Biology subjects

Chen, R.

Publications and source records attributed to Chen, R..

At least 217 records · Page 12Linked to original sources

bioRxiv2023

Toleration of Frameshift Mutations in mRNA Sequences Encoding the N-terminal Peptides of Bacterial Type III Effectors

Gram-negative bacteria deliver effector proteins into eukaryotic host cells through type III and type IV secretion systems, causing infections and diseases. It remains unclear about the signals guiding the specific secretion of the effectors. Here, we adopted an in silico approach to analyze the mRNA sequences encoding the putative peptides essential for effective secretion and translocation of type III and IV effectors. A surprisingly high proportion of type III effectors showed tolerance on frameshift mutations in signal-encoding mRNA sequences, and in contrast, very low percentage of type IV effectors showed the similar frameshift tolerance. The type III effectors with frameshift tolerance of secretion signals were widely distributed in effector or signal families and bacterial species. Natural frameshifts could be identified in type III effector genes, which were often remedied in time by nearby paired insertions or deletions. Frameshift-derived peptide sequences also retained the common properties present in the signal peptides of raw type III effectors. Natural language processing models were adopted to represent the common features in the mRNA sequences encoding N-terminal peptides of type III effectors or C-terminal peptides of type IV effectors, with which transfer learning models could well predict the effectors, especially type IV effectors. The observations in the study would facilitate us understand the nature and evolution of secretion signals of type III and IV effectors. SignificanceIt has been a debate on the nature of signals for translocation of type III secreted effectors for a long time. Meanwhile, there has been no examination on the possibility of mRNA being as translocation signals for type IV or other types of secreted effectors. By computational simulation, the study demonstrated the protein nature of translocation signals for both type IV effectors and most type III effectors. Despite wide frameshift tolerance and atypical common features in mRNA sequences encoding the putative N-terminal signal sequences of type III effectors, more typical common physicochemical and amino acid composition properties between the mutation-derived and raw peptides, and the frequent self-correction phenomenon for naturally happening frameshifts supported the translocation signals at protein level of type III effectors. The common features in mRNA sequences encoding the translocation signal peptides of type III and IV effectors could also be combined in models for better prediction of the effectors respectively.

microbiology↗

bioRxiv2023

Robust Removal of Slow Artifactual Dynamics Induced by Deep Brain Stimulation in Local Field Potential Recordings using SVD-based Adaptive Filtering

Deep brain stimulation (DBS) is widely used as a treatment option for patients with movement disorders. In addition to its clinical impact, DBS has been utilized in the field of cognitive neuroscience wherein the answers to several fundamental questions underpinning the mechanisms of neuromodulation in decision making rely on how a burst of DBS pulses, usually delivered at clinical frequency, i.e., 130 Hz, perturb participants choices. It was observed that neural activities recorded during DBS were contaminated with stereotype large artifacts, which lasts for a few milliseconds, as well as a low-frequency (slow) signal ([~]1-2 Hz) that can persist for hundreds of milliseconds. While the focus of the most of methods for removing DBS artifact was on the former, the artifact removal of the slow signal has not been addressed. In this work, we propose a new method based on combining singular value decomposition (SVD) and normalized adaptive filtering to remove both large (fast) and slow artifacts in local field potentials recorded during a cognitive task in which bursts of DBS were utilized. Using synthetic data, we show that our proposed algorithm outperforms four commonly used techniques in the literature, namely, (1) Normalized least mean square adaptive filtering, (2) Optimal FIR Wiener filtering, (3) Gaussian model matching, and (4) Moving average. The algorithms capabilities are further demonstrated by its ability to effectively remove DBS artifacts in local field potentials recorded from the subthalamic nucleus during a verbal Stroop task, highlighting its utility in real-world applications.

neuroscience↗

bioRxiv2023

Single-cell transcriptome analysis reveals the cellular atlas of human intracranial aneurysm and highlights inflammation features associated with aneurysm rupture

Intracranial aneurysm (IA) is pouch-like pathological dilations of cerebral arteries, which often affects middle-aged people and culminates in life-threatening hemorrhagic stroke. A deeper knowledge of the cellular and gene expression perturbations in human IA tissue deepens our understanding of disease mechanisms and facilitates developing pharmacological targets for unruptured IA. In this study, 21,332 qualified cells were obtained from cell-sparse ruptured and unruptured human IA tissues and a detailed cellular profile was determined, including conventional endothelial cells, smooth muscle cells (SMC), fibroblasts and the newly identified pericytes. Notably, striking proportion of immune cells were identified in IA tissue, with the number of monocyte/macrophages and neutrophils being remarkably higher in ruptured IA. By leveraging external datasets and machine learning algorithms, a subset of macrophages characterized by high expression of CCL3 and CXCL3, and transcriptional activation of NF-{kappa}B and HIVEP2 was identified as the cell most associated with IA rupture. Further, the interactome of CCL3/CXCL3 macrophages disclosed their role in regulating vascular cell survival and orchestrating inflammation. In summary, this study illustrated the profile and interactions of vascular and immune cells in human IA tissue and the opportunities for targeting local chronic inflammation.

cell biology↗

bioRxiv2023

Effects of six pyrimidine analogs on the growth of Tetrahymena thermophila and their implications in pyrimidine metabolism

Tetrahymena are ciliated protists that have been used to study the effects of toxic chemicals, including anticancer drugs. In this study, we tested the inhibitory effects of six pyrimidine analogs (5-fluorouracil, floxuridine, 5-deoxy-5-fluorouridine, 5-fluorouridine, gemcitabine, cytarabine) on wild-type CU428 and conditional mutant NP1 Tetrahymena thermophila at room temperature and the restrictive temperature (37{degrees}C) where NP1 does not form the oral apparatus. We found that cytarabine was the only tested analog that did not inhibit growth, and phagocytosis was not required for pyrimidine analog entry. IC50 values did not significantly differ between strains for the same analog at either temperature. To investigate the mechanism of inhibition, we used two pyrimidine bases (uracil and thymine) and three nucleosides (uridine, thymidine, 5-methyluridine) to help determine whether the inhibitory effects from analogs were reversible. We found that the inhibitory effects from 5-fluorouracil could be reversed by uracil and thymine, from floxuridine could be reversed by thymidine, and from 5-deoxy-5-fluorouridine could be reversed by uracil. None of the tested nucleobases or nucleosides could reverse the inhibitory effects of gemcitabine or 5-fluorouridine. Our results suggest that the five pyrimidine analogs act on different sites to inhibit T. thermophila growth and that nucleobases and nucleosides are metabolized differently.

cell biology↗

bioRxiv2023

Retroelement decay by the exonuclease XRN1 is a viral mimicry dependency in cancer

Viral mimicry describes the immune response induced by endogenous stimuli such as dsRNA formed by endogenous retroelements. Activation of viral mimicry has the potential to kill cancer cells or augment anti-tumor immune response. Paradoxically, cancer cells frequently present a dysregulated epigenome, leading to increased expression of retroelements. We previously found that ADAR1 p150 upregulation is an adaptation mechanism to tolerate high retroelement-derived dsRNA levels, leading to a druggable dependency. Here, we systematically identified novel mechanisms of viral mimicry adaptation associated with cancer cell dependencies. We correlated the gene knockout sensitivity from the DepMap dataset and interferon stimulated gene (ISG) expression in the Cancer Cell Line Encyclopedia (CCLE) dataset of 1005 human cell lines and identified pathways such as RNA modification and nucleic acid metabolism. Among the top hits was the RNA decay protein XRN1 as an essential gene for the survival of a subset of cancer cell lines. XRN1-sensitive cancer cell lines have a high level of cytosolic dsRNA and high ISG expression. Furthermore, sensitivity to XRN1 knockout was mediated by MAVS and PKR activation, indicating that the cells die due to XRN1-dependent induction of viral mimicry. XRN1-resistant cell lines had low basal dsRNA levels, but became synthetically dependent on XRN1 upon treatment with viral mimicry inducing drugs such as 5-AZA-CdR or palbociclib. Finally, XRN1-dependency is partly independent of ADAR1 activity. These results confirm the potential for our ISG correlation analysis to discover novel regulators of viral mimicry and show that XRN1 activation is an adaptive mechanism to control high dsRNA stress induced by dysregulated retroelements in cancer cells and creates a dependency that can be explored for novel cancer therapies.

cell biology↗

bioRxiv2023

Genome-scale enzymatic reaction prediction by variational graph autoencoders

BackgroundEnzymatic reaction networks are crucial to explore the mechanistic function of metabolites and proteins in biological systems and understanding the etiology of diseases and potential target for drug discovery. The increasing number of metabolic reactions allows the development of deep learning-based methods to discover new enzymatic reactions, which will expand the landscape of existing enzymatic reaction networks to investigate the disrupted metabolisms in diseases. ResultsIn this study, we propose the MPI-VGAE framework to predict metabolite-protein interactions (MPI) in a genome-scale heterogeneous enzymatic reaction network across ten organisms with thousands of enzymatic reactions. We improved the Variational Graph Autoencoders (VGAE) model to incorporate both molecular features of metabolites and proteins as well as neighboring features to achieve the best predictive performance of MPI. The MPI-VGAE framework showed robust performance in the reconstruction of hundreds of metabolic pathways and five functional enzymatic reaction networks. The MPI-VGAE framework was also applied to a homogenous metabolic reaction network and achieved as high performance as other state-of-art methods. Furthermore, the MPI-VGAE framework could be implemented to reconstruct the disease-specific MPI network based on hundreds of disrupted metabolites and proteins in Alzheimers disease and colorectal cancer, respectively. A substantial number of new potential enzymatic reactions were predicted and validated by molecular docking. These results highlight the potential of the MPI-VGAE framework for the discovery of novel disease-related enzymatic reactions and drug targets in real-world applications. Data availability and implementationThe MPI-VGAE framework and datasets are publicly accessible on GitHub https://github.com/mmetalab/mpi-vgae. Author BiographiesCheng Wang received his Ph.D. in Chemistry from The Ohio State Univesity, USA. He is currently a Assistant Professor in School of Public Health at Shandong University, China. His research interests include bioinformatics, machine learning-based approach with applications to biomedical networks. Chuang Yuan is a research assistant at Shandong University. He obtained the MS degree in Biology at the University of Science and Technology of China. His research interests include biochemistry & molecular biology, cell biology, biomedicine, bioinformatics, and computational biology. Yahui Wang is a PhD student in Department of Chemistry at Washington University in St. Louis. Her research interests include biochemistry, mass spectrometry-based metabolomics, and cancer metabolism. Ranran Chen is a master graduate student in School of Public Health at University of Shandong, China. Yuying Shi is a master graduate student in School of Public Health at University of Shandong, China. Gary J. Patti is the Michael and Tana Powell Professor at Washington University in St. Louis, where he holds appointments in the Department of Chemisrty and the Department of Medicine. He is also the Senior Director of the Center for Metabolomics and Isotope Tracing at Washington University. His research interests include metabolomics, bioinformatics, high-throughput mass spectrometry, environmental health, cancer, and aging. Leyi Wei received his Ph.D. in Computer Science from Xiamen University, China. He is currently a Professor in School of Software at Shandong University, China. His research interests include machine learning and its applications to bioinformatics. Qingzhen Hou received his Ph.D. in the Centre for Integrative Bioinformatics VU (IBIVU) from Vrije Universiteit Amsterdam, the Netherlands. Since 2020, He has serveved as the head of Bioinformatics Center in National Institute of Health Data Science of China and Assistant Professor in School of Public Health, Shandong University, China. His areas of research are bioinformatics and computational biophysics. Key pointsO_LIGenome-scale heterogeneous networks of metabolite-protein interaction (MPI) based on thousands of enzymatic reactions across ten organisms were constructed semi-automatically. C_LIO_LIAn enzymatic reaction prediction method called Metabolite-Protein Interaction Variational Graph Autoencoders (MPI-VGAE) was developed and optimized to achieve higher performance compared with existing machine learning methods by using both molecular features of metabolites and proteins. C_LIO_LIMPI-VGAE is broadly useful for applications involving the reconstruction of metabolic pathways, functional enzymatic reaction networks, and homogenous networks (e.g., metabolic reaction networks). C_LIO_LIBy implementing MPI-VGAE to Alzheimers disease and colorectal cancer, we obtained several novel disease-related protein-metabolite reactions with biological meanings. Moreover, we further investigated the reasonable binding details of protein-metabolite interactions using molecular docking approaches which provided useful information for disease mechanism and drug design. C_LI

bioinformatics↗

bioRxiv2023

Connectional Hierarchy in Human Brain Revealed by Individual Variability of Functional Network Edges

The human cerebral cortex exhibits intricate interareal functional synchronization at the macroscale, with substantial individual variability in these functional connections. However, the spatial organization of functional connectivity (FC) variability across the human connectome edges and its significance in cognitive development remain unclear. Here, we identified a connectional axis in the edge-level FC variability. The variability declined continuously along this axis from within-network to between-network connections, and from the edges linking association networks to those linking the sensorimotor and association networks. This connectional axis of functional variability is associated with spatial pattern of structural connectivity variability. Moreover, the connectional variability axis evolves in youth with an increasing flatter axis slope. We also observed that the slope of connectional variability axis was positively related to the performance in the higher-order cognition. Together, our results reveal a connectional axis in functional variability that is linked with structural connectome variability, refines during development, and is relevant to cognition. Significance StatementUnderstanding the spatial organization of inter-individual variability in functional connectivity across the human connectome can offer insights into which connections are most susceptible to insults and interventions. We identify a stable axis on functional connectome along which connectivity variability continuously varies, aligning with structural connectivity variability. We find that the pattern of this axis evolves during development, marked by a decrease in functional connectivity variability among association connections. Moreover, the variability axis is associated with individual differences in higher-order cognitions, driven by increased variability in higher-order association connections linked to enhanced cognitive performance. These findings highlight the importance of connectivity-specific plasticity in understanding both typical and atypical cognitive development across diverse populations.

neuroscience↗

bioRxiv2023

Efficient and scalable prediction of spatio-temporal stochastic gene expression in cells and tissues using graph neural networks

The simulation of spatial stochastic models is highly computationally expensive, an issue that has severely limited our understanding of the spatial nature of gene expression. Here we devise a graph neural network based method to learn, from stochastic trajectories in a small region of space, an effective master equation for the time-dependent marginal probability distributions of mRNA and protein numbers at sub-cellular resolution for every cell in a tissue. Numerical solution of this equation leads to accurate results in a small fraction of the computation time of standard simulation methods. Moreover its predictions can be extrapolated to a spatial organisation (a cell network topology) and regions of parameter space unseen in its neural network training. The scalability and accuracy of the method suggest it is a promising approach for whole cell modelling and for detailed comparisons of stochastic models with spatial genomics data.

systems biology↗

bioRxiv2023

A molecularly distinct accumbal-to-lateral hypothalamic circuit modulates food seeking and consumption

Orchestrating complex behavioral states, such as approach and consumption of food, is critical for survival. In addition to hypothalamus neuronal circuits, the nucleus accumbens (NAc) also plays an important role in controlling appetite and satiety in responses to changing external stimuli. However, the specific neuronal subtypes of NAc involved as well as how the humoral and neuronal signals coordinate to regulate feeding remain incompletely understood. Here, we deciphered the spatial diversity of neuron subtypes of the NAc shell (NAcSh) and defined a dopamine receptor D1(Drd1)- and Serpinb2-expressing subtype located in NAcSh encoding food consumption. Chemogenetics- and optogenetics-mediated regulation of Serpinb2+ neurons bidirectionally regulates food seeking and consumption specifically. Circuitry stimulation revealed the NAcShSerpinb2[->]LHLepR projection controls refeeding and can overcome leptin-mediated feeding suppression. Furthermore, NAcSh Serpinb2+ neuron ablation reduces food intake and upregulates energy expenditure resulting in body weight loss. Together, our study reveals a neural circuit consisted of molecularly distinct neuronal subtype that bidirectionally regulates energy homeostasis, which can serve as a potential therapeutic target for eating disorders.

neuroscience↗

bioRxiv2023

Boosting the toolbox for live imaging of translation

Live imaging of translation based on tag recognition by a single chain antibody is a powerful technique to assess translation regulation in living cells. However, especially in a multicellular organism, this approach is challenging and requires optimization in terms of expression level and detection sensitivity of the system. Here, we improved existing fluorescent tools and developed new ones to image and quantify nascent translation in the living Drosophila embryo and in mammalian cells. We tested and characterized five different Green Fluorescent Protein variants fused to the single chain fragment variable (scFv) and uncover photobleaching, aggregation and intensity disparities. Using different strengths of germline and somatic drivers, we determined that the availability of the scFv is critical in order to detect translation throughout development. We introduced a new translation imaging method based on a nanobody/tag system named ALFA-array, allowing the sensitive and simultaneous detection of the translation of several distinct mRNA species. Finally, we developed a largely improved RNA imaging system based on an MCP-tdStaygold fusion.

developmental biology↗

bioRxiv2023

Cerebellar Granule Cells Develop Non-neuronal 3D Genome Architecture over the Lifespan

The cerebellum contains most of the neurons in the human brain, and exhibits unique modes of development, malformation, and aging. For example, granule cells--the most abundant neuron type--develop unusually late and exhibit unique nuclear morphology. Here, by developing our high-resolution single-cell 3D genome assay Dip-C into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we were able to resolve the first 3D genome structures of single cerebellar cells, create life-spanning 3D genome atlases for both human and mouse, and jointly measure transcriptome and chromatin accessibility during development. We found that while the transcriptome and chromatin accessibility of human granule cells exhibit a characteristic maturation pattern within the first year of postnatal life, 3D genome architecture gradually remodels throughout life into a non-neuronal state with ultra-long-range intra-chromosomal contacts and specific inter-chromosomal contacts. This 3D genome remodeling is conserved in mice, and robust to heterozygous deletion of chromatin remodeling disease-associated genes (Chd8 or Arid1b). Together these results reveal unexpected and evolutionarily-conserved molecular processes underlying the unique development and aging of the mammalian cerebellum.

neuroscience↗

bioRxiv2023

Auditory confounds can drive online effects of transcranial ultrasonic stimulation in humans

Transcranial ultrasonic stimulation (TUS) is rapidly emerging as a promising non-invasive neuromodulation technique. TUS is already well-established in animal models, providing foundations to now optimize neuromodulatory efficacy for human applications. Across multiple studies, one promising protocol, pulsed at 1000 Hz, has consistently resulted in motor cortical inhibition in humans (Fomenko et al., 2020). At the same time, a parallel research line has highlighted the potentially confounding influence of peripheral auditory stimulation arising from TUS pulsing at audible frequencies. In this study, we disentangle direct neuromodulatory and indirect auditory contributions to motor inhibitory effects of TUS. To this end, we include tightly matched control conditions across four experiments, one preregistered, conducted independently at three institutions. We employed a combined transcranial ultrasonic and magnetic stimulation paradigm, where TMS-elicited motor-evoked potentials (MEPs) served as an index of corticospinal excitability. First, we replicated motor inhibitory effects of TUS but showed through both tight controls and manipulation of stimulation intensity, duration, and auditory masking conditions that this inhibition was driven by peripheral auditory stimulation, not direct neuromodulation. Further, we consider neuromodulation beyond driving overall excitation/inhibition and show preliminary evidence of how TUS might interact with ongoing neural dynamics instead. Primarily, this study highlights the substantial shortcomings in accounting for the auditory confound in prior TUS-TMS work where only a flip-over sham and no active control was used. The field must critically reevaluate previous findings given the demonstrated impact of peripheral confounds. Further, rigorous experimental design via (in)active control conditions is required to make substantiated claims in future TUS studies. Only when direct effects are disentangled from those driven by peripheral confounds can TUS fully realize its potential for research and clinical applications.

neuroscience↗

bioRxiv2023

The thalamic reticular nucleus-lateral habenula circuit regulates depressive-like behaviors in chronic stress and chronic pain

Chronic stress and chronic pain are two major predisposing factors to trigger depression. Enhanced excitatory input to the lateral habenula (LHb) has been implicated in the pathophysiology of depression. However, the contribution of inhibitory transmission remains elusive. Here, we dissect an inhibitory projection from the sensory thalamic reticular nucleus (sTRN) to LHb, which is activated by acute aversive stimuli. However, chronic restraint stress (CRS) weakens sTRN-LHb synaptic strength, and this synaptic attenuation is indispensable for CRS-induced LHb neural hyperactivity and depression onset. Moreover, artificially inhibiting sTRN-LHb circuit induces depressive-like behaviors in healthy mice, while enhancing this circuit relieves depression induced by both chronic stress and chronic pain. Intriguingly, neither neuropathic pain nor comorbid pain in chronic stress is affected by this pathway. Together, our study demonstrates a novel sTRN-LHb circuit in establishing and modulating depression, thus shedding light on potential therapeutic targets for preventing or managing depression.

neuroscience↗

bioRxiv2023

A Single Cell Genomics Atlas of the Drosophila Larval Eye Reveals Distinct Developmental Timelines and Novel Markers for All Photoreceptor Subtypes

The Drosophila eye is a powerful model system to study principles of cell differentiation, proliferation, survival and morphogenesis. However, a high-resolution single cell genomics resource that accurately captures all major cell types of the larval eye disc and their spatiotemporal relationships is lacking. Here, we report transcriptomic and chromatin accessibility data for all known cell types in the developing eye. Photoreceptors appear as streams of cells that represent dynamic developmental timelines. Photoreceptor subtypes are transcriptionally distinct when they begin to differentiate, but then converge upon a common transcriptome just 24 hours later. We identify novel cell type-specific marker genes, enhancers and potential regulators, as well as genes with distinct R3 or R4 photoreceptor specific expression. Finally, we observe that photoreceptor chromatin accessibility is more permissive than non-neuronal lens-secreting cone cells, which show a more restrictive chromatin profile. This single cell genomics atlas will greatly empower the Drosophila eye as a model system.

genomics↗

bioRxiv2023

SUMOylation of PTEN promotes DNA end resection through directly dephosphorylating 53BP1 in homologous recombination repair

Homologous recombination (HR) repair for DNA double-strand breaks (DSBs) is critical for maintaining genome stability and cell survival. Nuclear PTEN plays a key role in HR repair, but the underlying mechanism remains largely elusive. We find that SUMOylated PTEN promotes HR repair but represses non-homologous end joining (NHEJ) repair by directly dephosphorylating 53BP1. During DNA damage responses (DDR), p14ARF was phosphorylated and then interacted efficiently with PTEN, thus promoting PTEN SUMOylation as an atypical SUMO E3 ligase. Interestingly, SUMOylated PTEN was subsequently recruited to the chromatin at DNA-break sites. This was because that SUMO1 conjugated to PTEN was recognized and bound by the SUMO-interacting motif (SIM) of BRCA1, which has been located to the core of 53BP1 foci on the chromatin during S/G2 stage. Further, these chromatin-loaded PTEN directly and specifically dephosphorylated pT543 of 53BP1, resulting in the dissociation of 53BP1-complex, which facilitated DNA end resection and ongoing HR repair. The SUMOylation-deficient PTENK254R mice also showed decreased DNA damage repair in vivo. Blocking PTEN SUMOylation pathway with either an SUMOylation inhibitor or a p14ARF(2-13) peptide sensitized tumor cells to chemotherapy. Our study therefore provides the new mechanistic understanding of PTEN in HR repair and clinical intervention of chemo-resistant tumors.

cell biology↗

bioRxiv2023

Development and optimisation of cationic lipid nanoparticles for mRNA delivery

Messenger RNA (mRNA) has been proposed as a therapeutic agent for various diseases, including cancer. To ensure effective transfection of cancer cells, mRNA needs to be transported with a delivery system that protects its integrity and functionality. In this regard, cationic lipid nanoparticles composed of dioleoylphosphatidylethanolamine (DOPE) and 3{beta}-[N-(N,N-dimethylaminoethane)-carbamoyl] cholesterol (DC-Chol) have emerged as common vectors to deliver mRNA. In this project, we aim to use luciferase mRNA as a reporter to synthesise mRNA-loaded cationic lipid nanoparticles, and optimise their mRNA encapsulation and transfection efficiency in ovarian cancer cells. The optimisation process included: 1) adjusting the lipid formulation; 2) adjusting the input mRNA concentration before lipid nanoparticle extrusion; and 3) adjusting the extrusion methods. After optimisation, the encapsulation efficiency was optimised to 62%, thus achieving a relatively high transfection luminescence signal (9.4 times compared to baseline). The lipid nanoparticles also demonstrated stable physical characteristics and high biocompatibility (above 75% cell viability after treatment) within 24 hours. Overall, this project evaluated the synthesis of DOPE/DC-Chol cationic lipid nanoparticles, and optimised their mRNA encapsulation and transfection efficiency in ovarian cancer cell lines. The optimised lipid nanoparticles can be utilised as an ideal system for mRNA delivery, which could be further developed as a potential platform for the immunotherapy in ovarian cancer.

bioengineering↗

bioRxiv2023

The Medicago truncatula nodule-specific cysteine-rich peptides, NCR343 and NCR-new35 are required for the maintenance of rhizobia in nitrogen-fixing nodules.

In the nodules of Inverted Repeat-Lacking Clade legumes, including M. truncatula, nitrogen-fixing rhizobia undergo terminal differentiation resulting in elongated and endoreduplicated bacteroids specialised for nitrogen fixation. This irreversible transition of rhizobia is mediated by host produced nodule-specific cysteine-rich (NCR) peptides, of which about 700 are encoded in the M. truncatula genome. Some of these NCR peptides, NCR169, NCR211 and NCR247, are essential for nitrogen-fixing symbiosis. The analysis of bacteroid and symbiotic host cell differentiation revealed that the symbiotic phenotype of M. truncatula mutants, Mtsym19, Mtsym20 and NF-FN9363, were defective likewise in the formerly studied ncr mutants, Mtdnf4-1 and Mtdnf7-2. The incomplete differentiation of bacteroids triggered premature senescence of rhizobia in the nitrogen fixation zones of mutant nodules. Mtsym19 and Mtsym20 mutants are defective in the same peptide NCR-new35 and the lack of NCR343 is responsible for the ineffective symbiosis of NF-FN9363. The activity of NCR-new35 is significantly lower and limited to the transition zone of the nodule compared with other crucial NCRs. The fluorescent protein-tagged version of NCR343 and NCR-new35 localize to the symbiotic compartment. Our discovery added two additional members to the group of NCR genes essential for nitrogen-fixing symbiosis in M. truncatula.

plant biology↗

bioRxiv2023

Mixed Lineage Leukemia (Mll1) establishes global histone H3K4 trimethylation and stem like memory Cd8 T cell formation

CD8+ T cells with stem cell-like properties (TSCM) sustain adaptive immunity to intracellular pathogens and tumors. However, the developmental origins and chromatin regulatory factors (CRFs) that establish their differentiation are unclear. Using an RNA interference screen of all CRFs we discovered the histone methylase Mll1 was required during T cell receptor (TCR) stimulation for development of a TSCM precursor state and mature memory (TMEM) cells, but not short-lived or transitory effector cell-like states, in response to viral infections and tumors. Mll1 was essential for widespread de novo deposition of histone H3 lysine 4 trimethylation (H3K4me3) upon TCR stimulation, which accounted for 70% of all activation-induced sites in mature TMEM cells. Mll1 promoted both H3K4me3 deposition and reduced TCR-induced Pol II pausing at genes whose single-cell transcriptional dynamics explained trajectories into nascent TSCM precursor states during viral infection. Our results suggest Mll1-dependent control of Pol II elongation and H3K4me3 establishes and maintains differentiation of CD8+ TSCM cell states.

immunology↗