Nature. 2023 Dec;624(7991):366-377. doi: 10.1038/s41586-023-06805-y. Epub 2023 Dec 13.

ABSTRACT

Cytosine DNA methylation is essential in brain development and is implicated in various neurological disorders. Understanding DNA methylation diversity across the entire brain in a spatial context is fundamental for a complete molecular atlas of brain cell types and their gene regulatory landscapes. Here we used single-nucleus methylome sequencing (snmC-seq3) and multi-omic sequencing (snm3C-seq)1 technologies to generate 301,626 methylomes and 176,003 chromatin conformation-methylome joint profiles from 117 dissected regions throughout the adult mouse brain. Using iterative clustering and integrating with companion whole-brain transcriptome and chromatin accessibility datasets, we constructed a methylation-based cell taxonomy with 4,673 cell groups and 274 cross-modality-annotated subclasses. We identified 2.6 million differentially methylated regions across the genome that represent potential gene regulation elements. Notably, we observed spatial cytosine methylation patterns on both genes and regulatory elements in cell types within and across brain regions. Brain-wide spatial transcriptomics data validated the association of spatial epigenetic diversity with transcription and improved the anatomical mapping of our epigenetic datasets. Furthermore, chromatin conformation diversities occurred in important neuronal genes and were highly associated with DNA methylation and transcription changes. Brain-wide cell-type comparisons enabled the construction of regulatory networks that incorporate transcription factors, regulatory elements and their potential downstream gene targets. Finally, intragenic DNA methylation and chromatin conformation patterns predicted alternative gene isoform expression observed in a whole-brain SMART-seq2 dataset. Our study establishes a brain-wide, single-cell DNA methylome and 3D multi-omic atlas and provides a valuable resource for comprehending the cellular-spatial and regulatory genome diversity of the mouse brain.

PMID:38092913 | DOI:10.1038/s41586-023-06805-y

Sci Rep. 2023 Dec 13;13(1):22145. doi: 10.1038/s41598-023-49426-1.

ABSTRACT

Phthalates constitute a family of anthropogenic chemicals developed to be used in the manufacture of plastics, solvents, and personal care products. Their dispersion and accumulation in many environments can occur at all stages of their use (from synthesis to recycling). However, many phthalates together with other accumulated engineered chemicals have been shown to interfere with hormone activities. These compounds are also in close contact with microorganisms that are free-living, in biofilms or in microbiota, within multicellular organisms. Herein, the activity of several phthalates and their substitutes were investigated on the opportunistic pathogen Legionella pneumophila, an aquatic microbe that can infect humans. Beside showing the toxicity of some phthalates, data suggested that Acetyl tributyl citrate (ATBC) and DBP (Di-n-butyl phthalate) at environmental doses (i.e. 10-6 M and 10-8 M) can modulate Legionella behavior in terms of motility, biofilm formation and response to antibiotics. A dose of 10-6 M mostly induced adverse effects for the bacteria, in contrast to a dose of 10-8 M. No perturbation of virulence towards Acanthamoeba castellanii was recorded. These behavioral alterations suggest that L. pneumophila is able to sense ATBC and DBP, in a cross-talk that either mimics the response to a native ligand, or dysregulates its physiology.

PMID:38092873 | DOI:10.1038/s41598-023-49426-1

Nat Commun. 2023 Dec 13;14(1):8075. doi: 10.1038/s41467-023-43690-5.

ABSTRACT

The metabolic and signaling pathways regulating aggressive mesenchymal colorectal cancer (CRC) initiation and progression through the serrated route are largely unknown. Although relatively well characterized as BRAF mutant cancers, their poor response to current targeted therapy, difficult preneoplastic detection, and challenging endoscopic resection make the identification of their metabolic requirements a priority. Here, we demonstrate that the phosphorylation of SCAP by the atypical PKC (aPKC), PKCλ/ι promotes its degradation and inhibits the processing and activation of SREBP2, the master regulator of cholesterol biosynthesis. We show that the upregulation of SREBP2 and cholesterol by reduced aPKC levels is essential for controlling metaplasia and generating the most aggressive cell subpopulation in serrated tumors in mice and humans. Since these alterations are also detected prior to neoplastic transformation, together with the sensitivity of these tumors to cholesterol metabolism inhibitors, our data indicate that targeting cholesterol biosynthesis is a potential mechanism for serrated chemoprevention.

PMID:38092754 | DOI:10.1038/s41467-023-43690-5

PLoS Comput Biol. 2023 Dec 13;19(12):e1011699. doi: 10.1371/journal.pcbi.1011699. Online ahead of print.

ABSTRACT

When grown on agar surfaces, microbes can produce distinct multicellular spatial structures called colonies, which contain characteristic sizes, shapes, edges, textures, and degrees of opacity and color. For over one hundred years, researchers have used these morphology cues to classify bacteria and guide more targeted treatment of pathogens. Advances in genome sequencing technology have revolutionized our ability to classify bacterial isolates and while genomic methods are in the ascendancy, morphological characterization of bacterial species has made a resurgence due to increased computing capacities and widespread application of machine learning tools. In this paper, we revisit the topic of colony morphotype on the within-species scale and apply concepts from image processing, computer vision, and deep learning to a dataset of 69 environmental and clinical Pseudomonas aeruginosa strains. We find that colony morphology and complexity under common laboratory conditions is a robust, repeatable phenotype on the level of individual strains, and therefore forms a potential basis for strain classification. We then use a deep convolutional neural network approach with a combination of data augmentation and transfer learning to overcome the typical data starvation problem in biological applications of deep learning. Using a train/validation/test split, our results achieve an average validation accuracy of 92.9% and an average test accuracy of 90.7% for the classification of individual strains. These results indicate that bacterial strains have characteristic visual 'fingerprints' that can serve as the basis of classification on a sub-species level. Our work illustrates the potential of image-based classification of bacterial pathogens and highlights the potential to use similar approaches to predict medically relevant strain characteristics like antibiotic resistance and virulence from colony data.

PMID:38091365 | DOI:10.1371/journal.pcbi.1011699

Proc Natl Acad Sci U S A. 2023 Dec 19;120(51):e2309760120. doi: 10.1073/pnas.2309760120. Epub 2023 Dec 13.

ABSTRACT

Genetic assimilation is the process by which a phenotype that is initially induced by an environmental stimulus becomes stably inherited in the absence of the stimulus after a few generations of selection. While the concept has attracted much debate after being introduced by C. H. Waddington 70 y ago, there have been few experiments to quantitatively characterize the phenomenon. Here, we revisit and organize the results of Waddington's original experiments and follow-up studies that attempted to replicate his results. We then present a theoretical model to illustrate the process of genetic assimilation and highlight several aspects that we think require further quantitative studies, including the gradual increase of penetrance, the statistics of delay in assimilation, and the frequency of unviability during selection. Our model captures Waddington's picture of developmental paths in a canalized landscape using a stochastic dynamical system with alternative trajectories that can be controlled by either external signals or internal variables. It also reconciles two descriptions of the phenomenon-Waddington's, expressed in terms of an individual organism's developmental paths, and that of Bateman in terms of the population distribution crossing a hypothetical threshold. Our results provide theoretical insight into the concepts of canalization, phenotypic plasticity, and genetic assimilation.

PMID:38091287 | DOI:10.1073/pnas.2309760120

Genet Mol Biol. 2023 Dec 11;46(3 Suppl 1):e20230141. doi: 10.1590/1678-4685-GMB-2023-0141. eCollection 2023.

ABSTRACT

The Subcortical Maternal Complex (SCMC) is composed of maternally encoded proteins required for the early stages of embryo development. Here we aimed to investigate the expression profile of the genes that encode the individual members of the SCMC in human reproductive failures. To accomplish that, we selected three datasets in the Gene Expression Omnibus repository for differential gene expression (DGE) analysis, comprising human endometrial and placental tissues of patients with recurrent implantation failure (RIF) or recurrent pregnancy loss (RPL). The SCMC genes KHDC3L, NLRP2, NLRP4, NLRP5, OOEP, PADI6, TLE6, and ZBED3 were included in the DGE analysis, as well as CFL1 and CFL2 that connect the SCMC with the actin cytoskeleton. Additionally, differential co-expression analysis and systems biology analysis of gene-gene co-expression were performed for KHDC3L, NLRP5, OOEP, and TLE6, demonstrating gene pairs differentially correlated under the two conditions, and the co-expression with genes involved in immune response, cell cycle, DNA damage repair, embryo development, and male reproduction. Compared to control groups, NLRP5 demonstrated upregulation in the endometrium of RIF patients, and KHDC3L was upregulated in the fetal placental tissue of RPL patients, shedding light on the importance of considering SCMC genes in reproductive failures.

PMID:38091268 | DOI:10.1590/1678-4685-GMB-2023-0141

J Exp Med. 2024 Jan 1;221(1):e20230930. doi: 10.1084/jem.20230930. Epub 2023 Dec 13.

ABSTRACT

The site of transition between tissue-resident memory (TRM) and circulating phenotypes of T cells is unknown. We integrated clonotype, alloreactivity, and gene expression profiles of graft-repopulating recipient T cells in the intestinal mucosa at the single-cell level after human intestinal transplantation. Host-versus-graft (HvG)-reactive T cells were mainly distributed to TRM, effector T (Teff)/TRM, and T follicular helper compartments. RNA velocity analysis demonstrated a trajectory from TRM to Teff/TRM clusters in association with rejection. By integrating pre- and post-transplantation (Tx) mixed lymphocyte reaction-determined alloreactive repertoires, we observed that pre-existing HvG-reactive T cells that demonstrated tolerance in the circulation were dominated by TRM profiles in quiescent allografts. Putative de novo HvG-reactive clones showed a transcriptional profile skewed to cytotoxic effectors in rejecting grafts. Inferred protein regulon network analysis revealed upstream regulators that accounted for the effector and tolerant T cell states. We demonstrate Teff/TRM interchangeability for individual T cell clones with known (allo)recognition in the human gut, providing novel insight into TRM biology.

PMID:38091025 | DOI:10.1084/jem.20230930

Epigenetics. 2024 Dec;19(1):2289786. doi: 10.1080/15592294.2023.2289786. Epub 2023 Dec 13.

ABSTRACT

DNA methylation has been extensively utilized to study epigenetic patterns across many diseases as well as to deconvolve blood cell type proportions. This study builds upon previous studies examining methylation patterns in paediatric patients with varying stages of Crohn's disease to extend the immune profiling of these patients using a novel deconvolution approach. Compared with control subjects, we observed significantly decreased levels of CD4 memory and naive, CD8 naive, and natural killer cells and elevated neutrophil levels in Crohn's disease. In addition, Crohn's patients had a significantly elevated neutrophil-to-lymphocyte ratio. Using an epigenome-wide association approach and adjusting for potential confounders, including cell type, we observed 397 differentially methylated CpG (DMC) sites associated with Crohn's disease. The top genetic pathway associated with the DMCs was the regulation of arginine metabolic processes which are involved in the regulation of T cells.

PMID:38090774 | DOI:10.1080/15592294.2023.2289786

RSC Adv. 2023 Dec 12;13(51):36048-36059. doi: 10.1039/d3ra03954d. eCollection 2023 Dec 8.

ABSTRACT

Drug discovery is a process that finds new potential drug candidates for curing diseases and is also vital to improving the wellness of people. Enhancing deep learning approaches, e.g., molecular generation models, increases the drug discovery process's efficiency. However, there is a problem in this field in creating drug candidates with desired properties such as the quantitative estimate of druglikeness (QED), synthetic accessibility (SA), and binding affinity (BA), and there is a challenge for training a generative model for specific protein targets that has less pharmaceutical data. In this research, we present Mol-Zero-GAN, a framework that aims to solve the problem based on Bayesian optimization (BO) to find the model optimal weights' singular values, factorized by singular value decomposition, and generate drug candidates with desired properties with no additional data. The proposed framework can produce drugs with the desired properties on protein targets of interest by optimizing the model's weights. Our framework outperforms the state-of-the-art methods sharing the same objectives. Mol-Zero-GAN is publicly available at https://github.com/cucpbioinfo/Mol-Zero-GAN.

PMID:38090100 | PMC:PMC10714197 | DOI:10.1039/d3ra03954d

PeerJ. 2023 Dec 8;11:e16419. doi: 10.7717/peerj.16419. eCollection 2023.

ABSTRACT

The spread of infectious illnesses has been a significant factor restricting aquaculture production. To maximise aquatic animal health, vaccination tactics are very successful and cost-efficient for protecting fish and aquaculture animals against many disease pathogens. However, due to the increasing number of immunological cases and their complexity, it is impossible to manage, analyse, visualise, and interpret such data without the assistance of advanced computational techniques. Hence, the use of immunoinformatics tools is crucial, as they not only facilitate the management of massive amounts of data but also greatly contribute to the creation of fresh hypotheses regarding immune responses. In recent years, advances in biotechnology and immunoinformatics have opened up new research avenues for generating novel vaccines and enhancing existing vaccinations against outbreaks of infectious illnesses, thereby reducing aquaculture losses. This review focuses on understanding in silico epitope-based vaccine design, the creation of multi-epitope vaccines, the molecular interaction of immunogenic vaccines, and the application of immunoinformatics in fish disease based on the frequency of their application and reliable results. It is believed that it can bridge the gap between experimental and computational approaches and reduce the need for experimental research, so that only wet laboratory testing integrated with in silico techniques may yield highly promising results and be useful for the development of vaccines for fish.

PMID:38089909 | PMC:PMC10712311 | DOI:10.7717/peerj.16419

Front Plant Sci. 2023 Nov 28;14:1340170. doi: 10.3389/fpls.2023.1340170. eCollection 2023.

NO ABSTRACT

PMID:38089799 | PMC:PMC10715301 | DOI:10.3389/fpls.2023.1340170

iScience. 2023 Nov 14;26(12):108467. doi: 10.1016/j.isci.2023.108467. eCollection 2023 Dec 15.

ABSTRACT

Accurate risk stratification for patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) is crucial for prognosis and treatment decisions. Here, we develop a tumor microenvironment-associated circular RNA (circRNA) signature that can stratify LA-NPC patients with different risks of relapse and vulnerability to induction chemotherapy (IC). Relapsed-related circRNAs are identified by comparing expression profiles between patients with and without relapse, followed by quantitative validation in the training cohort (n = 170). A nine-circRNA signature is constructed to classify patients into high-risk and low-risk groups. Low-risk patients have significantly favorable clinical survivals, which is validated in the internal (n = 170) and external (n = 150) cohorts. They are characterized by an immune-active microenvironment and can derive benefits from IC. Meanwhile, high-risk patients characterized with pro-relapse and DNA repair-associated features, are vulnerable to chemoresistance. Overall, the circRNA-based classifier serves as a reliable prognostic tool and might guide chemotherapy decisions for patients with LA-NPC.

PMID:38089590 | PMC:PMC10711393 | DOI:10.1016/j.isci.2023.108467

Avicenna J Phytomed. 2023 Sep-Oct;13(5):500-512. doi: 10.22038/AJP.2023.21909.

ABSTRACT

OBJECTIVE: The objective of this study was to determine the role of Iranian herbal Zofa® syrup in improving the clinical symptoms of patients with COVID-19.

MATERIALS AND METHODS: This randomized clinical trial was conducted on 105 patients with COVID-19. Patients were randomly assigned to the intervention (n=35) group (received 10 ml of Zofa® syrup every 8 hours/seven days plus standard treatment) or the control (n=70) group (received only standard treatment). Assessments were performed before and after treatment.

RESULTS: The groups were comparable regarding age (p=0.980), gender (p=0.584), comorbidities (p=0.318), or drug history (p=0.771). There was no difference between patients' recovery status at the time of discharge (p=0.327) or two weeks post-discharge (p=0.165) in the intervention and control groups. No patient was hospitalized to the intensive care unit (ICU) for supplemental oxygen therapy and no patient died in the intervention group. However, in the control group, three (4.5%) patients were transferred to the ICU, and two (3.03%) patients died.

CONCLUSION: Considering the better recovery status of the patients at the time of discharge and the absence of patient deaths in the intervention group, more additional studies are needed to confirm these findings and elucidate the role of Zofa® in COVID-19.

PMID:38089414 | PMC:PMC10711577 | DOI:10.22038/AJP.2023.21909

Bioinform Adv. 2023 Nov 24;3(1):vbad172. doi: 10.1093/bioadv/vbad172. eCollection 2023.

ABSTRACT

MOTIVATION: Differential network (D-Net) analysis has attracted great attention in systems biology for its ability to identify genetic variations in response to different conditions. Current approaches either estimate the condition-specific networks separately followed by post-procedures to determine the differential edges or estimate the D-Net directly. Both types of analysis overlook the probabilistic inference and can only provide deterministic inference of the edges.

RESULTS: Here, we propose a Bayesian solution and translate the probabilistic estimation in the regression model to an inferential D-Net analysis for genetic association and classification studies. The proposed PRobabilistic Interaction for Differential Edges (PRIDE) focuses on inferring the D-Net with uncertainty so that the existence of the differential edges can be evaluated with probability and even prioritized if comparison among these edges is of interest. The performance of the proposed model is compared with state-of-the-art methods in simulations and is demonstrated in glioblastoma and breast cancer studies. The proposed PRIDE performs comparably to or outperforms most existing tools under deterministic evaluation criteria. Additionally, it offers the unique advantages, including prioritizing the differential edges with probabilities, highlighting the relative importance of hub nodes, and identifying potential sub-networks in a D-Net.

AVAILABILITY AND IMPLEMENTATION: All the data analyzed in this research can be downloaded at https://xenabrowser.net/datapages/. The R code for implementing PRIDE is available at https://github.com/YJGene0806/PRIDE_Code.

PMID:38089111 | PMC:PMC10713123 | DOI:10.1093/bioadv/vbad172

ACS Mater Au. 2023 May 16;3(5):442-449. doi: 10.1021/acsmaterialsau.3c00018. eCollection 2023 Sep 13.

ABSTRACT

Living cells are characterized by the micrometric confinement of various macromolecules at high concentrations. Using droplets containing binary polymer blends as artificial cells, we previously showed that cell-sized confinement causes phase separation of the binary polymer solutions because of the length-dependent wetting of the polymers. Here, we demonstrate that the confinement-induced heterogeneity of polymers also emerges in single-component polymer solutions. The resulting structural heterogeneity also leads to a slower transport of small molecules at the center of cell-sized droplets than that in bulk solutions. Coarse-grained molecular simulations support this confinement-induced heterogeneous distribution by polymer length and demonstrate that the effective wetting of the shorter chains at the droplet surface originates from the length-dependent conformational entropy. Our results suggest that cell-sized confinement functions as a structural regulator for polydisperse polymer solutions that specifically manipulates the diffusion of molecules, particularly those with sizes close to the correlation length of the polymer chains.

PMID:38089102 | PMC:PMC10510498 | DOI:10.1021/acsmaterialsau.3c00018

Front Pharmacol. 2023 Nov 27;14:1243505. doi: 10.3389/fphar.2023.1243505. eCollection 2023.

ABSTRACT

Background: We hypothesize that the poor survival outcomes of end-stage kidney disease (ESKD) patients undergoing hemodialysis are associated with a low filtering efficiency and selectivity. The current gold standard criteria using single or several markers show an inability to predict or disclose the treatment effect and disease progression accurately. Methods: We performed an integrated mass spectrometry-based metabolomic and proteomic workflow capable of detecting and quantifying circulating small molecules and proteins in the serum of ESKD patients. Markers linked to cardiovascular disease (CVD) were validated on human induced pluripotent stem cell (iPSC)-derived cardiomyocytes. Results: We identified dozens of elevated molecules in the serum of patients compared with healthy controls. Surprisingly, many metabolites, including lipids, remained at an elevated blood concentration despite dialysis. These molecules and their associated physical interaction networks are correlated with clinical complications in chronic kidney disease. This study confirmed two uremic toxins associated with CVD, a major risk for patients with ESKD. Conclusion: The retained molecules and metabolite-protein interaction network address a knowledge gap of candidate uremic toxins associated with clinical complications in patients undergoing dialysis, providing mechanistic insights and potential drug discovery strategies for ESKD.

PMID:38089059 | PMC:PMC10715419 | DOI:10.3389/fphar.2023.1243505

Anal Chem. 2023 Dec 13. doi: 10.1021/acs.analchem.3c03765. Online ahead of print.

ABSTRACT

Spatially resolved lipidomics is pivotal for detecting and interpreting lipidomes within spatial contexts using the mass spectrometry imaging (MSI) technique. However, comprehensive and efficient lipid identification in MSI remains challenging. Herein, we introduce a high-coverage, database-driven approach combined with air-flow-assisted desorption electrospray ionization (AFADESI)-MSI to generate spatial lipid profiles across whole-body mice. Using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS), we identified 2868 unique lipids in the serum and various organs of mice. Subsequently, we systematically evaluated the distinct ionization properties of the lipids between LC-MS and MSI and created a detailed MSI database containing 14 123 ions. This method enabled the visualization of aberrant fatty acid and phospholipid metabolism across organs in a diabetic mouse model. As a powerful extension incorporated into the MSIannotator tool, our strategy facilitates the rapid and accurate annotation of lipids, providing new research avenues for probing spatially resolved heterogeneous metabolic changes in response to diseases.

PMID:38088904 | DOI:10.1021/acs.analchem.3c03765

Microbiol Spectr. 2023 Dec 13:e0337423. doi: 10.1128/spectrum.03374-23. Online ahead of print.

ABSTRACT

Flavonoids are a group of compounds generally produced by plants with proven biological activity, which have recently beeen recommended for the treatment and prevention of diseases and ailments with diverse causes. In this study, naringenin was produced in adequate amounts in yeast after in silico design. The four genes of the involved enzymes from several organisms (bacteria and plants) were multi-expressed in two vectors carrying each two genes linked by a short viral peptide sequence. The batch kinetic behavior of the product, substrate, and biomass was described at lab scale. The engineered strain might be used in a more affordable and viable bioprocess for industrial naringenin procurement.

PMID:38088543 | DOI:10.1128/spectrum.03374-23

Plant Physiol. 2023 Dec 13:kiad658. doi: 10.1093/plphys/kiad658. Online ahead of print.

ABSTRACT

Angiosperms are characterized by the formation of flowers, and in their inner floral whorl, one or various gynoecia are produced. These female reproductive structures are responsible for fruit and seed production, thus ensuring the reproductive competence of angiosperms. In Arabidopsis (Arabidopsis thaliana), the gynoecium is composed of two fused carpels with different tissues that need to develop and differentiate to form a mature gynoecium and thus the reproductive competence of Arabidopsis. For these reasons, they have become the object of study for floral and fruit development. However, due to the complexity of the gynoecium, specific spatio-temporal tissue expression patterns are still scarce. In this study, we used precise laser-assisted microdissection and high-throughput RNA sequencing to describe the transcriptional profiles of the medial and lateral domain tissues of the Arabidopsis gynoecium. We provide evidence that the method used is reliable and that, in addition to corroborating gene expression patterns of previously reported regulators of these tissues, we found genes whose expression dynamics point to being involved in cytokinin and auxin homeostasis and in cell cycle progression. Furthermore, based on differential gene expression analyses, we functionally characterized several genes and found that they are involved in gynoecium development. This resource is available via the Arabidopsis eFP browser and will serve the community in future studies on developmental and reproductive biology.

PMID:38088205 | DOI:10.1093/plphys/kiad658

J R Soc Interface. 2023 Dec;20(209):20230374. doi: 10.1098/rsif.2023.0374. Epub 2023 Dec 13.

ABSTRACT

A key challenge for public health policymakers is determining when an infectious disease outbreak has finished. Following a period without cases, an estimate of the probability that no further cases will occur in future (the end-of-outbreak probability) can be used to inform whether or not to declare an outbreak over. An existing quantitative approach (the Nishiura method), based on a branching process transmission model, allows the end-of-outbreak probability to be approximated from disease incidence time series, the offspring distribution and the serial interval distribution. Here, we show how the end-of-outbreak probability under the same transmission model can be calculated exactly if data describing who-infected-whom (the transmission tree) are also available (e.g. from contact tracing studies). In that scenario, our novel approach (the traced transmission method) is straightforward to use. We demonstrate this by applying the method to data from previous outbreaks of Ebola virus disease and Nipah virus infection. For both outbreaks, the traced transmission method would have determined that the outbreak was over earlier than the Nishiura method. This highlights that collection of contact tracing data and application of the traced transmission method may allow stringent control interventions to be relaxed quickly at the end of an outbreak, with only a limited risk of outbreak resurgence.

PMID:38086402 | DOI:10.1098/rsif.2023.0374