reliable diagnostic tool. This strain is susceptible to routine antifungal drugs, and clinicians should raise awareness of atypical Asp species-induced invasive pulmonary infections.

Humans↗

PubMed2026

Single-organ proteomics in Drosophila melanogaster larva.

The combination of genetic accessibility, organ complexity, evolutionary conservation, and cost-efficiency makes Drosophila melanogaster (Dm) a well-known model system for biomedical and fundamental biological research. Proteomic analysis of single organs enables the identification and quantification of proteins expressed in specific organs. This will help to uncover specific biological functions and unique protein profiles that are not detectable in whole-organism analyses. In this study we have isolated single organs form Dm larvae, and we have performed a deep proteomics mapping by following a minimal manipulation preparation procedure. The combined dataset across all organs comprised 9132 identified proteins. As anticipated, principal component analysis (PCA) revealed clear separation between the proteomes of most organs, confirming distinct protein profiles. These findings demonstrate the applicability of the sample preparation strategy for high-resolution proteomic characterization of individual organs in Drosophila. Given the extensive genetic tools available for this model organism, our approach has the potential to open new avenues for proteomic studies in Drosophila melanogaster and any other biological systems where the sample amount is limiting. SIGNIFICANCE STATEMENT: Drosophila melanogaster is a well-known model system for biomedical and fundamental biological research that serves as a valuable in vivo model organism due to its high degree of evolutionary conservation with higher vertebrates, tractable genetics, and logistical efficiency. However, the proteome of Drosophila at single organ level has been elusive to date, due to several factors like low sensitivity of previous generation mass spectrometers and sample preparation procedures, difficult isolation of some organs. In this study we have applied a compilation of advanced methods including minimal sample manipulation together with simple, straightforward and efficient protein extraction and digestion methods. Obtained peptides were minimally handled to be analyzed by applying specific and sensitive nLC methods coupled on-line to state-of-the-art MS/MS system. Altogether, the applied strategy allowed us to get the first single organ study to date for this animal. These datasets represent a significative resource for future genomic, transcriptomic and proteomic studies in Drosophila, as multi-omic integration requires deep proteomics to translate data into functional biochemistry, and serves as a critical bridge and an indispensable standalone resource across the genomic, transcriptomic, and proteomic landscapes.

Animals↗

PubMed2026

Longitudinal dynamics of gene expression and metabolomics in an aging population cohort.

Multiomic profiling provides a comprehensive physiological overview at the molecular level, but understanding of its spatiotemporal dynamics remains limited in human populations. We profiled longitudinal whole-blood gene expression and metabolite levels in 335 females over 8 years. Levels of 5061 genes and 181 metabolites changed over time, with individual trajectories often diverging from population-level trends. Longitudinally variable genes showed cell type specificity and enrichment for aging-relevant pathways, including cardiometabolic and neurodegenerative disorders. Longitudinal trajectories were further shaped by genetics, circadian rhythm, seasonality, and environmental pollutant exposures. Integrative analyses revealed extensive static and time-variable cross-omic connectivity. Longitudinal profiling offers insight into the temporal evolution of age-related conditions at the molecular level, and understanding individual variation within these longitudinal patterns will be essential for future precision medicine approaches.

Female↗

PubMed2026

A longitudinal single-cell and spatial multiomic atlas of pediatric high-grade glioma.

Pediatric high-grade glioma (pHGG) is an incurable central nervous system malignancy that is a leading cause of pediatric cancer death. While pHGG shares many similarities with adult glioma, it comprises distinct disease entities. In this study, we longitudinally profile a molecularly diverse cohort of 16 pHGG patients through single-nucleus RNA and ATAC sequencing, whole-genome sequencing, and CODEX spatial proteomics to capture the evolution of neoplastic and microenvironmental features during disease progression and treatment. We define a set of core pHGG neoplastic cell states and observe differential tumor-myeloid interactions between malignant cell phenotypes. We find that essential neuromodulators and the interferon response are upregulated post-therapy, implicating them as malignant cell-intrinsic targets. We observe an increase in oligodendrocytes upon progression and that they coordinate spatial motifs with proneural tumor cells. This multiomic atlas of longitudinal pHGG captures features of therapy response and provides a scalable reference for the study of pediatric brain tumors.

Humans↗

PubMed2026

Isoform-Level Analysis Reveals Reproducible Early Changes in Transcript Usage During Human Vaccine Responses.

Vaccine-induced transcriptional responses have been extensively characterized at the gene level, but whether vaccination also alters transcript isoform usage remains largely unexplored. Here, we reanalyzed longitudinal whole-blood RNA-seq data from a discovery cohort of mRNA COVID-19 vaccine recipients using the IsoformSwitchAnalyzeR framework and validated the findings in an independent cohort. Key findings were validated by full-length RNA long-read sequencing and extended to four additional vaccine cohorts covering distinct platforms and pathogens. mRNA vaccination induced a rapid and transient wave of differential transcript usage, peaking at 24 h post-vaccination with 131 isoforms significantly altered across 107 genes, before largely resolving by Day 14. Isoform switching events were reproducible across independent cohorts and confirmed by full-length RNA long-read sequencing. Structural annotation of switching transcripts, including RMI2, WARS1, and NT5C3A, revealed changes affecting predicted protein domains and signal peptides. Notably, highly concordant isoform switching patterns were observed across MVA-based SARS-CoV-2, influenza, and Ebola vaccine cohorts and showed dose-dependent modulation. Overall, differential transcript isoform usage is a rapid and transient feature of the early human immune response to vaccination that was observed across multiple vaccine platforms. These findings reveal an underappreciated layer of transcriptional regulation that complements conventional gene-level analyses and warrants integration into future vaccine immunogenicity studies.

Humans↗

PubMed2004

Adaptation of enzymes to temperature: searching for basic "strategies".

The pervasive influence of temperature on biological systems necessitates a suite of temperature--compensatory adaptations that span all levels of biological organization--from behavior to fine-scale molecular structure. Beginning about 50 years ago, physiological studies conducted with whole organisms or isolated tissues, by such pioneers of comparative thermal physiology as V.Ya. Alexandrov, T.H. Bullock, F.E.J. Fry, H. Precht, C.L. Prosser, and P.F. Scholander, began to document in detail the abilities of ectothermic animals to sustain relatively similar rates of metabolic activity at widely different temperatures of adaptation or acclimation. These studies naturally led to investigation of the roles played by enzymatic proteins in metabolic temperature compensation. Peter Hochachka's laboratory became an epicenter of this new focus in comparative physiology. The studies of the enzyme lactate dehydrogenase (LDH) that he initiated as a PhD student at Duke University in the mid-1960s and continued for several years at the University of British Columbia laid much of the foundation for subsequent studies of protein adaptation to temperature. Studies of orthologs of LDH have revealed the importance of conserving kinetic properties (catalytic rate constants (kcat) and Michaelis-Menten constants (Km) and structural stability during adaptation to temperature, and recently have identified the types of amino acid substitutions causing this adaptive variation. The roles of pH and low-molecular-mass organic solutes (osmolytes) in conserving the functional and structural properties of enzymes also have been elucidated using LDH. These studies, begun in Peter Hochachka's laboratory almost 40 years ago, have been instrumental in the development of a conceptual framework for the study of biochemical adaptation, a field whose origin can be traced largely to his creative influences. This framework emphasizes the complementary roles of three "strategies" of adaptation: (1) changes in amino acid sequence that cause adaptive variation in the kinetic properties and stabilities of proteins, (2) shifts in concentrations of proteins, which are mediated through changes in gene expression and protein turnover; and (3) changes in the milieu in which proteins function, which conserve the intrinsic properties of proteins established by their primary structure and modulate protein activity in response to physiological needs. This theoretical framework has helped guide research in adaptational biochemistry for many years and now stands poised to play a critical role in the post-genomic era, as physiologists grapple with the challenge of integrating the wealth of new data on gene sequences (genome), gene expression (transcriptome and proteome), and metabolic profiles (metabolome) into a realistic physiological context that takes into account the evolutionary histories and environmental relationships of species.

Adaptation, Physiological↗

PubMed2025

Dual RNA isolation from blood: an optimized protocol for host and bacterial RNA purification for dual RNA-sequencing analysis in whole blood sepsis samples.

Dual RNA-sequencing (dual RNA-seq) holds significant promise for deciphering bacterial virulence mechanisms during systemic infections. However, its application in sepsis research is hindered by technical challenges, including a low bacterial burden in blood and limited sample volumes and RNA yield from vulnerable populations, such as neonates. We developed an optimized protocol [dual RNA isolation from blood (DRIB)] for simultaneous stabilization, isolation and purification of high-quality host leukocyte and bacterial RNA from low-volume whole blood samples (0.5 ml). This protocol is compatible with clinical sample collection workflows and high-throughput RNA sequencing. The feasibility of DRIB for dual RNA-seq was validated using a pilot cohort of clinical adult sepsis samples, enabling the investigation of host-bacterial gene expression during sepsis. The DRIB protocol yielded 2.10-6.91 µg of total RNA per clinical sample in our pilot cohort. Dual-species ribosomal RNA (rRNA) depletion and RNA-seq generated 16.6-24.8 million filtered reads per sample, with 63±7% of reads uniquely mapped to host or bacterial sequences. Host genes accounted for 51-68% (8.4-10.9 million) reads, while 0.5-6.7% (79,496-789,808 reads) mapped to bacterial genomes. Bioinformatic analysis revealed that both shared and individual transcriptional patterns were identified in host and bacterial responses, including pathways related to immune metabolism and metal-ion binding. Our optimized DRIB protocol and RNA-seq pipeline effectively captured both host and bacterial RNA transcription in clinical sepsis samples. Expanding this approach to larger cohorts and varying disease timepoints will provide crucial new insights into host-bacterial gene co-expression dynamics in sepsis progression and outcomes.

Humans↗