Dev Cell. 2024 Dec 9:S1534-5807(24)00699-3. doi: 10.1016/j.devcel.2024.11.017. Online ahead of print.

ABSTRACT

Transitional cell states are at the crossroads of crucial developmental and regenerative events, yet little is known about how these states emerge and influence outcomes. The alveolar and airway epithelia arise from distal lung multipotent progenitors, which undergo cell fate transitions to form these distinct compartments. The identification and impact of cell states in the developing lung are poorly understood. Here, we identified a population of Icam1/Nkx2-1 epithelial progenitors harboring a transitional state program remarkably conserved in humans and mice during lung morphogenesis and regeneration. Lineage-tracing and functional analyses reveal their role as progenitors to both airways and alveolar cells and the requirement of this transitional program to make distal lung progenitors competent to undergo airway cell fate specification. The identification of a common progenitor cell state in vastly distinct processes suggests a unified program reiteratively regulating outcomes in development and regeneration.

PMID:39667932 | DOI:10.1016/j.devcel.2024.11.017

Environ Microbiol. 2024 Dec;26(12):e70012. doi: 10.1111/1462-2920.70012.

ABSTRACT

The canonical arsRBC genes of the ars1 operon in Pseudomonas putida KT2440, which confer tolerance to arsenate and arsenite, are followed by a series of additional ORFs culminating in phoN1. The phoN1 gene encodes an acetyltransferase that imparts resistance to the glutamine synthetase inhibitor herbicide phosphinothricin (PPT). The co-expression of phoN1 and ars genes in response to environmental arsenic, along with the physiological effects, was analysed through transcriptomics of cells exposed to the oxyanion and phenotypic characterization of P. putida strains deficient in different components of the bifan motif governing arsenic resistance in this bacterium. Genetic separation of arsRBC and phoN1 revealed that their associated phenotypes operate independently, indicating that their natural co-regulation is not functionally required for simultaneous response to the same signal. The data suggest a scenario of associative evolution, akin to Pavlovian conditioning, where two unrelated but frequently co-occurring signals result in one regulating the other's response - even if there is no functional link between the signal and the response. Such surrogate regulatory events may provide an efficient solution to complex regulatory challenges and serve as a genetic patch to address transient gaps in evolving regulatory networks.

PMID:39667752 | DOI:10.1111/1462-2920.70012

Bioconjug Chem. 2024 Dec 12. doi: 10.1021/acs.bioconjchem.4c00426. Online ahead of print.

ABSTRACT

Cancer-associated fibroblasts (CAFs) expressing fibroblast activation protein alpha (FAP) are abundant in tumor microenvironments and represent an emerging target for PET cancer imaging. While different quinolone-based small molecule agents have been developed for whole-body imaging, there is a scarcity of well-validated fluorescent small molecule imaging agents to better study these cells in vivo. Here, we report the synthesis and characterization of a series of fluorescent FAP imaging agents based on the common quinolone azide inhibitor. Our data show excellent performance of some synthesized FAP Targeting Fluorescent probes (FTFs) for both topical application and intravenous delivery to label CAF populations in solid tumors. These results suggest that FTF can be used to study CAF biology and therapeutic targeting in vivo.

PMID:39667730 | DOI:10.1021/acs.bioconjchem.4c00426

Vascul Pharmacol. 2024 Dec 10:107452. doi: 10.1016/j.vph.2024.107452. Online ahead of print.

ABSTRACT

Despite the discovery and prevalent clinical use of potent lipid-lowering therapies, including statins and PCSK9 inhibitors, cardiovascular diseases (CVD) caused by atherosclerosis remain a large unmet clinical need, accounting for frequent deaths worldwide. The pathogenesis of atherosclerosis is a complex process underlying the presence of modifiable and non-modifiable risk factors affecting several cell types including endothelial cells (ECs), monocytes/macrophages, smooth muscle cells (SMCs) and T cells. Heterogeneous composition of the plaque and its morphology could lead to rupture or erosion causing thrombosis, even a sudden death. To decipher this complexity, various cell model systems have been developed. With recent advances in systems biology approaches and single or multi-omics methods researchers can elucidate specific cell types, molecules and signalling pathways contributing to certain stages of disease progression. Compared with animals, in vitro models are economical, easily adjusted for high-throughput work, offering mechanistic insights. Hereby, we review the latest work performed employing the cellular models of atherosclerosis to generate a variety of omics data. We summarize their outputs and the impact they had in the field. Challenges in the translatability of the omics data obtained from the cell models will be discussed along with future perspectives.

PMID:39667548 | DOI:10.1016/j.vph.2024.107452

Cell Genom. 2024 Dec 11;4(12):100721. doi: 10.1016/j.xgen.2024.100721.

ABSTRACT

Copy-number variants (CNVs) that increase the risk for neurodevelopmental disorders also affect cognitive ability. However, such CNVs remain challenging to study due to their scarcity, limiting our understanding of gene-dosage-sensitive biological processes linked to cognitive ability. We performed a genome-wide association study (GWAS) in 258,292 individuals, which identified-for the first time-a duplication at 2q12.3 associated with higher cognitive performance. We developed a functional-burden analysis, which tested the association between cognition and CNVs disrupting 6,502 gene sets biologically defined across tissues, cell types, and ontologies. Among those, 864 gene sets were associated with cognition, and effect sizes of deletion and duplication were negatively correlated. The latter suggested that functions across all biological processes were sensitive to either deletions (e.g., subcortical regions, postsynaptic) or duplications (e.g., cerebral cortex, presynaptic). Associations between non-brain tissues and cognition were driven partly by constrained genes, which may shed light on medical comorbidities in neurodevelopmental disorders.

PMID:39667348 | DOI:10.1016/j.xgen.2024.100721

Cell Host Microbe. 2024 Dec 11;32(12):2037-2038. doi: 10.1016/j.chom.2024.10.018.

ABSTRACT

Fungal-bacterial endosymbioses, the most intimate typology of symbioses, have been described in different taxa of Mucoromycota, an early diverging group of Fungi. In a recent issue of Nature, Giger and colleagues describe how they implanted a Burkolderia-related microbe inside a Mucoromycota fungus, giving rise to a functional and stable endosymbiosis.

PMID:39667341 | DOI:10.1016/j.chom.2024.10.018

Angew Chem Int Ed Engl. 2024 Dec 12:e202422075. doi: 10.1002/anie.202422075. Online ahead of print.

ABSTRACT

Versatile DNA and polypeptide-based structures have been designed based on complementary modules. However, polypeptides can also form higher oligomeric states. We investigated the introduction of tetrameric modules as a substitute for coiled-coil dimerization units used in previous modular nanostructures. Tetramerizing helical bundles can run in parallel or antiparallel orientation, expanding the number of topological solutions for modular nanostructures. Furthermore, this strategy facilitates the construction of nanostructures from two identical polypeptide chains. Importantly, tetrameric modules substantially stabilized protein nanostructures against air-water interface denaturation, enabling the determination of the first cryo-electron microscopy three-dimensional structure of a coiled-coil-based nanostructure, confirming the designed agreement of the modules forming a tetrahedral cage.

PMID:39666653 | DOI:10.1002/anie.202422075

Protein Sci. 2025 Jan;34(1):e5239. doi: 10.1002/pro.5239.

ABSTRACT

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

PMID:39665261 | DOI:10.1002/pro.5239

Biol Methods Protoc. 2024 Nov 27;9(1):bpae090. doi: 10.1093/biomethods/bpae090. eCollection 2024.

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic underscored the necessity for rapid and efficient diagnostic testing to mitigate outbreaks and control disease transmission. While real-time reverse transcriptase quantitative PCR (RT-qPCR) has been the gold standard due to its high sensitivity and specificity, its logistical complexities and extended turnaround times highlighted the need for alternative molecular methods and non-standard equipment and consumables not subject to supply chain pressure. Loop-mediated isothermal amplification (LAMP) offers several advantages over RT-qPCR, including faster processing time, assay flexibility and cost-effectiveness. During the pandemic, LAMP was successfully demonstrated as a viable alternative to RT-qPCR for SARS-Related Coronavirus 2 detection. However, due to a 100 to 1,000-fold increase in testing volumes, there was an imminent need for automating and scaling up existing LAMP testing workflows leveraging a robotic infrastructure, while retaining analytical performance and cost-effectiveness. In 2020, the Foundation TOMi started the "TOMi corona initiative" to develop and validate a high-throughput, end-to-end, automated, scalable single-step RNA purification, and LAMP-based COVID-19 testing system called SMART-LAMP (Scalable Molecular Automation for Rapid Testing using LAMP) that can process up to 40,000 samples per day using existing laboratory equipment infrastructure with sensitivity comparable to RT-qPCR. This system provides a rapid and scalable diagnostic solution for future pandemics, capable of processing over 40,000 samples per day. In addition, the system is designed to minimize consumable costs and reduces the overall use of plastics to align with increasingly strict sustainability goals that will be imposed over the coming years. Importantly, this system and public-private partnerships in the TOMi corona initiative has the potential to serve as a baseline to enhance pandemic preparedness and response capabilities.

PMID:39664603 | PMC:PMC11634539 | DOI:10.1093/biomethods/bpae090

Front Microbiol. 2024 Nov 27;15:1470054. doi: 10.3389/fmicb.2024.1470054. eCollection 2024.

ABSTRACT

The terrestrial green alga Chromochloris zofingiensis is an emerging model species with potential applications including production of triacylglycerol or astaxanthin. How C. zofingiensis interacts with the diverse substrates during trophic transitions is unknown. To characterize its substrate utilization and secretion dynamics, we cultivated the alga in a soil-based defined medium in transition between conditions with and without glucose supplementation. Then, we examined its exometabolite and endometabolite profiles. This analysis revealed that regardless of trophic modes, C. zofingiensis preferentially uptakes exogenous lysine, arginine, and purines, while secreting orotic acid. Here, we obtained metabolomic evidences that C. zofingiensis may use arginine for putrescine synthesis when in transition to heterotrophy, and for the TCA cycle during transition to photoautotrophy. We also report that glucose and fructose most effectively inhibited photosynthesis among thirteen different sugars. The utilized or secreted metabolites identified in this study provide important information to improve C. zofingiensis cultivation, and to expand its potential industrial and pharmaceutical applications.

PMID:39664052 | PMC:PMC11631937 | DOI:10.3389/fmicb.2024.1470054

Genome Biol Evol. 2024 Dec 4;16(12):evae175. doi: 10.1093/gbe/evae175.

ABSTRACT

Proteins that emerge de novo from noncoding DNA could negatively or positively influence cellular physiology in the sense of providing a possible adaptive advantage. Here, we employ two approaches to study such effects in a human cell line by expressing random sequences and mouse de novo genes that lack homologs in the human genome. We show that both approaches lead to differential growth effects of the cell clones dependent on the sequences they express. For the random sequences, 53% of the clones decreased in frequency, and about 8% increased in frequency in a joint growth experiment. Of the 14 mouse de novo genes tested in a similar joint growth experiment, 10 decreased, and 3 increased in frequency. When individually analysed, each mouse de novo gene triggers a unique transcriptomic response in the human cells, indicating mostly specific rather than generalized effects. Structural analysis of the de novo gene open reading frames (ORFs) reveals a range of intrinsic disorder scores and/or foldability into alpha-helices or beta sheets, but these do not correlate with their effects on the growth of the cells. Our results indicate that de novo evolved ORFs could easily become integrated into cellular regulatory pathways, since most interact with components of these pathways and could therefore become directly subject to positive selection if the general conditions allow this.

PMID:39663928 | DOI:10.1093/gbe/evae175

J Basic Microbiol. 2024 Dec 11:e2400527. doi: 10.1002/jobm.202400527. Online ahead of print.

ABSTRACT

DNA replication origins play a crucial role in cellular division and are evolutionarily conserved across domains. This study investigated the evolutionary transitions of replication origins between archaea and bacteria by analyzing 2733 bacterial and 257 archaeal genomes. Our findings revealed that certain methanogens and bacteria share phylogenetic proximity, suggesting evolutionary interactions across diverse ecological systems. Evolutionary transitions in replication origins may have occurred between gut methanogens and bacteria, haloarchaea (Halogeometricum borinquense DSM 11551 and Halovivax ruber XH-70), halobacteria, and sulfur-reducing archaea. Methanosarcina barkeri (M. barkeri), Methanosaeta thermophila, and Methanococcoides burtonii (M. burtonii) were closely related to respiratory tract bacteria in humans. Methanohalobium evestigatum (M. evestigatum) is strongly linked to the animal gut pathogen Mycoplasma putrefaciens (M. putrefaciens). Several thermophilic hydrogenotrophic methanogens clustered with oral and fish pathogens. Pyrococcus furiosus (P. furiosus) was evolutionarily related to the replication origin of plant pathogens. This study sheds light on the ecological drivers of DNA replication origin evolution and their role in microbial speciation and adaptation. Our findings highlight the influence of mutualistic and parasitic relationships on these evolutionary transitions. It could have significant implications in biotechnology and medicine, such as developing novel antimicrobial strategies and understanding host-pathogen dynamics.

PMID:39663550 | DOI:10.1002/jobm.202400527

Nature. 2024 Dec;636(8042):322-331. doi: 10.1038/s41586-024-08280-5. Epub 2024 Dec 11.

ABSTRACT

The human body contains trillions of cells, classified into specific cell types, with diverse morphologies and functions. In addition, cells of the same type can assume different states within an individual's body during their lifetime. Understanding the complexities of the proteome in the context of a human organism and its many potential states is a necessary requirement to understanding human biology, but these complexities can neither be predicted from the genome, nor have they been systematically measurable with available technologies. Recent advances in proteomic technology and computational sciences now provide opportunities to investigate the intricate biology of the human body at unprecedented resolution and scale. Here we introduce a big-science endeavour called π-HuB (proteomic navigator of the human body). The aim of the π-HuB project is to (1) generate and harness multimodality proteomic datasets to enhance our understanding of human biology; (2) facilitate disease risk assessment and diagnosis; (3) uncover new drug targets; (4) optimize appropriate therapeutic strategies; and (5) enable intelligent healthcare, thereby ushering in a new era of proteomics-driven phronesis medicine. This ambitious mission will be implemented by an international collaborative force of multidisciplinary research teams worldwide across academic, industrial and government sectors.

PMID:39663494 | DOI:10.1038/s41586-024-08280-5

Nature. 2024 Dec 11. doi: 10.1038/s41586-024-08264-5. Online ahead of print.

ABSTRACT

The complete blood count (CBC) is an important screening tool for healthy adults and a common test at periodic exams. However, results are usually interpreted relative to one-size-fits-all reference intervals1,2, undermining the precision medicine goal to tailor care for patients on the basis of their unique characteristics3,4. Here we study thousands of diverse patients at an academic medical centre and show that routine CBC indices fluctuate around stable values or setpoints5, and setpoints are patient-specific, with the typical healthy adult's nine CBC setpoints distinguishable as a group from those of 98% of other healthy adults, and setpoint differences persist for at least 20 years. Haematological setpoints reflect a deep physiologic phenotype enabling investigation of acquired and genetic determinants of haematological regulation and its variation among healthy adults. Setpoints in apparently healthy adults were associated with significant variation in clinical risk: absolute risk of some common diseases and morbidities varied by more than 2% (heart attack and stroke, diabetes, kidney disease, osteoporosis), and absolute risk of all-cause 10 year mortality varied by more than 5%. Setpoints also define patient-specific reference intervals and personalize the interpretation of subsequent test results. In retrospective analysis, setpoints improved sensitivity and specificity for evaluation of some common conditions including diabetes, kidney disease, thyroid dysfunction, iron deficiency and myeloproliferative neoplasms. This study shows CBC setpoints are sufficiently stable and patient-specific to help realize the promise of precision medicine for healthy adults.

PMID:39663453 | DOI:10.1038/s41586-024-08264-5

Nat Commun. 2024 Dec 11;15(1):10668. doi: 10.1038/s41467-024-55089-x.

ABSTRACT

Biomolecular condensates are membraneless organelles that can concentrate hundreds of different proteins in cells to operate essential biological functions. However, accurate identification of their components remains challenging and biased towards proteins with high structural disorder content with focus on self-phase separating (driver) proteins. Here, we present a machine learning algorithm, PICNIC (Proteins Involved in CoNdensates In Cells) to classify proteins that localize to biomolecular condensates regardless of their role in condensate formation. PICNIC successfully predicts condensate members by learning amino acid patterns in the protein sequence and structure in addition to the intrinsic disorder. Extensive experimental validation of 24 positive predictions in cellulo shows an overall ~82% accuracy regardless of the structural disorder content of the tested proteins. While increasing disorder content is associated with organismal complexity, our analysis of 26 species reveals no correlation between predicted condensate proteome content and disorder content across organisms. Overall, we present a machine learning classifier to interrogate condensate components at whole-proteome levels across the tree of life.

PMID:39663388 | DOI:10.1038/s41467-024-55089-x

Protoplasma. 2024 Dec 11. doi: 10.1007/s00709-024-02015-z. Online ahead of print.

ABSTRACT

In this work, we propose a possible correlation between carbohydrate content in hazelnut pollen (wild type) and viability/germinability, also in a perspective of adaptation to climate variability. Samples from four different cultivation fields in Italy showed values of pollen viability characterized by high levels, ranging between 77.3 and 98.4% and a unique trend during the flowering period for each accession. When subjected to dehydration in controlled environment, pollen reduced the levels of viability to almost zero but recovered the initial values when rehydrated. The presence of anomalous pollen was found to be not significant, always below 4% in all accessions. The analysis on starch content gave negative results both when it was determined biochemically and detected by histological staining. Sucrose content resulted always higher than glucose and fructose in all the accessions analyzed. Its concentration throughout the dispersal phases reflected the trend of both pollen viability and germinability. These data seem to suggest a direct involvement of sucrose in the protection of plasma membranes from dehydration and the maintenance of pollen viability and germinability. This study demonstrates the sensitivity of hazelnut pollen to climatic fluctuations, particularly to air dry condition, stressing a significant role of sucrose in maintaing viablity and germinabilty during all dispersal period.

PMID:39663238 | DOI:10.1007/s00709-024-02015-z

Bioresour Technol. 2024 Dec 9:131966. doi: 10.1016/j.biortech.2024.131966. Online ahead of print.

ABSTRACT

To successfully scale-up the production of bio-based building blocks through CO2 and H2-based gas fermentation, it is crucial to deeply understand and control the microbial catalyst response to the bioreactor environment. This study investigates the effects of key process parameters, such as CO2 and H2 partial pressures, gas feeding strategies, and mixture composition, on the production pathways of an evolved Clostridium carboxidivorans strain. The ultimate goal is to optimize 1-hexanol production in elevated-pressure stirred-tank reactors. Continuous gas feeding enhanced acetogenic and solventogenic metabolisms, while gas-limited conditions promoted chain elongation to caproic acid. An optimized process, combining an initial gas-limited step followed by a continuous gas phase, increased 1-hexanol production, achieving a maximum biomass-specific productivity of 0.9 g gCDW-1 day-1. In-situ product extraction improved 1-hexanol carbon selectivity to an unprecedented 60 %. These findings demonstrate the potential of CO2 and H2-fed fermentation to produce high-value chemicals other than ethanol and acetate.

PMID:39662847 | DOI:10.1016/j.biortech.2024.131966

J Dairy Sci. 2024 Dec 9:S0022-0302(24)01350-X. doi: 10.3168/jds.2024-25341. Online ahead of print.

ABSTRACT

Homozygosity, which can arise from several genetic mechanisms including inbreeding, is frequently observed in the offspring of related parents. This inbreeding can lead to a reduced performance, due to a phenomenon known as inbreeding depression. This study assessed inbreeding depression using whole genome and regional approaches in first-lactation Australian Holsteins and Jerseys, involving approximately 33,000 Holstein and 7,000 Jersey cows born between 2000 and 2017. These cows had phenotypic records (milk production, fertility, and survival), pedigree records, and genomic data available. We analyzed genome-wide inbreeding depression through a mixed animal model examining 4 measures of inbreeding: pedigree data, runs of homozygosity (ROH) of at least 1Mb, ROH greater than 8 Mb, and ROH exceeding 16 Mb, which indicates more recent inbreeding. Additionally, unique ROH haplotypes, identified using a sliding-window approach, were incorporated as fixed effects in the model to estimate their effect on the traits of interest. Results indicated that a 1% increase in pedigree inbreeding led to reduced performance across all traits, with estimates of inbreeding depression ranging from 0.11% to 0.45% of the phenotypic mean. In Holsteins, genome-wide estimates (FROH) were statistically significant and reasonably aligned with pedigree estimates, while more recent inbreeding (FROH > 16 Mb) had between 2.6 and 3.3 times greater effect on inbreeding depression across all traits compared with smaller FROH (≥1 Mb). In Jerseys, more recent inbreeding had a 2.2-2.3 times greater reduction in the performance of milk and protein yields for a 1% increase in genomic inbreeding. For both fitness traits in Jerseys, the effects of inbreeding on fertility and survival were not statistically significant. The most negative impacts of ROH were also noted in specific traits: Jersey and Holstein cows with unfavorable ROH took significantly longer to re-calve and showed marked reductions in production traits. Moreover, increased homozygosity in certain genomic regions, like BTA 25 in Jerseys, markedly reduced performance, highlighting the importance of genomic location in assessing the effects of homozygosity. This data informs next-generation mating programs, emphasizing avoiding inbreeding in genomic regions most susceptible to inbreeding depression, to enhance animal performance.

PMID:39662810 | DOI:10.3168/jds.2024-25341

Environ Pollut. 2024 Dec 9:125504. doi: 10.1016/j.envpol.2024.125504. Online ahead of print.

ABSTRACT

Micro- and nanoplastics are globally important environmental pollutants. Although research in this field is continuously improving, there are a number of uncertainties, inconsistencies and methodological challenges in the effect assessment of micro-nanoparticles in freshwater systems. The current understanding of adverse effects is partly biased by the use of non-relevant particle types, unsuitable test setups and environmentally unrealistic dose metrics, which does not take into account realistic processes in particle uptake and consequent effects. Here we summarize the current state of the art by compiling the most recent research with the aim to highlight research gaps and further necessary steps towards more harmonized testing systems. In particular, ecotoxicological scenarios need to mirror environmentally realistic particle diversity and bioavailability. Harmonized test setups should include different uptake pathways, exposure and comparisons with natural reference particles. Effect assessments need to differentiate direct physical particle effects, such as lesions and toxicity caused by the polymer, from indirect effects, such as alterations of ambient environmental conditions by leaching, change of turbidity, food dilution and organisms' behavior. Implementation of these suggestions can contribute to harmonization and more effective, evidence-based assessments of the ecotoxicological effects of micro- and nanoplastics.

PMID:39662584 | DOI:10.1016/j.envpol.2024.125504

Cell Rep Methods. 2024 Dec 5:100933. doi: 10.1016/j.crmeth.2024.100933. Online ahead of print.

ABSTRACT

Stochastic fluctuations (noise) in transcription generate substantial cell-to-cell variability. However, how best to quantify genome-wide noise remains unclear. Here, we utilize a small-molecule perturbation (5'-iodo-2'-deoxyuridine [IdU]) to amplify noise and assess noise quantification from numerous single-cell RNA sequencing (scRNA-seq) algorithms on human and mouse datasets and then compare it to noise quantification from single-molecule RNA fluorescence in situ hybridization (smFISH) for a panel of representative genes. We find that various scRNA-seq analyses report amplified noise-without altered mean expression levels-for ∼90% of genes and that smFISH analysis verifies noise amplification for the vast majority of tested genes. Collectively, the analyses suggest that most scRNA-seq algorithms (including a simple normalization approach) are appropriate for quantifying noise, although all algorithms appear to systematically underestimate noise changes compared to smFISH. For practical purposes, this analysis further argues that IdU noise enhancement is globally penetrant-i.e., homeostatically increasing noise without altering mean expression levels-and could enable investigations of the physiological impacts of transcriptional noise.

PMID:39662473 | DOI:10.1016/j.crmeth.2024.100933