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At least 199 records · Page 11

Haloanaerobium kushneri sp. nov., an obligately halophilic, anaerobic bacterium from an oil brine

Three strains, designated VS-751T, VS-511 and VS-732, of a strictly anaerobic, moderately halophilic, Gram-negative, rod-shaped bacterium were isolated from a highly saline (15-20%) brine from an oil reservoir in central Oklahoma, USA. The optimal concentration of NaCl for growth of these three strains was 2 M (12%), and the strains also grew in the presence of an additional 1 M MgCl2. The strains were mesophilic and grew at a pH range of 6-8. Carbohydrates used by all three strains included glucose, fructose, arabinose, galactose, maltose, mannose, cellobiose, sucrose and inulin. Glucose fermentation products included ethanol, acetate, H2 and CO2, with formate produced by two of the three strains. Differences were noted among strains in the optimal temperature and pH for growth, the maximum and minimum NaCl concentration that supported growth, substrate utilization and cellular fatty acid composition. Despite the phenotypic differences among the three strains, analysis of the 16S rRNA gene sequences and DNA-DNA hybridizations showed that these three strains were members of the same genospecies which belonged to the genus Haloanaerobium. The phenotypic and genotypic characteristics of strains VS-751T, VS-511 and VS-732 are different from those of previously described species of Haloanaerobium. It is proposed that strain VS-751T (ATCC 700103T) be established as the type strain of a new species, Haloanaerobium kushneri.

NASA Discipline Exobiology↗

Polyphasic taxonomy of the genus Shewanella and description of Shewanella oneidensis sp. nov

The genus Shewanella has been studied since 1931 with regard to a variety of topics of relevance to both applied and environmental microbiology. Recent years have seen the introduction of a large number of new Shewanella-like isolates, necessitating a coordinated review of the genus. In this work, the phylogenetic relationships among known shewanellae were examined using a battery of morphological, physiological, molecular and chemotaxonomic characterizations. This polyphasic taxonomy takes into account all available phenotypic and genotypic data and integrates them into a consensus classification. Based on information generated from this study and obtained from the literature, a scheme for the identification of Shewanella species has been compiled. Key phenotypic characteristics were sulfur reduction and halophilicity. Fatty acid and quinone profiling were used to impart an additional layer of information. Molecular characterizations employing small-subunit 16S rDNA sequences were at the limits of resolution for the differentiation of species in some cases. As a result, DNA-DNA hybridization and sequence analyses of a more rapidly evolving molecule (gyrB gene) were performed. Species-specific PCR probes were designed for the gyrB gene and used for the rapid screening of closely related strains. With this polyphasic approach, in addition to the ten described Shewanella species, two new species, Shewanella oneidensis and 'Shewanella pealeana', were recognized; Shewanella oneidensis sp. nov. is described here for the first time.

NASA Discipline Exobiology↗

Cell contact as an independent factor modulating cardiac myocyte hypertrophy and survival in long-term primary culture

Cardiac myocytes maintained in cell culture develop hypertrophy both in response to mechanical loading as well as to receptor-mediated signaling mechanisms. However, it has been shown that the hypertrophic response to these stimuli may be modulated through effects of intercellular contact achieved by maintaining cells at different plating densities. In this study, we show that the myocyte plating density affects not only the hypertrophic response and features of the differentiated phenotype of isolated adult myocytes, but also plays a significant role influencing myocyte survival in vitro. The native rod-shaped phenotype of freshly isolated adult myocytes persists in an environment which minimizes myocyte attachment and spreading on the substratum. However, these conditions are not optimal for long-term maintenance of cultured adult cardiac myocytes. Conditions which promote myocyte attachment and spreading on the substratum, on the other hand, also promote the re-establishment of new intercellular contacts between myocytes. These contacts appear to play a significant role in the development of spontaneous activity, which enhances the redevelopment of highly differentiated contractile, junctional, and sarcoplasmic reticulum structures in the cultured adult cardiomyocyte. Although it has previously been shown that adult cardiac myocytes are typically quiescent in culture, the addition of beta-adrenergic agonists stimulates beating and myocyte hypertrophy, and thereby serves to increase the level of intercellular contact as well. However, in densely-plated cultures with intrinsically high levels of intercellular contact, spontaneous contractile activity develops without the addition of beta-adrenergic agonists. In this study, we compare the function, morphology, and natural history of adult feline cardiomyocytes which have been maintained in cultures with different levels of intercellular contact, with and without the addition of beta-adrenergic agonists. Intercellular contact, communication, and transmission of contractile forces between myocytes appears to play a primary role in remodeling the 2-dimensional cell layer into a parallel alignment of elongated myocytes with highly developed intercalated disk-like junctions. This highly differentiated state is very stable, and cultures which achieve this state exhibit significantly greater longevity than more sparsely plated myocytes. These myocytes typically continue beating, and survive from 6 to more than 12 weeks in culture. When this level of contact and differentiation are not achieved, even among beta-adrenergic stimulated myocytes, contractile activity is not sustained, myofibrils atrophy, there is little or no development of junctional complexes, and the period of myocyte viability is typically no more than 5 weeks in vitro.

Non-NASA Center↗

The role of clinical pharmacology in molecular genetics

PROBLEM: Discovering the causes of unusual phenotypes in human subjects is an important aspect of patient-oriented research. MATERIAL: The tools of clinical pharmacology are uniquely useful in addressing these problems. PATIENTS, SUBJECTS, OR CASE HISTORIES: We evaluated a 42-year-old patient with lifelong orthostatic hypotension and ptosis of the eyelids. He underwent a series of biochemical, physiological, and pharmacological tests outlined in this article. RESULTS: These studies indicated that sympathetic innervation was intact but that the sympathetic neurotransmitter was dopamine rather than norepinephrine. These results demonstrated that dopamine-beta-hydroxylase deficiency underlies the clinical abnormalities of this patient. CONCLUSION: In selected individuals with unusual phenotypes, the techniques of clinical chemistry and clinical pharmacology can define the nature of the defect at almost the resolution of the human genome.

NASA Discipline Regulatory Physiology↗

Cell proliferation and hair cell addition in the ear of the goldfish, Carassius auratus

Cell proliferation and hair cell addition have not been studied in the ears of otophysan fish, a group of species who have specialized hearing capabilities. In this study we used the mitotic S-phase marker bromodeoxyuridine (BrdU) to identify proliferating cells in the ear of one otophysan species, Carassius auratus (the goldfish). Animals were sacrificed at 3 h or 5 days postinjection with BrdU and processed for immunocytochemistry. The results of the study show that cell proliferation occurs in all of the otic endorgans and results in the addition of new hair cells. BrdU-labeled cells were distributed throughout all epithelia, including the primary auditory endorgan (saccule), where hair cell phenotypes vary considerably along the rostrocaudal axis. This study lays the groundwork for our transmission electron microscopy study of proliferative cells in the goldfish ear (Presson et al., Hearing Research 100 (1996) 10-20) as well as future studies of hair cell development in this species. The ability to predict, based on epithelial location, the future phenotype of developing hair cells in the saccule of the goldfish make that endorgan a particularly powerful model system for the investigation of early hair cell differentiation.

NASA Discipline Number 40-10↗

A mutation in protein phosphatase 2A regulatory subunit A affects auxin transport in Arabidopsis

The phytohormone auxin controls processes such as cell elongation, root hair development and root branching. Tropisms, growth curvatures triggered by gravity, light and touch, are also auxin-mediated responses. Auxin is synthesized in the shoot apex and transported through the stem, but the molecular mechanism of auxin transport is not well understood. Naphthylphthalamic acid (NPA) and other inhibitors of auxin transport block tropic curvature responses and inhibit root and shoot elongation. We have isolated a novel Arabidopsis thaliana mutant designated roots curl in NPA (rcn1). Mutant seedlings exhibit altered responses to NPA in root curling and hypocotyl elongation. Auxin efflux in mutant seedlings displays increased sensitivity to NPA. The rcn1 mutation was transferred-DNA (T-DNA) tagged and sequences flanking the T-DNA insert were cloned. Analysis of the RCN1 cDNA reveals that the T-DNA insertion disrupts a gene for the regulatory A subunit of protein phosphatase 2A (PP2A-A). The RCN1 gene rescues the rcn1 mutant phenotype and also complements the temperature-sensitive phenotype of the Saccharomyces cerevisiae PP2A-A mutation, tpd3-1. These data implicate protein phosphatase 2A in the regulation of auxin transport in Arabidopsis.

Non-NASA Center↗

Genetics and molecular biology of hypotension

Major strides in the molecular biology of essential hypertension are currently underway. This has tended to obscure the fact that a number of inherited disorders associated with low blood pressure exist and that these diseases may have milder and underrecognized phenotypes that contribute importantly to blood pressure variation in the general population. This review highlights some of the gene products that, if abnormal, could cause hypotension in some individuals. Diseases due to abnormalities in the catecholamine enzymes are discussed in detail. It is likely that genetic abnormalities with hypotensive phenotypes will be as interesting and diverse as those that give rise to hypertensive disorders.

Review, Academic↗

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Bacteria rapidly adapt to environmental cues through morphological and ultrastructural changes that correlate with physiology and behavior. Cryogenic transmission electron microscopy (cryo‐TEM) can capture these phenotypic changes in near‐native, vitrified states, but manual analysis of low‐dose micrographs is labor intensive and limits throughput. Here, we present an end‐to‐end workflow that combines low‐dose cryo‐TEM imaging with a YOLOv11‐based instance‐segmentation model to automatically identify bacteria and quantify key structural features directly from the micrographs. This workflow enables (i) robust bacterial localization and counting from low‐magnification atlas/montage images, (ii) automated measurements of cell‐envelope (outer–inner membrane) thickness and anisotropy from higher‐magnification views, and (iii) detection and quantification of bacteria–flagella interactions, including overlap length and curvature metrics for interacting versus noninteracting flagella. Using Pantoea sp. YR343 grown under distinct media conditions, we show that the automated measurements agree with manual annotations while substantially reducing analysis time. Together, these tools provide a practical framework for scalable bacterial identification and quantitative phenotyping in low‐dose cryo‐TEM datasets and establish a foundation for extending cryo‐TEM image analysis toward higher‐throughput studies of microbial heterogeneity and biointerfaces.

YOLOv11↗

Artificial intelligence to unlock real-world evidence in clinical oncology: A primer on recent advances

Purpose: Real world evidence is crucial to understanding the diffusion of new oncologic therapies, monitoring cancer outcomes, and detecting unexpected toxicities. In practice, real world evidence is challenging to collect rapidly and comprehensively, often requiring expensive and time-consuming manual case-finding and annotation of clinical text. In this Review, we summarise recent developments in the use of artificial intelligence to collect and analyze real world evidence in oncology. Methods: We performed a narrative review of the major current trends and recent literature in artificial intelligence applications in oncology. Results: Artificial intelligence (AI) approaches are increasingly used to efficiently phenotype patients and tumors at large scale. These tools also may provide novel biological insights and improve risk prediction through multimodal integration of radiographic, pathological, and genomic datasets. Custom language processing pipelines and large language models hold great promise for clinical prediction and phenotyping. Conclusions: Despite rapid advances, continued progress in computation, generalizability, interpretability, and reliability as well as prospective validation are needed to integrate AI approaches into routine clinical care and real-time monitoring of novel therapies.

60 APPLIED LIFE SCIENCES↗

All the light we cannot see: Climate manipulations leave short and long‐term imprints in spectral reflectance of trees

Abstract Anthropogenic climate change, particularly changes in temperature and precipitation, affects plants in multiple ways. Because plants respond dynamically to stress and acclimate to changes in growing conditions, diagnosing quantitative plant‐environment relationships is a major challenge. One approach to this problem is to quantify leaf responses using spectral reflectance, which provides rapid, inexpensive, and nondestructive measurements that capture a wealth of information about genotype as well as phenotypic responses to the environment. However, it is unclear how warming and drought affect spectra. To address this gap, we used an open‐air field experiment that manipulates temperature and rainfall in 36 plots at two sites in the boreal‐temperate ecotone of northern Minnesota, USA. We collected leaf spectral reflectance (400–2400 nm) at the peak of the growing season for three consecutive years on juveniles (two to six years old) of five tree species planted within the experiment. We hypothesized that these mid‐season measurements of spectral reflectance capture a snapshot of the leaf phenotype encompassing a suite of physiological, structural, and biochemical responses to both long‐ and short‐time scale environmental conditions. We show that the imprint of environmental conditions experienced by plants hours to weeks before spectral measurements is linked to regions in the spectrum associated with stress, namely the water absorption regions of the near‐infrared and short‐wave infrared. In contrast, the environmental conditions plants experience during leaf development leave lasting imprints on the spectral profiles of leaves, attributable to leaf structure and chemistry (e.g., pigment content and associated ratios). Our analyses show that after accounting for baseline species spectral differences, spectral responses to the environment do not differ among the species. This suggests that building a general framework for understanding forest responses to climate change through spectral metrics may be possible, likely having broader implications if the common responses among species detected here represent a widespread phenomenon. Consequently, these results demonstrate that examining the entire spectrum of leaf reflectance for environmental imprints in contrast to single features (e.g., indices and traits) improves inferences about plant‐environment relationships, which is particularly important in times of unprecedented climate change.

Stefanski, Artur [Department of Forest Resources U↗

Quantifying leaf symptoms of sorghum charcoal rot in images of field‐grown plants using deep neural networks

Abstract Charcoal rot of sorghum (CRS) is a significant disease affecting sorghum crops, with limited genetic resistance available. The causative agent, Macrophomina phaseolina (Tassi) Goid, is a highly destructive fungal pathogen that targets over 500 plant species globally, including essential staple crops. Utilizing field image data for precise detection and quantification of CRS could greatly assist in the prompt identification and management of affected fields and thereby reduce yield losses. The objective of this work was to implement various machine learning algorithms to evaluate their ability to accurately detect and quantify CRS in red‐green‐blue images of sorghum plants exhibiting symptoms of infection. EfficientNet‐B3 and a fully convolutional network emerged as the top‐performing models for image classification and segmentation tasks, respectively. Among the classification models evaluated, EfficientNet‐B3 demonstrated superior performance, achieving an accuracy of 86.97%, a recall rate of 0.71, and an F1 score of 0.73. Of the segmentation models tested, FCN proved to be the most effective, exhibiting a validation accuracy of 97.76%, a recall rate of 0.68, and an F1 score of 0.66. As the size of the image patches increased, both models’ validation scores increased linearly, and their inference time decreased exponentially. This trend could be attributed to larger patches containing more information, improving model performance, and fewer patches reducing the computational load, thus decreasing inference time. The models, in addition to being immediately useful for breeders and growers of sorghum, advance the domain of automated plant phenotyping and may serve as a foundation for drone‐based or other automated field phenotyping efforts. Additionally, the models presented herein can be accessed through a web‐based application where users can easily analyze their own images.

Gonzalez, Emmanuel M.↗

CMPLE: Correlation Modeling to Decode Photosynthesis Using the Minorize–Maximize Algorithm

In plant genomic experiments, correlations among various biological traits (phenotypes) give new insights into how genetic diversity may have tuned biological processes to enhance fitness under diverse conditions. Consequently, knowing how the correlations are affected by genetic (G) and environmental (E) factors helps develop climate-resilient plants. However, the current literature lacks any method for assessing the effect of predictors on pairwise correlations among multiple phenotypes together with easily interpretable model parameters. To address this need, we propose to model pairwise correlations directly in terms of G and E and develop a computationally efficient inference procedure. Two major novelties in our methodology are (1) the use of a composite pairwise likelihood method to avoid the positive definiteness restriction on the correlation matrix and (2) the use of a novel Minorize–Maximize (MM) algorithm for the efficient estimation of a large number of parameters. The proposed method shows excellent numerical performance on synthetic datasets. Here, the analysis of the motivating data on cowpea reveals that the rates of solar energy storage by photosynthesis (the aggregate trait) are differentially affected by different genetic loci through two distinct processes: “photoinhibition” which results from photodamage caused by excess light, and “photoprotection” which protects plants from photodamage but also results in energy loss.

Correlation modeling↗

A susceptibility gene signature for ERBB2-driven mammary tumour development and metastasis in collaborative cross mice

Background: Deeper insights into ERBB2-driven cancers are essential to develop new treatment approaches for ERBB2+ breast cancers (BCs). We employed the Collaborative Cross (CC) mouse model to unearth genetic factors underpinning Erbb2-driven mammary tumour development and metastasis. Methods: 732 F1 hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains were monitored for mammary tumour phenotypes. GWAS pinpointed SNPs that influence various tumour phenotypes. Multivariate analyses and models were used to construct the polygenic score and to develop a mouse tumour susceptibility gene signature (mTSGS), where the corresponding human ortholog was identified and designated as hTSGS. The importance and clinical value of hTSGS in human BC was evaluated using public datasets, encompassing TCGA, METABRIC, GSE96058, and I-SPY2 cohorts. The predictive power of mTSGS for response to chemotherapy was validated in vivo using genetically diverse MMTV-Erbb2 mice. Findings: Distinct variances in tumour onset, multiplicity, and metastatic patterns were observed in F1-hybrid female mice between FVB/N MMTV-Erbb2 and 30 CC strains. Besides lung metastasis, liver and kidney metastases emerged in specific CC strains. GWAS identified specific SNPs significantly associated with tumour onset, multiplicity, lung metastasis, and liver metastasis. Multivariate analyses flagged SNPs in 20 genes (Stx6, Ramp1, Traf3ip1, Nckap5, Pfkfb2, Trmt1l, Rprd1b, Rer1, Sepsecs, Rhobtb1, Tsen15, Abcc3, Arid5b, Tnr, Dock2, Tti1, Fam81a, Oxr1, Plxna2, and Tbc1d31) independently tied to various tumour characteristics, designated as a mTSGS. hTSGS scores (hTSGSS) based on their transcriptional level showed prognostic values, superseding clinical factors and PAM50 subtype across multiple human BC cohorts, and predicted pathological complete response independent of and superior to MammaPrint score in I-SPY2 study. The power of mTSGS score for predicting chemotherapy response was further validated in an in vivo mouse MMTV-Erbb2 model, showing that, like findings in human patients, mouse tumours with low mTSGS scores were most likely to respond to treatment. Interpretation: Our investigation has unveiled many new genes predisposing individuals to ERBB2-driven cancer. Translational findings indicate that hTSGS holds promise as a biomarker for refining treatment strategies for patients with BC.

60 APPLIED LIFE SCIENCES↗

ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis

Objective: Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. Here, to address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features. Methods: Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH performs a sparse embedding regression to remove indirect linkage between features to build a sparse KG. Finally, ARCH was validated on various clinical tasks, including detecting known relationships between entity pairs, predicting drug side effects, disease phenotyping, as well as sub-typing Alzheimer’s disease patients. Results: ARCH produces high-quality clinical embeddings and KG for over 60,000 codified and narrative EHR concepts. The KG and embeddings are visualized in the R-shiny powered web-API.3 ARCH achieved high accuracy in detecting EHR concept relationships, with AUCs of 0.926 (codified) and 0.861 (NLP) for similar EHR concepts, and 0.810 (codified) and 0.843 (NLP) for related pairs. It detected drug side effects with a 0.723 AUC, which improved to 0.826 after fine-tuning. Using both codified and NLP features, the detection power increased significantly. Compared to other methods, ARCH has superior accuracy and enhances weakly supervised phenotyping algorithms’ performance. Notably, it successfully categorized Alzheimer’s patients into two subgroups with varying mortality rates. Conclusion: The proposed ARCH algorithm generates large-scale high-quality semantic representations and knowledge graph for both codified and NLP EHR features, useful for a wide range of predictive modeling tasks.

Electronic health records↗

Tre-DST: A Drug Susceptibility Test for Mycobacterium tuberculosis Using Solvatochromic Trehalose Probes

In 2024, an estimated 10 million people developed Tuberculosis (TB), nearly half a million of whom were infected with drug-resistant tuberculosis (DR-TB). Early detection of infection and drug resistance enables rapid engagement in effective care. Bacterial culture and nucleic acid testing remain the primary diagnostic methods, with smear microscopy being phased out. However, these methods present significant limitations for diagnosing drug resistance, such as lengthy time-to-result for phenotypic tests, as well as the need for prior knowledge of resistance mutations and prohibitive cost for molecular tests. To address this, we developed a rapid phenotypic TB drug susceptibility test, termed Tre-DST, based on novel metabolically incorporated trehalose probes, which specifically detect live mycobacteria. We used the nonpathogenic Mycobacterium smegmatis and the virulence-attenuated Mycobacterium tuberculosis (Mtb) H37Ra or auxotrophic Mtb to demonstrate a strong correlation between cost-effective plate reader results and flow cytometry data, suggesting that the plate reader is a suitable fluorescence detector for Tre-DST. We determined that adding a 1-week incubation step allowed Mtb samples originally seeded at 10 4 CFU/mL to become detectable, over 2 weeks earlier than colony-forming unit analysis. We found that Tre-DST reports on drug susceptibility in a drug-agnostic manner, demonstrating loss of fluorescence with frontline TB drugs as well as the newer drug bedaquiline. Tre-DST distinguished RIF- and INH-resistant auxotrophs from susceptible controls and accurately reported the resistance activity. Ultimately, because Tre-DST is agnostic to mechanisms of drug resistance, this assay is likely compatible with all WHO-recommended and future DR-TB drugs as a diagnostic in reference laboratories.

diagnostics↗

Rational Modulation of Plant Root Development Using Engineered Cytokinin Regulators

Achieving precise control over quantitative developmental phenotypes is a key objective in plant biology. Recent advances in synthetic biology have enabled tools to reprogram entire developmental pathways; however, the complexity of designing synthetic genetic programs and the inherent interactions between various signaling processes remains a critical challenge. Here, we leverage Type-B response regulators to modulate the expression of genes involved in cytokinin-dependent growth and development processes. We rationally engineered these regulators to modulate their transcriptional activity (i.e., repression or activation) and potency while reducing their sensitivity to cytokinin. By localizing the expression of these engineered transcription factors using tissue-specific promoters, we can predictably tune cytokinin-regulated traits. As a proof of principle, we deployed this synthetic system in Arabidopsis thaliana to either decrease or increase the number of lateral roots. The simplicity and modularity of our approach makes it an ideal system for controlling other developmental phenotypes of agronomic interest in plants.

Cell signaling↗

Systematic benchmarking demonstrates large language models have not reached the diagnostic accuracy of traditional rare-disease decision support tools

Large language models (LLMs) show promise in supporting differential diagnosis, but their performance is challenging to evaluate due to the unstructured nature of their responses, and their accuracy compared to existing diagnostic tools is not well characterized. To assess the current capabilities of LLMs to diagnose genetic diseases, we benchmarked these models on 5213 previously published case reports using the Phenopacket Schema, the Human Phenotype Ontology and Mondo disease ontology. Prompts generated from each phenopacket were sent to seven LLMs, including four generalist models and three LLMs specialized for medical applications. The same phenopackets were used as input to a widely used diagnostic tool, Exomiser, in phenotype-only mode. The best LLM ranked the correct diagnosis first in 23.6% of cases, whereas Exomiser did so in 35.5% of cases. While the performance of LLMs for supporting differential diagnosis has been improving, it has not reached the level of commonly used traditional bioinformatics tools. Future research is needed to determine the best approach to incorporate LLMs into diagnostic pipelines.

Reese, Justin T. [Lawrence Berkeley National Labor↗

Symmetric adenine methylation is an essential DNA modification in the early-diverging fungus Rhizopus microsporus

The discovery of N6-methyladenine (6mA) in eukaryotic genomes, typically found in prokaryotic DNA, has revolutionized epigenetics. Here, we show that symmetric 6mA is essential in the early diverging fungus Rhizopus microsporus, as the absence of the MT-A70 complex (MTA1c) responsible for this modification results in a lethal phenotype. 6mA is present in 70% of the genes, correlating with the presence of H3K4me3 and H2A.Z in open euchromatic regions. This modification is found predominantly in nucleosome linker regions, influencing the nucleosome positioning around the transcription start sites of highly expressed genes. Controlled downregulation of MTA1c reduces symmetric 6mA sites affecting nucleosome positioning and histone modifications, leading to altered gene expression, which is likely the cause of the severe phenotypic changes observed. Our study highlights the indispensable role of the DNA 6mA in a multicellular organism and delineates the mechanisms through which this epigenetic mark regulates gene expression in a eukaryotic genome.

59 BASIC BIOLOGICAL SCIENCES↗