Biology subjects

Ma, B.

Publications and source records attributed to Ma, B..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Chitinase 3-like-1 (CHI3L1) Inhibits Innate Anti-Tumor and Tissue Remodeling ImmuneResponses by Regulating CD47-SIRPα and CD24-Siglec10-Mediated Phagocytosis

Innate immune responses such as phagocytosis are critically linked to the generation of adaptive immune responses against the neoantigens in cancer and the efferocytosis that is essential for homeostasis in diseases characterized by lung injury, inflammation, and remodeling as in Chronic Obstructive Pulmonary Disease (COPD). Chitinase 3-like-1 (CHI3L1) is induced in many cancers where it inhibits adaptive immune responses by stimulating immune checkpoint molecules (ICPs) and portends a poor prognosis. CHI3L1 is also induced in COPD where it regulates epithelial cell death. Here we demonstrate that pulmonary melanoma metastasis inhibits macrophage phagocytosis by stimulating the CD47-SIRP and CD24-Siglec10 phagocytosis checkpoint pathways while inhibiting macrophage "eat me" signals from calreticulin and HMGB1. We also demonstrate that these effects on macrophage phagocytosis are mediated by CHI3L1 stimulation of the SHP-1 and SHP-2 phosphatases and the inhibition of the accumulation and phosphorylation of cytoskeleton-regulating non-muscle myosin IIa. This inhibition of innate immune responses like phagocytosis provides a mechanistic explanation for the ability of CHI3L1 to stimulate ICPs and inhibit adaptive immune responses in cancer and diseases like COPD. The ability of CHI3L1 to simultaneously inhibit innate immune responses, stimulate ICPs, inhibit T cell co-stimulation, and regulate a number of other oncogenic and inflammation pathways suggest that CHI3L1-targeted therapeutics are promising interventions in cancer, COPD and other disorders.

immunology↗

bioRxiv2023

ST-GEARS: Advancing 3D Downstream Research through Accurate Spatial Information Recovery

Three-dimensional Spatial Transcriptomics has revolutionized our understanding of tissue regionalization, organogenesis, and development. However, to reconstruct single sections back to their in situ three-dimensional morphology, existing approaches either only adopt gene expression information to guide reconstruction or overlook shape correction against experiment-induced section distortions. This leads to significant discrepancies between reconstruction results and the actual in vivo locations of cells, imposing unreliable spatial profiles to downstream analysis. To address these challenges, we propose ST-GEARS (Spatial Transcriptomics GEospatial profile recovery system through AnchoRS), which solves optimized anchors between in situ closest spots utilizing expression and structural similarity across sections and recovers in vivo spatial information under the guidance of anchors. By employing innovative Distributive Constraints into the Optimization scheme, it retrieves anchors with higher precision compared to existing methods. Taking these anchors as reference points, ST-GEARS first rigidly aligns sections, then introduces and infers Elastic Fields to counteract distortions. ST-GEARS denoises the fields using context information by Gaussian Denoising. Utilizing the denoised fields, it eliminates distortions and eventually recovers original spatial profile through innovative and mathematically proved Bi-sectional Fields Application. Studying ST-GEARS on both bi-sectional registration and complete tissue reconstruction across sectional distances and sequencing platforms, we observed its outstanding performance in spatial information recovery across tissue, cell, and gene levels compared to current approaches. Through this recovery, ST-GEARS provides precise and well-explainable gears between in vivo situations and 3D in vitro analysis, powerfully fueling the potential of biological discoveries.

bioinformatics↗

bioRxiv2023

The receptor VLDLR binds East Equine Encephalitis virus through multiple distinct modes

Eastern Equine Encephalitis virus (EEEV) is an alphavirus that can cause severe diseases in infected humans. The very low-density lipoprotein receptor (VLDLR) was recently identified as a receptor of EEEV. Herein, we performed cryo-electron microscopy structural and biochemistry studies on the specific interactions between EEEV and VLDLR. Our results show that VLDLR binds EEEV at three different sites A, B and C through its membrane-distal 8 LDLR class A (LA) repeats (LA1-8). Site A is located in the cleft in between the E1-E2 heterodimers of the surface trimeric spikes. Site B is located near the connecting {beta} ribbon in between the B and A-C domains of E2 and is in proximity to site A, while site C is on the domain B of E2. LA1 and LA5 specifically recognize site A, whereas LA2, LA3 and LA6 can bind both sites A and C. The binding of VLDLR LAs to EEEV is in complex modes. The LA1-2 mediated binding plays a critical role in mediating virus entry. The mutation W132G of VLDLR impairs the binding of LA3, drives the switch of the binding modes, and significantly enhances the attachment of EEEV to the cell. The W132G variant of VLDLR could be identified in human genome and SNP sequences, implying that people with similar mutations in VLDLR may be highly susceptible to EEEV infection.

microbiology↗

bioRxiv2023

Phylogeny-metabolism dual-directed single-cell genomics for dissecting and mining ecosystem function

Although microbiome-wide association studies (MWAS) have uncovered many marker organisms for an ecosystem trait, mechanisms of most microbiota-mediated processes remain elusive, due to challenges in validating the markers in situ metabolic activities and tracing such activities to individual genomes. Here we introduced a phylogeny-metabolism dual-directed single-cell genomics approach called Fluorescence-In-Situ-Hybridization-guided Single-Cell Raman-activated Sorting and Sequencing (FISH-scRACS-Seq). It directly localizes individual cells from target taxon via a FISH probe for marker organism, profiles their in situ metabolic functions via single-cell Raman spectra, sorts cells of target taxonomy and target metabolism, and produces indexed, high-coverage and precisely-one-cell genomes. From cyclohexane-contaminated seawater, cells representing the MWAS-derived marker taxon of {gamma}-Proteobacteria and that are actively degrading cyclohexane in situ were directly identified via FISH and Raman respectively, then sorted and sequenced for one-cell full genomes. In such a Pseudoalteromonas fuliginea cell, we discovered a three-component cytochrome P450 system that can convert cyclohexane to cyclohexanol in vitro, representing a previously unknown group of cyclohexane-degrading enzymes and organisms. By culture-independently unveiling enzymes, pathways, genomes and their in situ functions specifically for those single-cells with ecological relevance, FISH-scRACS-Seq is a rational and generally applicable approach for dissecting and mining microbiota functions. TeaserFISH-scRACS-Seq is a new strategy to dissect microbiota functional mechanism at single-cell resolution.

microbiology↗

bioRxiv2023

SAGERank: Inductive Learning of Protein-Protein Interaction from Antibody-Antigen Recognition using Graph Sample and Aggregate Networks Framework

Numerous experiments and computationally solved antibody-antigen interfaces offer the possibility of training deep-learning models to help predict their biological correlations. Predicting antibody-antigen docking and structure-based design represent significant long-term and therapeutically important challenges in computational biology. We present SAGERank, a general, configurable deep learning framework for antibody design using Graph Sample and Aggregate Networks, which mainly includes ranking docking decoys, detecting binding, and identifying biological interfaces. The model proved its reliability in three different tasks. For both problems ranking docking decoys and identifying biological interfaces, SAGERank is competitive with or outperforms, state-of-the-art methods. Besides, the SAGERank model still showed a high degree of confidence in determining whether the antibody-antigen could bind. All of these demonstrate the versatility of SAGERank for structural biology research. Most importantly, our study demonstrated the real potential of inductive deep learning to overcome small dataset problem in molecular science. The SAGERank models trained for antibody-antigen docking can be used to examine generally protein-protein interaction docking and differentiate crystal packing from biological interface.

bioinformatics↗

bioRxiv2023

ABTrans: A Transformer-based model for predicting interaction between anti-Abeta antibodies and peptides

Understanding the recognition of antibodies and A{beta} peptide is crucial for the development of more effective therapeutic agents. Here we studied the interaction between anti-A{beta} antibodies and different peptides by building a deep learning model, using the dodecapeptide sequences elucidated from phage display and known anti-A{beta} antibody sequences collected from public sources. Our multi-classification model, ABTrans was trained to determine the four levels of binding ability between anti-A{beta} antibody and dodecapeptide: not binding, weak binding, medium binding, and strong binding. The accuracy of our model reached 0.8278. Using the ABTrans, we examined the cross-reaction of anti-A{beta} antibodies with other human amyloidogenic proteins, and we found that Aducanumab and Donanemab have the least cross-reactions with other human amyloidogenic proteins. We also systematically screened all human proteins interaction with eleven selected anti-A{beta} antibodies to identify possible peptide fragments that could be an off-target candidate. Key PointsO_LIABTrans is a Transformer-based model that was developed for the first time to predict the interaction between anti-A{beta} antibodies and peptides. C_LIO_LIABTrans was trained using a dataset with 1.5 million peptides and 110 anti-A{beta} antibodies. C_LIO_LIABTrans achieved an accuracy of 0.8278 and is capable of determining the four levels of binding ability between antibody and A{beta}: not binding, weak binding, medium binding, and strong binding. C_LIO_LIABTrans has potential applications in predicting off-target and cross-reactivity effects of antibodies and in designing new anti-A{beta} antibodies. C_LI

bioinformatics↗

bioRxiv2023

Gut microbial genomes with paired isolates from China signify probiotic and cardiometabolic effects

The gut microbiome displays significant genetic differences between populations while systematic characterization of the genomic landscape of the gut microbiome in Asia populations remains limited. Here, we present the Chinese gut microbial reference (CGMR) set, comprising 101,060 high quality metagenomic assembled genomes (MAGs) of 3,707 non-redundant species paired with 1,376 live isolates from a national wide collection of 3,234 fecal samples across China. This improved reference set contains 987 novel species compared with existing resources worldwide. By associating MAGs with geographic and phenotypic characteristics, we observed regional-specific coexisting MAGs and MAGs with probiotic and cardiometabolic functionalities. We further conducted mice experiments to confirm the probiotic effects of two Faecalibacterium intestinalis isolates in alleviating constipation, the cardiometabolic influences of three Bacteroides fragilis_A isolates in obesity, and the functional potential of isolates from the two new species belonging to the genera Parabacteroides and Lactobacillus in host lipids metabolism. Our study not only expands the current microbial genomes with paired isolates but also demonstrates their probiotic and cardiometabolic effects on hosts, contributing to the mechanistic understanding of host-microbe interactions and the translation of microbiome-based personalized therapies.

microbiology↗

bioRxiv2023

Chitinase 3-like-1 (CHI3L1) in the Pathogenesis of Epidermal Growth Factor Receptor Mutant Non-Small Cell Lung Cancer

Non-small cell lung cancer (NSCLC) accounts for 85% of all lung cancers. In NSCLC, 10-20% of Caucasian patients and 30-50% of Asian patients have tumors with activating mutations in the Epidermal Growth Factor Receptor (EGFR). A high percentage of these patients exhibit favorable responses to treatment with tyrosine kinase inhibitors (TKI). Unfortunately, a majority of these patients develop therapeutic resistance with progression free survival lasting 9-18 months. The mechanisms that underlie the tumorigenic effects of EGFR and the ability of NSCLC to develop resistance to TKI therapies, however, are poorly understood. Here we demonstrate that CHI3L1 is produced by EGFR activation of normal epithelial cells, transformed epithelial cells with wild type EGFR and cells with cancer-associated, activating EGFR mutations. We also demonstrate that CHI3L1 auto-induces itself and feeds back to stimulate EGFR and its ligands. Highly specific antibodies against CHI3L1 (anti-CHI3L1/FRG) and TKI, individually and in combination, abrogated the effects of EGFR activation on CHI3L1 and the ability of CHI3L1 to stimulate the EGFR axis. Anti-CHI3L1 also interacted with osimertinib to reverse TKI therapeutic resistance and induce tumor cell death and inhibit pulmonary metastasis while stimulating tumor suppressor genes including KEAP1. CHI3L1 is a downstream target of EGFR that feeds back to stimulate and activate the EGFR axis. Anti-CHI3L1 is an exciting potential therapeutic for EGFR mutant NSCLC, alone and in combination with osimertinib or other TKIs.

cancer biology↗

bioRxiv2023

VirEvol platform:accurate prediction and visualization of SARS-CoV-2 evolutionary trajectory based on protein language model, structural information and immunological recognition mechanism

Predicting the mutation direction of SARS-CoV-2 using exploratory computational methods presents a challenging, yet prospective, research avenue. However, existing research methods often ignore the effects of protein structure and multi-source viral information on mutation prediction, making it difficult to accurately predict the evolutionary trend of the SARS-CoV-2 S protein receptor-binding domain (RBD). To overcome this limitation, we proposed an interpretable language model combining structural, sequence and immune information. The dual utility of this model lies in its ability to predict SARS-CoV-2s affinity for the ACE2 receptor, and to assess its potential for immune evasion. Additionally, it explores the mutation trend of SARS-CoV-2 via a genetic algorithm-directed evolution. The model exhibits high accuracy in both regards and has displayed promising early warning capabilities, effectively identifying 13 out of 14 high-risk strains, marking a success rate of 93%.". This study provides a novel method for discerning the molecular evolutionary pattern, as well as predicting the evolutionary trend of SARS-CoV-2 which is of great significance for vaccine design and drug development of new coronaviruses. We further developed VirEvol, a unique platform designed to visualize the evolutionary trajectories of novel SARS-CoV-2 strains, thereby facilitating real-time predictive analysis for researchers. The methodologies adopted in this work may inspire new strategies and offer technical support for addressing challenges posed by other highly mutable viruses.

bioinformatics↗

bioRxiv2023

Proteasomal cleavage prediction: state-of-the-art and future directions

Epitope vaccines are a promising approach for precision treatment of pathogens, cancer, autoimmune diseases, and allergies. Effectively designing such vaccines requires accurate proteasomal cleavage prediction to ensure that the epitopes included in the vaccine trigger an immune response. The performance of proteasomal cleavage predictors has been steadily improving over the past decades owing to increasing data availability and methodological advances. In this review, we summarize the current proteasomal cleavage prediction landscape and, in light of recent progress in the field of deep learning, develop and compare a wide range of recent architectures and techniques, including long short-term memory (LSTM), transformers, and convolutional neural networks (CNN), as well as four different denoising techniques. All open-source cleavage predictors re-trained on our dataset performed within two AUC percentage points. Our comprehensive deep learning architecture benchmark improved performance by 1.7 AUC percentage points, while closed-source predictors performed considerably worse. We found that a wide range of architectures and training regimes all result in very similar performance, suggesting that the specific modeling approach employed has a limited impact on predictive performance compared to the specifics of the dataset employed. We speculate that the noise and implicit nature of data acquisition techniques used for training proteasomal cleavage prediction models and the complexity of biological processes of the antigen processing pathway are the major limiting factors. While biological complexity can be tackled by more data and, to a lesser extent, better models, noise and randomness inherently limit the maximum achievable predictive performance. All our datasets and experiments are available at https://github.com/ziegler-ingo/cleavage_benchmark.

bioinformatics↗

bioRxiv2023

Flexible coding schemes in dorsomedial prefrontal cortex underlie decision-making during delay discounting

Determining how an agent decides between a small, immediate versus a larger, delayed reward has provided insight into the psychological and neural basis of decision-making. The tendency to excessively discount the value of delayed rewards is thought to reflect deficits in brain regions critical for impulse control such as the prefrontal cortex (PFC). This study tested the hypothesis that dorsomedial PFC (dmPFC) is critically involved in flexibly managing neural representations of strategies that limit impulsive choices. Optogenetic silencing of neurons in the rat dmPFC increased impulsive choices at an 8 sec, but not 4 sec, delay. Neural recordings from dmPFC ensembles revealed that, at the 8-sec delay, the encoding landscape transitions to reflect a deliberative-like process rather than the schema-like processes observed at the 4-sec delay. These findings show that changes in the encoding landscape reflect changes in task demands and that dmPFC is uniquely involved in decisions requiring deliberation.

neuroscience↗

bioRxiv2023

Targeted Protein O-GlcNAcylation Using Bifunctional Small Molecules

Protein O-linked {beta}-N-acetylglucosamine modification (O-GlcNAcylation) plays a crucial role in regulating essential cellular processes. The disruption of O-GlcNAcylation homeostasis has been linked to various human diseases, including cancer, diabetes, and neurodegeneration. However, there are limited chemical tools for protein- and site-specific O-GlcNAc modification, rendering the precise study of O-GlcNAcylation challenging. To address this, we have developed first-in-class heterobifunctional small molecules, named O-GlcNAcylation targeting chimeras (OGTACs), which enable protein-specific O-GlcNAcylation in cells. OGTACs promote O-GlcNAcylation of proteins such as BRD4, CK2, and EZH2 in cellulo by recruiting O-GlcNAc transferase (OGT), with temporal and magnitude control. Mass spectrometry data revealed that OGTACs induced site-selective O-GlcNAcylation of BRD4. Overall, OGTACs represent a promising approach for inducing protein-specific O-GlcNAcylation, thus enabling functional dissection and offering new directions for O-GlcNAc-targeting therapeutic development.

cell biology↗

bioRxiv2023

Proactive Versus Reactive Control Strategies Differentially Mediate Alcohol Drinking in Wistar and P rats

Problematic alcohol consumption is associated with deficits in decision-making, and alterations in prefrontal cortex neural activity likely contributes. We hypothesized that differences in cognitive control would be evident between male Wistar rats and a model for genetic risk for alcohol use disorder (alcohol-preferring P rats). Cognitive control can be split into proactive and reactive components. Proactive control maintains goal-directed behavior independent of a stimulus whereas reactive control elicits goal-directed behavior at the time of a stimulus. We hypothesized that Wistars would show proactive control over alcohol-seeking whereas P rats would show reactive control over alcohol-seeking. Neural ensembles were recorded from prefrontal cortex during an alcohol seeking task that utilized two session types. On congruent sessions the CS+ was on the same side as alcohol access. Incongruent sessions presented alcohol opposite the CS+. Wistars, but not P rats, exhibited an increase in incorrect approaches during incongruent sessions, suggesting that Wistars utilized the previously learned task-rule. This motivated the hypothesis that ensemble activity reflecting proactive control would be observable in Wistars but not P rats. While P rats showed differences in neural activity at times relevant for alcohol delivery, Wistars showed differences prior to approaching the sipper. These results support our hypothesis that Wistars are more likely to engage proactive cognitive-control strategies whereas P rats are more likely to engage reactive cognitive control strategies. Although P rats were bred to prefer alcohol, differences in cognitive control may reflect a sequela of behaviors that mirror those in humans at risk for an AUD. Significance StatementCognitive control refers to the set of executive functions necessary for goal-directed behavior. It is a major mediator of addictive behaviors and can be subdivided into proactive and reactive cognitive control. We observed behavioral and electrophysiological differences between outbred Wistar rats and the selectively bred Indiana alcohol-preferring P rat while they sought and consumed alcohol. These differences are best explained by reactive cognitive control in P rats and proactive in Wistar rats.

neuroscience↗

bioRxiv2023

C-type natriuretic peptide improves maternally aged oocytes quality by inhibiting excessive PINK1/Parkin-mediated mitophagy

The overall oocyte quality declines with ageing, and this effect is strongly associated with a higher reactive oxygen species (ROS) level and the resultant oxidative damage. C-type natriuretic peptide (CNP) is a well-characterized physiological meiotic inhibitor that has been successfully used to improve immature oocyte quality during in vitro maturation (IVM). However, the underlying roles of CNP in maternally aged oocytes have not been reported. Here, we found that the age-related reduction in the serum CNP concentration was highly correlated with decreased oocyte quality. Treatment with exogenous CNP promoted follicle growth and ovulation in aged mice and enhanced meiotic competency and fertilization ability. Interestingly, the cytoplasmic maturation of aged oocytes was thoroughly improved by CNP treatment, as assessed by spindle/chromosome morphology and redistribution of organelles (mitochondria, the endoplasmic reticulum [ER], cortical granules [CGs], and the Golgi apparatus). CNP treatment also ameliorated DNA damage and apoptosis caused by ROS accumulation in aged oocytes. Importantly, oocyte RNA-seq revealed that the beneficial effect of CNP on aged oocytes was mediated by restoration of mitochondrial oxidative phosphorylation, eliminating excessive mitophagy. CNP reversed the defective phenotypes in aged oocytes by alleviating oxidative damage and suppressing excessive PINK1/Parkin-mediated mitophagy. Mechanistically, CNP functioned as a cAMP/PKA pathway modulator to decrease PINK1 stability and inhibit Parkin recruitment. In summary, our results demonstrated that CNP supplementation constitutes an alternative therapeutic approach for advanced maternal age-related oocyte deterioration and may improve the overall success rates of clinically assisted reproduction in older women.

developmental biology↗

bioRxiv2023

Lepidoptera proboscis pollens are mainly derived from nectar

The pollens which are rejected or ignored by the dry stigma cant germinate since they havent acquired sugar solution from dry stigmas. But almost all research has ignored the participation of insects which may transport pollens from the nectar to stigmas, and that pollens may germinate on the dry stigma since they have soaked in the nectar. So, the key question is that whether insects carry pollens from nectar to the stigma. Since the adult Lepidoptera are important to the plant pollination and there is a general consensus that pollens are mainly deposited on the proboscis of adult Lepidoptera, and pollens are ubiquitous in the nectar of field flowers, we simulated the flower environment to conduct several groups of behavioral experiments in the adult Mythimna separata by controlling the presence, absence or movement of pollens in nectar, then counted and compared the proboscis pollens. We found that the pollens on the proboscis were mainly derived from the nectar. Our conclusion may contributes to the research of pollen germination on stigmas, especially the dry stigma, and also shows the importance of adult Lepidoptera to pollination, even supports the coevolution of Lepidoptera and angiosperm.

zoology↗

bioRxiv2023

High-resolution functional description of vaginal microbiomes in health and disease

BackgroundA Lactobacillus-dominated vaginal microbiome provides the first line of defense against numerous adverse genital tract health outcomes. However, there is limited understanding of the mechanisms by which the vaginal microbiome modulates protection, as prior work mostly described its composition through morphologic assessment and marker gene sequencing methods that do not capture functional information. To address this limitation, we developed metagenomic community state types (mgCSTs) which uses metagenomic sequences to describe and define vaginal microbiomes based on both composition and function. ResultsMgCSTs are categories of microbiomes classified using taxonomy and the functional potential encoded in their metagenomes. MgCSTs reflect unique combinations of metagenomic subspecies (mgSs), which are assemblages of bacterial strains of the same species, within a microbiome. We demonstrate that mgCSTs are associated with demographics such as age and race, as well as vaginal pH and Gram stain assessment of vaginal smears. Importantly, these associations varied between mgCSTs predominated by the same bacterial species. A subset of mgCSTs, including three of the six predominated by Gardnerella mgSs, as well as a mgSs of L. iners, were associated with a greater likelihood of Amsel bacterial vaginosis diagnosis. This L. iners mgSs, among other functional features, encoded enhanced genetic capabilities for epithelial cell attachment that could facilitate cytotoxin-mediated cell lysis. Finally, we report a mgSs and mgCST classifier as an easily applied, standardized method for use by the microbiome research community. ConclusionsMgCSTs are a novel and easily implemented approach to reducing the dimension of complex metagenomic datasets, while maintaining their functional uniqueness. MgCSTs enable investigation of multiple strains of the same species and the functional diversity in that species. Future investigations of functional diversity may be key to unraveling the pathways by which the vaginal microbiome modulates protection to the genital tract. Importantly, our findings support the hypothesis that functional differences between vaginal microbiomes, including those that may look compositionally similar, are critical considerations in vaginal health. Ultimately, mgCSTs may lead to novel hypotheses concerning the role of the vaginal microbiome in promoting health and disease, and identify targets for novel prognostic, diagnostic, and therapeutic strategies to improve womens genital health.

genomics↗

bioRxiv2022

Equalizing epigenetically imprinted centromeres in early mammalian embryos

The CENP-A histone variant epigenetically defines centromeres, where its levels and locations are precisely maintained through mitotic cell divisions. However, differences in centromere CENP-A propagation in soma versus female/male germline remains poorly understood. Here, we generated CenpamScarlet mice and followed CENP-A dynamics in gametes, zygotes, and embryos. We found that, unlike somatic cells, progenitor female and male germ cells carry high centromeric CENP-A levels that decrease upon terminal differentiation. The reduction in CENP-A is differentially regulated between sexes, resulting in a ten-fold higher level in oocytes compared to sperm. In the zygote, the parent-of-origin CENP-A asymmetry is equalized prior to initial S-phase by redistribution of nuclear CENP-A from maternal to paternal chromosomes. Redistribution of CENP-A requires both CDK1/2 and PLK1 centromeric machinery. These experiments provide direct evidence for resetting of epigenetically imprinted centromeres in early pronuclear stage embryos and imply a mechanism to sense the non-equivalency of parental chromosomes. HighlightsO_LIIncreased CENP-A density at centromeres is a conserved property of germline stem cells while CENP-A reduction is coincident with germ cell differentiation C_LIO_LIPaternal and maternal CENP-A containing nucleosomes are intergenerationally inherited C_LIO_LICENP-A density at centromeres differs between male and female mature gametes C_LIO_LIUpon fertilization, maternal nuclear CENP-A is redistributed to equalize with parental CENP-A C_LIO_LICENP-C and MIS18BP1 are asymmetrically enriched in the parental pronuclei in accordance with CENP-A asymmetry. C_LIO_LILicensing for centromere equalization begins before zygotic DNA replication C_LI

developmental biology↗

bioRxiv2022

Early immunomodulatory program triggered by pro-tolerogenic Bifidobacterium pseudolongum drives cardiac transplant outcomes

BackgroundDespite ongoing improvements in regimens to prevent allograft rejection, most cardiac and other organ grafts eventually succumb to chronic vasculopathy, interstitial fibrosis, or endothelial changes, and eventually graft failure. The events leading to chronic rejection are still poorly understood and the gut microbiota is a known driving force in immune dysfunction. We previously showed that gut microbiota dysbiosis profoundly influences the outcome of vascularized cardiac allografts and subsequently identified biomarker species associated with these differential graft outcomes. MethodsIn this study, we further detailed the multifaceted immunomodulatory properties of pro-tolerogenic and pro-inflammatory bacterial species over time, using our clinically relevant model of allogenic heart transplantation. ResultsIn addition to tracing longitudinal changes in the recipient gut microbiome over time, we observed that Bifidobacterium pseudolongum (Bifido) induced an early anti-inflammatory phenotype within 7 days, while Desulfovibrio desulfuricans (Desulfo) resulted in a pro-inflammatory phenotype, defined by alterations in leukocyte distribution and lymph node (LN) structure. Indeed, in vitro results showed that Bifido and Desulfo acted directly on primary innate immune cells. However, by 40 days after treatment, these two bacterial strains were associated with mixed effects in their impact on LN architecture and immune cell composition and loss of colonization within gut microbiota, despite protection of allografts from inflammation with Bifido treatment. ConclusionsThese dynamic effects suggest a critical role for early microbiota-triggered immunological events such as innate immune cell engagement, T cell differentiation, and LN architectural changes in the subsequent modulation of pro-tolerant versus pro-inflammatory immune responses in organ transplant recipients.

immunology↗