Biology subjects

Shen, X.

Publications and source records attributed to Shen, X..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Geometric influences on the regional organization of the mammalian brain

The mammalian brain comprises anatomically and functionally distinct regions, yet the principles governing their organization across scales remain unclear. Efforts to map regional boundaries use expert judgement or data-driven clustering of functional, connectional, and/or architectonic properties, but these approaches are often descriptive, have limited generalizability, and do not elucidate generative mechanisms. Here, we develop a geometrically constrained framework for the hierarchical, multiscale regional organization of neocortical and non-neocortical structures. The framework yields parcels at any resolution with high internal homogeneity across hundreds of anatomical, functional, cellular, and molecular properties in humans, macaques, marmosets, and mice, and it generalizes to understudied mammalian species. Finally, we demonstrate that the framework captures the essence of a reaction-diffusion mechanism in which brain geometry shapes the spatial expression of putative patterning molecules that establish a blueprint of regional identity during development. Our findings point to a conserved, universal influence of geometry on mammalian brain organization.

neuroscience↗

bioRxiv2025

Glycan-reactive antibodies isolated from human HIV-1 vaccine trial participants show broad pathogen cross-reactivity

HIV-1 continues to pose a significant global health challenge, requiring ongoing research into effective prevention and treatment strategies. Understanding the B cell repertoire that can be engaged upon vaccination in humans is crucial for the development of future preventive vaccines. In this study, PBMCs from HIV-negative participants in the multivalent HVTN124 human HIV-1 vaccine clinical trial were interrogated for HIV-reactive B cells using LIBRA-seq, a high-throughput B cell mapping technology. We report the discovery of glycan-reactive antibodies capable of neutralizing diverse heterologous HIV-1 virus strains. Further, isolated antibodies showed broad cross-reactivity against antigens from a variety of other pathogens, while remaining mostly negative on autoreactivity assays. The emerging class of glycan- reactive virus-neutralizing antibodies with exceptional breadth of pathogen cross- reactivity may present an effective target for vaccination at the population level.

immunology↗

bioRxiv2024

Kun-peng: an ultra-memory-efficient, fast, and accurate pan-domain taxonomic classifier for all

Comprehensive metagenomic sequence classification of diverse environmental samples faces significant computing memory challenges due to exponentially expanding genome databases. Here, we present Kun-peng, featuring a unique ordered 4GB block database design for ultra-efficient resource management, faster processing, and higher accuracy. When benchmarked on mock communities (Amos HiLo, Mixed, and NIST) against Kraken2, Centrifuge, and Sylph. Kun-peng matched Sylph, achieving the highest precision and lowest false-positive rates while demonstrating superior time and memory efficiency among all tested tools. Furthermore, Kun-pengs efficient database architecture enables the practical utilization of large-scale reference databases that were previously computationally prohibitive. In comprehensive testing across 586 air, water, soil, and human metagenomic samples using an expansive pan-domain database (204,477 genomes, 4.3TB), Kun-peng classified 69.78-94.29% of reads, achieving 38-43% higher classification rates than Kraken2 with the standard database. Unexpectedly, Sylph failed to classify any reads in air samples and left > 99.85% of reads unclassified in water and soil samples. In terms of computational efficiency, Kun-peng processed each sample in 0.2[~]11.2 minutes using only 4.0[~]35.4GB peak memory. Remarkably, these processing times were comparable to Kraken2 using the standard database (81GB, 5% of the pan-domain database). Memory-wise, Kun-peng required only 35.4GB peak memory with the pan-domain database, representing a 473-fold reduction compared to Kraken2. When compared to Sylph, Kun-peng processes samples up to 46.3 times faster while using up to 20.6 times less memory. Overall, Kun-peng offers an ultra-memory-efficient, fast, and accurate solution for pan-domain metagenomic classifications.

bioinformatics↗

bioRxiv2024

Spatially barcoding biochemical reactions using DNA nanostructures unveil a major contact mechanism in proximity labeling

Proximity labeling techniques like TurboID and APEX2 have become pivotal tools in spatial omics research for studying protein interactions. However, the biochemical mechanisms underlying these reactive species-mediated labelings, particularly the spatial patterns of labeling methods within the sub-m range, remain poorly understood. Here, we employed DNA nanostructure platforms to precisely measure the labeling radii of TurboID and APEX2 through in vitro assays. Our DNA nanoruler design enables the deployment of oligonucleotide-barcoded labeling targets with nanometer precision near the enzymes. By quantifying labeling yields using quantitative PCR and mapping them against target distances, we uncovered surprising insights into the labeling mechanisms. Contrary to the prevailing diffusive labeling model, our results demonstrate that TurboID primarily operates through contact-dependent labeling. Similarly, APEX2 shows high labeling efficiency within its direct contact range. In parallel, it exhibits a low-level diffusive labeling towards more distant phenols. These findings reframe our understanding in the mechanism of proximity labeling enzymes, at the same time highlight the potential of DNA nanotechnology in spatially profiling reactive species.

biochemistry↗

bioRxiv2024

A simple neural circuit model explains diverse types of integration kernels in perceptual decision-making

The ability to accumulate evidence over time for deliberate decision is essential for both humans and animals. Decades of decision-making research have documented various types of integration kernels that characterize how evidence is temporally weighted. While numerous normative models have been proposed to explain these kernels, there remains a gap in circuit models that account for the complexity and heterogeneity of single neuron activities. In this study, we sought to address this gap by using low-rank neural network modeling in the context of a perceptual decision-making task. Firstly, we demonstrated that even a simple rank-one neural network model yields diverse types of integration kernels observed in human data--including primacy, recency, and non-monotonic kernels--with a performance comparable to state-of-the-art normative models such as the drift diffusion model and the divisive normalization model. Moreover, going beyond the previous normative models, this model enabled us to gain insights at two levels. At the collective level, we derived a novel explicit mechanistic expression that explains how these kernels emerge from a neural circuit. At the single neuron level, this model exhibited heterogenous single neuron response kernels, resembling the diversity observed in neurophysiological recordings. In sum, we present a simple rank-one neural circuit that reproduces diverse types of integration kernels at the collective level while simultaneously capturing complexity of single neuron responses observed experimentally. Author SummaryThis study introduces a simple rank-one neural network model that replicates diverse integration kernels--such as primacy and recency--observed in human decision-making tasks. The model performs comparably to normative models like the drift diffusion model but offers novel insights by linking neural circuit dynamics to these kernels. Additionally, it captures the heterogeneity of single neuron responses, resembling diversity observed in experimental data. This work bridges the gap between decision-making models and the complexity of neural activity, offering a new perspective on how evidence is integrated in the brain.

neuroscience↗

bioRxiv2024

A Novel Bispecific Antibody CVL006 Superior to AK112 for Dual Targeting of PD-L1 and VEGF in Cancer Therapy

Both preclinical and clinical studies have shown that combining anti-VEGF/VEGFR drugs with immune checkpoint inhibitors (ICIs) significantly enhances anticancer efficacy. Currently, PDL-1/ VEGF bispecific antibodies demonstrate superior antitumor activity compared to monotherapy or even the combination of PD-L1 inhibitors with anti-VEGF antibodies. This enhanced efficacy results from the simultaneous blockade of the PD-1/PD-L1 pathway and the inhibition of VEGF-driven angiogenesis. In this study, we developed a novel bispecific antibody, CVL006, by fusing an anti-PDL1 VHH domain with a humanized IgG1 anti-VEGF monoclonal antibody while retaining antibody-dependent cellular cytotoxicity (ADCC) functionality. CVL006 demonstrated high affinity and specificity for both human PD-L1 and VEGF, effectively blocking both the VEGF/VEGFR signaling pathway and the PD-L1/PD-1 axis. This dual blockade not only suppressed VEGF-induced angiogenesis but also reactivated T cells, increasing the secretion of cytokines essential for immune response. In vivo studies further indicated that CVL006 achieved superior antitumor efficacy compared to the PD-L1 inhibitor atezolizumab in mouse models, with greater tumor growth inhibition and reduced angiogenesis. To compare with approved bispecific antibody PD-1/VEGF AK112 (ivonescimab), CVL006 showed superior antitumor efficacy in vivo. These findings underscore the therapeutic potential of CVL006, which integrates immune checkpoint inhibition with disruption of tumor vascularization, offering a robust and comprehensive anticancer strategy.

pharmacology and toxicology↗

bioRxiv2024

Deep-learning-enabled generative prevalent mutation prediction through host-to-herd in silico virus evolution

Predicting the mutation prevalence trends of emerging viruses in the real world is an efficient means to update vaccines or drugs in advance. It is crucial to develop a computational method for the prediction of real-world prevalent SARS-CoV-2 mutations considering the impact of multiple selective pressures within and between hosts. Here, a deep-learning generative framework for real-world prevalent SARS-CoV-2 mutation prediction, named ViralForesight, is developed on top of protein language models and in silico virus evolution. Through the paradigm of host-to-herd in silico virus evolution, ViralForesight reproduced previous real-world prevalent SARS-CoV-2 mutations for multiple lineages with superior performance. More importantly, ViralForesight correctly predicted the future prevalent mutations that dominate the COVID-19 pandemic in the real world more than half a year in advance with in vitro experimental validation. Overall, ViralForesight demonstrates a proactive approach to the prevention of emerging viral infections, accelerating the process of discovering future prevalent mutations with the power of generative deep learning.

evolutionary biology↗

bioRxiv2024

Immunofocusing on the conserved fusion peptide of HIV envelope glycoprotein in rhesus macaques

SummaryDuring infection, the fusion peptide (FP) of HIV envelope glycoprotein (Env) serves a central role in viral fusion with the host cell. As such, the FP is highly conserved and therefore an attractive epitope for vaccine design. Here, we describe a vaccination study in non-human primates (NHPs) where glycan deletions were made on soluble HIV Env to increase FP epitope exposure. When delivered via implantable osmotic pumps, this immunogen primed immune responses against the FP, which were then boosted with heterologous trimers resulting in a focused immune response targeting the conserved FP epitope. Although autologous immunizations did not elicit high affinity FP-targeting antibodies, the conserved FP epitope on a heterologous trimer further matured the lower affinity, FP-targeting B cells. This study suggests using epitope conservation strategies on distinct Env trimer immunogens can focus humoral responses on desired neutralizing epitopes and suppress immune-distracting antibody responses against non-neutralizing epitopes.

immunology↗

bioRxiv2024

Exploring the Neural Basis and Validity of Ordinal Emotion Representation through EEG

Accurately measuring emotion is a major challenge in advancing the understanding of human emotion and developing emotional artificial intelligence. In many existing studies, participants emotional ratings in interval scales are considered the true reflection of their emotional experiences. However, recent research suggests that ordinal annotations of emotions can more accurately capture the emotional expression process, providing a potential method for more precise emotion measurement. However, our understanding of the characteristics and validity of this new form of emotion representation is still relatively lacking. In particular, there is a lack of research using neural signals to explore the validity and neural basis of ordinal emotion representation. In this study, we used a video-elicited electroencephalogram (EEG) dataset (n = 123) to identify the neural basis of ordinal emotion representation and demonstrate its validity from a neural perspective. Furthermore, we explored various characteristics of ordinal emotion representation, showing how it is superior to the interval form. First, we conducted inter-situation representational similarity analysis (RSA) and inter-subject RSA to test the degree to which ordinal representation captures both group commonalities and individual differences of emotion. Next, we investigated the characteristics of ordinal representation under different combinations of emotion items, including uni-variate and multivariate emotions, positive and negative emotions. Our results show that both group commonalities and inter-subject variations in EEG features are better explained by ordinal emotion representations than by interval ones. Multivariate ordinal representations showed better inter-subject reliability and higher representational similarity with EEG features compared to uni-variate counterparts, highlighting the co-occurrence nature of human emotions. Compared to negative emotions, ordinal representation showed greater improvements for positive emotions, suggesting that the complexity of positive emotions is well captured by ordinal representations. Taken together, these findings demonstrate that multivariate ordinal emotion ratings provide a more accurate measure of real emotional experience, which is crucial for enabling machines to precisely understand and express human emotions.

neuroscience↗

bioRxiv2024

NOLC1 Suppresses Immuno-chemotherapy by Inhibiting p53-mediated Ferroptosis in Gastric Cancer

Gastric cancer (GC) is one of the most malignant cancers, and cisplatin (Cis)-based chemotherapy remains the main clinical treatment for GC. However, Cis resistance often occurs, largely limiting its therapeutic efficacy in tumors. Therefore, a better understanding of the drug resistance mechanism could reveal new approaches for improving GC treatment efficacy. Here, we define the integrative role of nucleolar and coiled-body phosphoprotein 1 (NOLC1), a molecular chaperone that is significantly upregulated in GC tissues and Cis-resistant GC cells. Knocking down NOLC1 increased GC sensitivity to Cis by regulating ferroptosis. Mechanistically, NOLC1 binds to the p53 DNA binding domain (DBD), decreasing p53 nuclear accumulation stimulated by Cis and suppressing p53 transcriptional functions. Then, the p53-mediated ferroptosis is suppressed. Furthermore, the silence of NOLC1 promoted ferroptosis-induced immunogenic cell death (ICD) and reprogrammed the immunosuppressive tumor microenvironment, thereby increasing sensitivity to anti-programmed cell death-1 (PD-1) therapy plus Cis. The combination of anti-PD-1 plus Cis effectively inhibited GC growth without significant side effects. In summary, our findings reveal that targeting NOLC1 may be a novel therapeutic strategy for GC and may increase the efficacy of chemotherapy combined with immune checkpoint inhibitor (ICI) therapy.

cancer biology↗

bioRxiv2024

A comparative study of navigation behaviours in ants

Ants inhabit a vast range of ecosystems and exhibit wide morphology. They are expert navigators employing a handful of well-understood navigational strategies. However, the specific relationships among ant navigation behaviours, ecology, and morphology remain unclear, highlighting the need for comparative studies across diverse species. Here, we conducted field displacement experiments with 15 ant species across different habitats, assessing the prevalence of path integration, view-based navigation, olfactory trail following, and backtracking. We further tested whether use of particular navigation strategies was correlated with variation in morphological traits that could affect navigation efficiency, namely body size, eye size (view-based, path integration) and scape length (olfactory). There was a negative correlation between path integration and olfaction across different ant species, and no other clear trade-offs were identified between navigational strategies. Olfactory navigation emerged as the most dominant strategy. Path integration was also prevalent but limited to arboreal ants. View-based navigation was observed in both ground-foraging and tree-climbing ant species, and, unexpectedly, backtracking was also widespread. Species with larger eyes and body size showed a stronger preference for view-based navigation. However, no significant relationship was found between eye size or antennal scape length with preference for either path integration or olfaction. These results highlight the diversity and specialization of navigational strategies in ants, which appear to depend on the species ecological niche and morphological traits. Our study confirmed that path integration performs better in open sky environments, while view-based navigation appears more effective in cluttered habitats. We also showed the importance of plasticity in both foraging strategies and navigational profile at individual and colony levels, demonstrating the adaptability of ants navigation strategies to their environment.

ecology↗

bioRxiv2024

Testing the Tests: Using Connectome-Based Predictive Models to Reveal the Systems Standardized Tests and Clinical Symptoms Are Reflecting

BackgroundSubstantial strides have been made in developing connectome-based predictive models that establish connections between external measures of cognition and/or symptoms obtained through testing performed in a clinical setting, and the human functional connectome. Often referred to as brain-behavior modeling such models offer insights into the functional brain organization supporting the test scores of these external measures1-7. Here, we depart from the conventional feed-forward approach and introduce a feed-back approach that provides new insight into the systems the external measures are reflecting and provides a framework for developing new test instruments that better target specific brain systems. MethodsIn fMRI data from 227 demographically and clinically diverse subjects (healthy participants and patients), we a priori define connectivity networks for the six cognitive constructs and employ kernel ridge regression in a predictive modeling framework to quantify each networks contribution to performance across a spectrum of standardized tests. ResultsThis approach provides a ranking of test scores according to the predictive power of each cognitive network, allowing one to choose the best test to probe a specific brain network. It yields a brain-driven process for forming new tests through selection of combinations of measures that probe the same brain systems. These new composite tests yield better external measures, as reflected by higher predictive power in brain-behavior modeling. We also evaluate the inclusion of specific subtests within a composite score, revealing instances where composite scores are reinforced or weakened by subtest inclusion regarding the specificity of the brain network they interrogate. ConclusionsThe brain-behavior modeling problem can be reconfigured to provide a biologically driven approach to the selection of external measures directed at specific brain systems. It opens new avenues of research by providing a framework for the development of measures, both cognitive and clinical, guided by quantitative brain metrics.

neuroscience↗

bioRxiv2024

CXXC-finger protein 1 associates with FOXP3 to stabilize homeostasis and suppressive functions of regulatory T cells

FOXP3-expressing regulatory T (Treg) cells play a pivotal role in maintaining immune homeostasis and tolerance, with their activation being crucial for preventing various inflammatory responses. However, the mechanisms governing the epigenetic program in Treg cells during their dynamic activation remain unclear. In this study, we demonstrate that CXXC finger protein 1 (CXXC1) interacts with the transcription factor FOXP3 and facilitates the regulation of target genes by modulating H3K4me3 deposition. Cxxc1 deletion in Treg cells leads to severe inflammatory disease and spontaneous T-cell activation, with impaired immunosuppressive function. As a transcriptional regulator, CXXC1 promotes the expression of key Treg functional markers under steady-state conditions, which are essential for the maintenance of Treg cell homeostasis and their suppressive functions. Epigenetically, CXXC1 binds to the genomic regulatory regions of Treg program genes in mouse Treg cells, overlapping with FOXP3 binding sites. Given its critical role in Treg cell homeostasis, CXXC1 presents itself as a promising therapeutic target for autoimmune diseases.

immunology↗

bioRxiv2024

Differential representations for affective and informative components of reward in the striatum and hippocampus

Receipt of a reward is composed of affective and informative components, which are often intertwined in most reward-processing and decision-making tasks. Our previous work allowed us to identify regions that were more strongly engaged for the affective and informative components of reward upon receipt (Smith et al., 2016) and showed that the ventral striatum responds to both affective and informative components of reward processing. However, the limited spatial resolution and coarse analytical approaches made it hard to understand how these different components of reward were represented in the brain, wherein similar engagement may not necessitate similar representations. In our current study, we used high-resolution functional magnetic resonance imaging (voxel size: 1.75 mm3) and representational similarity analysis to investigate the representation of affective and informative components of reward receipt in the striatum and the hippocampus, another region that is sensitive to reward information. We found a differential representation of affective and informative components of reward receipt in the striatum and the hippocampus, with no difference in representation between the two structures. However, in the dorsal striatum, we found that representations were stronger for affective rather than the informative components of reward receipt. Finally, we observed that the ventral striatum was sensitive to the predictiveness of information, such that across-run pattern similarity in the ventral striatum increased with the predictiveness of information. In sum, our results provide evidence of how affective and informative components of rewards are represented in the striatum and the hippocampus, potentially indicating a differential coding schema for the dorsal and the ventral striatum.

neuroscience↗

bioRxiv2024

Novel insights into Emx2 and Dmrta2 cooperation during cortex development and evidence for Dmrta2 function in choroid plexus

Early dorsal telencephalon development is coordinated by an interplay of transcription factors that exhibit a graded expression pattern in neural progenitors. How they function together to orchestrate cortical development remains largely unknown. The Emx2 and Dmrta2 genes encode TFs that are expressed in a similar caudomedialhigh/ rostrolaterallowgradient in the ventricular zone of the developing dorsal telencephalon with, in the medial pallium, Dmrta2 but not Emx2 expressed in the developing choroid plexus. Their constitutive loss has been shown to impart similar cortical abnormalities, and their combined deletion exacerbates the phenotypes, suggesting possible cooperation during cortex development. In this study, we utilized molecular and genetic approaches to dissect how Emx2 functions with Dmrta2 during cortical development. Our results show that while they regulate a similar set of genes, their common direct targets are limited but include key regulators of cortical development. Identification of the interaction partners of Emx2 suggests that it coordinates with the LIM-domain binding protein Ldb1 to execute the activation and repression of some of its downstream targets. Finally, while Emx2 is known to suppress choroid plexus development, we also provide evidence that Dmrta2 is in contrast required for choroid plexus since in its absence in medial telencephalic progenitors, mice develop hydrocephalous postnatally, a phenotype that appears to be due to a compromised cytoarchitecture. Together, these data indicate that Emx2 and Dmrta2 have similar but also distinct functions in telencephalon development and provide the first insights into Emx2 mechanism of action. SIGNIFICANCE STATEMENTEmx2 and Dmrta2 encode transcription factors that generate similar phenotypes upon their loss in the developing cortex suggesting possible cooperation. Here we explored how Emx2 functions with Dmrta2 during cortical development. Results obtained indicate that Emx2 directly regulates with Dmrta2 only a few genes, some coding for key cortical determinants and that Emx2 utilizes the Ldb1 cofactor for the regulation of some of its targets. Results also suggest that, unlike Emx2 which suppresses choroid plexus development, Dmrta2 is required for choroid plexus as its loss in medial telencephalic progenitors leads to hydrocephalus. Together, our results reveal that Emx2 and Dmrta2 have similar but also distinct functions during telencephalon development and provide novel insights into the mechanism of action of Emx2.

neuroscience↗

bioRxiv2024

Evidence that Dmrta2 acts as a transcriptional repressor of Pax6 in murine cortical progenitors and identification of a mutation crucial for DNA recognition associated with microcephaly in human

Dmrta2 (also designated Dmrt5) is a transcriptional regulator expressed in cortical progenitors in a caudomedialhigh/rostrolaterallow gradient with important roles at different steps of cortical development. Dmrta2 has been suggested to act in cortex development mainly by differential suppression of Pax6 and other homeobox transcription factors such as the ventral telencephalic regulator Gsx2, which remains to be fully demonstrated. Here we have addressed the epistatic relation between Pax6 and Dmrta2 by comparing phenotypes in mutant embryos or embryos overexpressing both genes in various allelic combinations. We showed that Dmrta2 cooperates with Pax6 in the maintenance of cortical identity in dorsal telencephalic progenitors and that it acts as a transcriptional repressor of Pax6 to control cortical patterning. Mechanistically, we show that in P19 cells, Dmrta2 can act as a DNA-binding dependent repressor on the Pax6 E60 enhancer and that a point mutation that affects its DNA binding properties leads to agenesis of the corpus callosum, pachygyria, and the absence of the cingulate gyrus. Finally, we provide evidence that Dmrta2 binds to the Zfp423 zinc finger protein and that it enhances its ability to recruit the NurD repressor complex. Together, our results highlight the importance and conserved function of Dmrta2 in cortical development and provide novel insights into its mechanism of action. SIGNIFICANCE STATEMENTCorticogenesis is controlled by an array of transcription factors that coordinate neural progenitor self-renewal and differentiation to generate correct cortical cell number and diversity. However, how this complex array of transcription factors works in concert to regulate this delicate process remains largely unknown. Here we provide important insights into the mechanism of action of Dmrta2 by demonstrating that it cooperates with the transcription factor Pax6 to define the pallium-subpallium boundary and that it acts by repressing it, likely via the recruitment of Zfp423 and the NurD repressor complex, to control cortical patterning. Our data also reveal that a point mutation that affects its DNA binding causes cortical abnormalities in human, further highlighting its importance in cortex development.

neuroscience↗

bioRxiv2024

A T6SS DNase effector induces nuclear DNA Damage to trigger apoptosis via activation of the cGAS-STING-TNF axis

In the relentless battle for survival, bacteria have evolved sophisticated weaponry like the Type VI secretion system (T6SS) to not only outcompete rivals but also manipulate host cell processes to their advantage. Apoptosis, a controlled form of programmed cell death without triggering inflammatory responses, is often exploited by pathogens. While many bacterial pathogens are known to induce apoptosis, the role of T6SS effectors in this process remains unexplored. In this study, we discovered that Yersinia pseudotuberculosis (Yptb) utilizes its T6SS to secrete a DNase effector, TkeA, which induces apoptosis in host cells. Mechanistically, the translocation of TkeA into host cells causes nuclear DNA damage, leading to the release of fragmented DNA into the cytoplasm. This, in turn, activates the DNA-sensing cyclic GMP-AMP synthase (cGAS)/stimulator of interferon genes (STING) pathway. The activation of the cGAS-STING pathway by TkeA subsequently triggers apoptosis in host cells via extrinsic pathways, with tumor necrosis factor (TNF) signaling playing a critical role. Additionally, TkeA also mediates interbacterial competition, promoting the colonization of Yptb in mices gut. Our findings reveal that the T6SS-secreted DNase effector TkeA acts as a trans-kingdom effector, enhancing interbacterial competition and inducing apoptosis in host cells by activating the cGAS-STING-TNF axis. This discovery adds a new dimension to the mechanisms employed by bacterial pathogens to manipulate host cell death pathways by using their secretion systems. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/613802v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1bfd70org.highwire.dtl.DTLVardef@19bfc89org.highwire.dtl.DTLVardef@1e0bf9dorg.highwire.dtl.DTLVardef@4412b9_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTS* Yptb T6SS secretes a trans-kingdom DNase effector TkeA * TkeA degrades bacterial DNA to mediate interbacterial competition * TkeA causes nuclear DNA damage in host cells to induce apoptosis * TkeA induces apoptosis via the cGAS-STING-TNF axis

microbiology↗

bioRxiv2024

Co-transcriptional RNA processing boosts zygotic gene activation

Transcription decodes protein-coding genes and interprets regulatory information embedded in the genome by generating RNA. In eukaryotes, gene transcription is coupled with RNA processing via the carboxyl terminal domain (CTD) of RNA polymerase (Pol) II, which enhances messenger RNA (mRNA) production. We propose that co-transcriptional RNA processing is essential for zygotic gene activation (ZGA), transitioning the transcription program from noncoding to protein-coding after fertilization. Truncating the CTD in mouse cells disrupts this coupling, halting global mRNA synthesis and increasing noncoding RNA (ncRNA) levels through enhanced intergenic transcription and RNA stabilization. CTD truncation also triggers epigenetic reprogramming and nuclear reorganization towards totipotency, resembling early cleavage embryos. Mechanistically, the CTD restrains nonproductive polymerase activity in noncoding sequences, while at protein-coding genes requiring RNA processing, it promotes elongation by facilitating polymerase promoter-proximal pausing, transcription directionality, and velocity. Longer CTD lengths enhance gene activity, likely evolving to accommodate the increasing noncoding sequences in mammalian genomes.

developmental biology↗