Sex-specific proximal tubular cell differentiation pathways identified by single-nucleus RNA sequencing.

Postnatal kidney growth is substantial and involves expansion in kidney tubules without growth of new nephrons, which are the functional units of the kidney. Proliferation and differentiation pathways underpinning nephron elongation are not well defined. To address this, we performed sequential characterization of mouse kidney transcriptomics at the single cell level. Single nuclear RNA sequencing (snRNA-seq) was performed on kidney tissue from male and female mice at 1, 2, 4 and 12 weeks of age using the 10x Chromium platform. Unbiased clustering was performed on 68,775 nuclei from 16 animals. 31 discrete cellular clusters were seen, which were identified through comparison of their gene expression profiles to canonical markers of kidney cell populations. High levels of proliferation were evident at early time points in some cell types, especially tubular cells, but not in other cell types, for example podocytes. Proliferation was especially evident in Proximal Tubular Cells (PTCs) which are the most abundant cell type in the adult kidney. Uniquely when compared to other kidney cell types, PTCs demonstrated sex-specific expression profiles at late, but not early, time points. Mapping of PTC differentiation pathways using techniques including trajectory and RNA Velocity analyses delineated increasing PTC specialization and sex-specific phenotype specification. Our single-cell transcriptomics data characterise cellular states observed during kidney growth. We have identified PTC differentiation pathways that lead to sex-specific tubular cell phenotypes. Tubular proliferative responses are of central importance in postnatal kidney growth and have also been linked to kidney recovery versus fibrosis following injury. Our unbiased and comprehensive dataset of tubular cell development can be used to identify candidate pathways for therapeutic targeting.

A high ratio of linoleic acid (n-6 PUFA) to alpha-linolenic acid (n-3 PUFA) adversely affects early stage of human neuronal differentiation and electrophysiological activity of glutamatergic neurons in vitro.

Introduction: There is a growing interest in the possibility of dietary supplementation with polyunsaturated fatty acids (PUFAs) for treatment and prevention of neurodevelopmental and neuropsychiatric disorders. Studies have suggested that of the two important classes of polyunsaturated fatty acids, omega-6 (n-6) and omega-3 (n-3), n-3 polyunsaturated fatty acids support brain development and function, and when used as a dietary supplement may have beneficial effects for maintenance of a healthy brain. However, to date epidemiological studies and clinical trials on children and adults have been inconclusive regarding treatment length, dosage and use of specific n-3 polyunsaturated fatty acids. The aim of this study is to generate a simplified in vitro cell-based model system to test how different n-6 to n-3 polyunsaturated fatty acids ratios affect human-derived neurons activity as a cellular correlate for brain function and to probe the mechanism of their action. Methods: All experiments were performed by use of human induced pluripotent stem cells (iPSCs). In this study, we examined the effect of different ratios of linoleic acid (n-6) to alpha-linolenic acid in cell growth medium on induced pluripotent stem cell proliferation, generation of neuronal precursors and electrophysiology of cortical glutamatergic neurons by multielectrode array (MEA) analysis. Results: This study shows that at a n-6:n-3 ratio of 5:1 polyunsaturated fatty acids induce stem cell proliferation, generating a large increase in number of cells after 72 h treatment; suppress generation of neuronal progenitor cells, as measured by decreased expression of FOXG1 and Nestin in neuronal precursor cells (NPC) after 20 days of development; and disrupt neuronal activity in vitro, increasing spontaneous neuronal firing, reducing synchronized bursting receptor subunits. We observed no significant differences for neuronal precursor cells treated with ratios 1:3 and 3:1, in comparison to 1:1 control ratio, but higher ratios of n-6 to n-3 polyunsaturated fatty acids adversely affect early stages of neuronal differentiation. Moreover, a 5:1 ratio in cortical glutamatergic neurons induce expression of GABA receptors which may explain the observed abnormal electrophysiological activity.

Nuclear factor I-C overexpression promotes monocytic development and cell survival in acute myeloid leukemia.

Nuclear factor I-C (NFIC) belongs to a family of NFI transcription factors that binds to DNA through CAATT-boxes and are involved in cellular differentiation and stem cell maintenance. Here we show NFIC protein is significantly overexpressed in 69% of acute myeloid leukemia patients. Examination of the functional consequences of NFIC overexpression in HSPCs showed that this protein promoted monocytic differentiation. Single-cell RNA sequencing analysis further demonstrated that NFIC overexpressing monocytes had increased expression of growth and survival genes. In contrast, depletion of NFIC through shRNA decreased cell growth, increased cell cycle arrest and apoptosis in AML cell lines and AML patient blasts. Further, in AML cell lines (THP-1), bulk RNA sequencing of NFIC knockdown led to downregulation of genes involved in cell survival and oncogenic signaling pathways including mixed lineage leukemia-1 (MLL-1). Lastly, we show that NFIC knockdown in an ex vivo mouse MLL::AF9 pre-leukemic stem cell model, decreased their growth and colony formation and increased expression of myeloid differentiation markers Gr1 and Mac1. Collectively, our results suggest that NFIC is an important transcription factor in myeloid differentiation as well as AML cell survival and is a potential therapeutic target in AML.

Modeling of open, closed, and open-inactivated states of the hERG1 channel: structural mechanisms of the state-dependent drug binding.

The human ether-a-go-go related gene 1 (hERG1) K ion channel is a key element for the rapid component of the delayed rectified potassium current in cardiac myocytes. Since there are no crystal structures for hERG channels, creation and validation of its reliable atomistic models have been key targets in molecular cardiology for the past decade. In this study, we developed and vigorously validated models for open, closed, and open-inactivated states of hERG1 using a multistep protocol. The conserved elements were derived using multiple-template homology modeling utilizing available structures for Kv1.2, Kv1.2/2.1 chimera, and KcsA channels. Then missing elements were modeled with the ROSETTA De Novo protein-designing suite and further refined with all-atom molecular dynamics simulations. The final ensemble of models was evaluated for consistency to the reported experimental data from biochemical, biophysical, and electrophysiological studies. The closed state models were cross-validated against available experimental data on toxin footprinting with protein-protein docking using hERG state-selective toxin BeKm-1. Poisson-Boltzmann calculations were performed to determine gating charge and compare it to electrophysiological measurements. The validated structures offered us a unique chance to assess molecular mechanisms of state-dependent drug binding in three different states of the channel.

Oxylipin metabolism is controlled by mitochondrial ß-oxidation during bacterial inflammation.

Oxylipins are potent biological mediators requiring strict control, but how they are removed en masse during infection and inflammation is unknown. Here we show that lipopolysaccharide (LPS) dynamically enhances oxylipin removal via mitochondrial ß-oxidation. Specifically, genetic or pharmacological targeting of carnitine palmitoyl transferase 1 (CPT1), a mitochondrial importer of fatty acids, reveal that many oxylipins are removed by this protein during inflammation in vitro and in vivo. Using stable isotope-tracing lipidomics, we find secretion-reuptake recycling for 12-HETE and its intermediate metabolites. Meanwhile, oxylipin ß-oxidation is uncoupled from oxidative phosphorylation, thus not contributing to energy generation. Testing for genetic control checkpoints, transcriptional interrogation of human neonatal sepsis finds upregulation of many genes involved in mitochondrial removal of long-chain fatty acyls, such as ACSL1,3,4, ACADVL, CPT1B, CPT2 and HADHB. Also, ACSL1/Acsl1 upregulation is consistently observed following the treatment of human/murine macrophages with LPS and IFN-γ. Last, dampening oxylipin levels by ß-oxidation is suggested to impact on their regulation of leukocyte functions. In summary, we propose mitochondrial ß-oxidation as a regulatory metabolic checkpoint for oxylipins during inflammation.

Bioactivities and in silico study of Pergularia tomentosa L. phytochemicals as potent antimicrobial agents targeting type IIA topoisomerase, TyrRS, and Sap1 virulence proteins.

Pergularia tomentosa L. (P. tomentosa) has been largely used in Tunisian folk medicine as remedies against skin diseases, asthma, and bronchitis. The main objectives of this study were to identify phytochemical compounds that have antioxidant and antimicrobial properties from the stem, leaves, and fruit crude methanolic extracts of P. tomentosa, and to search for tyrosyl-tRNA synthetase (TyrRS), topoisomerase type IIA, and Candidapepsin-1 (SAP1) enzyme inhibitors through molecular docking study. Phytochemical quantification revealed that fruit and leaves extracts displayed the highest total flavonoids (582 mg QE/g Ex; 219 mg QE/g Ex) and tannins content (375 mg TAE/g Ex; 216 mg TAE/g Ex), also exhibiting significant scavenging activity to decrease free radicals for ABTS, DPPH, ß-carotene, and FRAP assay with IC50 values (> 1 mg/mL). Additionally, promising antimicrobial activities towards different organs have been observed against several bacteria and Candida strains. From the liquid chromatography-mass spectrometry (LC-MS) analysis, five polyphenolic compounds, namely digitoxigenin, digitonin glycoside and calactina in the leaves, kaempferol in the fruit, and calotropagenin in the stems, were identified. They were also analyzed for their drug likeliness, based on computational methods. Molecular docking study affirmed that the binding affinity of calactin and actodigin to the active site of TyrRS, topoisomerase type IIA, and SAP1 target virulence proteins was the highest among the examined dominant compounds. Therefore, this study indicated that P. tomentosa methanolic extracts displayed great potential to become a potent antimicrobial agent and might be a promising source for therapeutic and nutritional functions. These phytocompounds could be further promoted as a candidate for drug discovery and development.

Ilimaquinone (marine sponge metabolite) as a novel inhibitor of SARS-CoV-2 key target proteins in comparison with suggested COVID-19 drugs: designing, docking and molecular dynamics simulation study.

The outbreak of novel coronavirus, SARS-CoV-2, has infected more than 36 million people and caused approximately 1 million deaths around the globe as of 9 October 2020. The escalating outspread of the virus and rapid rise in the number of cases require the instantaneous development of effectual drugs and vaccines. Presently, there are no approved drugs or vaccine available to treat the infection. In such scenario, one of the propitious therapeutic approaches against viral infection is to explore enzyme inhibitors amidst natural compounds, utilizing computational approaches aiming to get products with negligible side effects. In the present study, the inhibitory prospects of ilimaquinone (marine sponge metabolite) were assessed in comparison with hydroxychloroquine, azithromycin, favipiravir, ivermectin and remdesivir at the active binding pockets of nine different vital SARS-CoV-2 target proteins (spike receptor binding domain, RNA-dependent RNA polymerase, Nsp10, Nsp13, Nsp14, Nsp15, Nsp16, main protease, and papain-like-protease), employing an in silico molecular interaction based approach. In addition, molecular dynamics (MD) simulations of the SARS-CoV-2 papain-like protease (PLpro)-ilimaquinone complex were also carried out to calculate various structural parameters including root mean square fluctuation (RMSF), root mean square deviation (RMSD), radius of gyration (R g) and hydrogen bond interactions. PLpro is a promising drug target, due to its imperative role in viral replication and additional function of stripping ubiquitin and interferon-stimulated gene 15 (ISG15) from host-cell proteins. In light of the possible inhibition of all vital SARS-CoV-2 target proteins, our study has emphasized the importance to study in depth ilimaquinone actions in vivo.

Effect of Adiantum philippense Extract on Biofilm Formation, Adhesion With Its Antibacterial Activities Against Foodborne Pathogens, and Characterization of Bioactive Metabolites: An in vitro-in silico Approach.

Adiantum philippense (A. philippense), an ethnomedicinally important fern, has become an interesting herb in the search for novel bioactive metabolites, which can also be used as therapeutic agents. Primarily, in this study, A. philippense crude extract was screened for its phytochemical constituents, antagonistic potential, and effect on bacterial adhesion and biofilm formation against common food pathogens. Phytochemical profiling of A. philippense was carried out by using High Resolution-Liquid Chromatography and Mass Spectroscopy (HR-LCMS) followed by antibacterial activity via agar cup/well diffusion, broth microdilution susceptibility methods, and growth curve analysis. Antibiofilm potency and efficacy were assessed on the development, formation, and texture of biofilms through light microscopy, fluorescent microscopy, scanning electron microscopy, and the assessment of exopolysaccharide production. Correspondingly, a checkerboard test was performed to evaluate the combinatorial effect of A. philippense and chloramphenicol. Lastly, molecular docking studies of identified phytochemicals with adhesin proteins of tested food pathogens, which helps the bacteria in surface attachment and leads to biofilm formation, were assessed. A. philippense crude extract was found to be active against all tested food pathogens, displaying the rapid time-dependent kinetics of bacterial killing. A. philippense crude extract also impedes the biofilm matrix by reducing the total content of exopolysaccharide, and, likewise, the microscopic images revealed a great extent of disruption in the architecture of biofilms. A synergy was observed between A. philippense crude extract and chloramphenicol for E. coli, S. aureus, and P. aeruginosa, whereas an additive effect was observed for S. flexneri. Various bioactive phytochemicals were categorized from A. philippense crude extract using HR-LCMS. The molecular docking of these identified phytochemicals was interrelated with the active site residues of adhesin proteins, IcsA, Sortase A, OprD, EspA, and FimH from S. flexneri, S. aureus, P. aeruginosa, and E. coli, respectively. Thus, our findings represent the bioactivity and potency of A. philippense crude extract against food pathogens not only in their planktonic forms but also against/in biofilms for the first time. We have also correlated these findings with the possible mechanism of biofilm inhibition via targeting adhesin proteins, which could be explored further to design new bioactive compounds against biofilm producing foodborne bacterial pathogens.

PLIT: An alignment-free computational tool for identification of long non-coding RNAs in plant transcriptomic datasets.

Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs which play a significant role in several biological processes. RNA-seq based transcriptome sequencing has been extensively used for identification of lncRNAs. However, accurate identification of lncRNAs in RNA-seq datasets is crucial for exploring their characteristic functions in the genome as most coding potential computation (CPC) tools fail to accurately identify them in transcriptomic data. Well-known CPC tools such as CPC2, lncScore, CPAT are primarily designed for prediction of lncRNAs based on the GENCODE, NONCODE and CANTATAdb databases. The prediction accuracy of these tools often drops when tested on transcriptomic datasets. This leads to higher false positive results and inaccuracy in the function annotation process. In this study, we present a novel tool, PLIT, for the identification of lncRNAs in plants RNA-seq datasets. PLIT implements a feature selection method based on L1 regularization and iterative Random Forests (iRF) classification for selection of optimal features. Based on sequence and codon-bias features, it classifies the RNA-seq derived FASTA sequences into coding or long non-coding transcripts. Using L1 regularization, 31 optimal features were obtained based on lncRNA and protein-coding transcripts from 8 plant species. The performance of the tool was evaluated on 7 plant RNA-seq datasets using 10-fold cross-validation. The analysis exhibited superior accuracy when evaluated against currently available state-of-the-art CPC tools.