Biology subjects

Fu, J.

Publications and source records attributed to Fu, J..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

The BOD1L subunit of the mammalian SETD1A complex sustains the expression of DNA damage repair genes despite restraining H3K4 trimethylation

SETD1A is the histone 3 lysine 4 (H3K4) methyltransferase central to the mammalian version of the highly conserved eight subunit Set1 complex (Set1C) that apparently conveys H3K4 trimethylation (H3K4me3) onto all active Pol II promoters. Accordingly, the Setd1a mouse knock-out dies in early embryogenesis at the epiblast stage and mouse embryonic stem cells (ESCs) die when SETD1A is removed. We report that ESC death is accompanied by loss of expression of DNA repair genes and accumulating DNA damage. BOD1L and BOD1 are homologs of the yeast Set1C subunit, Shg1, and subunits of the mammalian SETD1A and B complexes. We show that the Shg1 homology region binds to a highly conserved central alpha-helix in SETD1A and B. Like mutagenesis of Shg1 in yeast, conditional mutagenesis of Bod1l in ESCs promoted increased H3K4 di- and tri-methylation but also, like loss of SETD1A, loss of expression of DNA repair genes, increased DNA damage and cell death. In contrast to similar losses of DNA repair gene expression, the converse changes in H3K4 methylation after loss of SETD1A or BOD1L implies that H3K4 methylation is not essential for expression of the target DNA repair genes. Because BOD1L becomes highly phosphorylated after DNA damage and acts to protect damaged replication forks, the SETD1A complex, and BOD1L in particular, are key nodes for the DNA damage repair network.

cell biology↗

bioRxiv2023

Towards a Foundation Model of the Mouse Visual Cortex

The complexity of neural circuits makes it challenging to decipher the brains algorithms of intelligence. Recent break-throughs in deep learning have produced models that accurately simulate brain activity, enhancing our understanding of the brains computational objectives and neural coding. However, these models struggle to generalize beyond their training distribution, limiting their utility. The emergence of foundation models, trained on vast datasets, has introduced a new AI paradigm with remarkable generalization capabilities. We collected large amounts of neural activity from visual cortices of multiple mice and trained a foundation model to accurately predict neuronal responses to arbitrary natural videos. This model generalized to new mice with minimal training and successfully predicted responses across various new stimulus domains, such as coherent motion and noise patterns. It could also be adapted to new tasks beyond neural prediction, accurately predicting anatomical cell types, dendritic features, and neuronal connectivity within the MICrONS functional connectomics dataset. Our work is a crucial step toward building foundation brain models. As neuroscience accumulates larger, multi-modal datasets, foundation models will uncover statistical regularities, enabling rapid adaptation to new tasks and accelerating research.

neuroscience↗

bioRxiv2023

Bipartite invariance in mouse primary visual cortex

A primary goal of sensory systems is to extract robust and meaningful features that are invariant to variations in the sensory input. Characterizing these invariances at the neuronal level is crucial for understanding how the visual system supports generalization, but the high-dimensional nature of ecological stimuli poses major challenges. Consequently, our understanding of how the brain represents invariances has historically depended on a few examples, such as phase invariance to grating stimuli in V1 complex cells. Here, we leverage the inception loop paradigm --iterating between large-scale recordings, deep learning neuronal predictive models, and in silico experiments with in vivo verification--to characterize neuronal invariances in mouse V1. Using a neuronal predictive model, we synthesized Diverse Exciting Inputs (DEIs) that strongly drive target neurons while differing substantially in image space. These DEIs revealed a novel bipartite invariance: one portion of the receptive field encodes shift-invariant, high-frequency textures, while the other encodes a fixed, low-frequency spatial pattern. This subfield division aligned with object boundaries defined by spatial frequency differences in highly activating stimuli, suggesting bi-partite invariance contributes to segmentation. Our analysis of computational models and anatomical data from the MICrONS dataset revealed a hierarchical organization of excitatory neurons in mouse V1 Layers 2/3: We found that postsynaptic neurons exhibited greater invariance than their presynaptic inputs, while neurons with lower invariance formed more connections. These findings suggest a synaptic-level hierarchy that progressively increases neural invariance within the primary visual cortex. Intriguingly, similar high-low frequency bipartite patterns strongly activate certain units in artificial neural networks, suggesting that universal visual representations govern both biological and artificial systems, potentially aiding in the extraction of visual features from complex backgrounds.

neuroscience↗

bioRxiv2023

Functional connectomics reveals general wiring rule in mouse visual cortex

Understanding the relationship between circuit connectivity and function is crucial for uncovering how the brain implements computation. In the mouse primary visual cortex (V1), excitatory neurons with similar response properties are more likely to be synaptically connected, but previous studies have been limited to within V1, leaving much unknown about broader connectivity rules. In this study, we leverage the millimeter-scale MICrONS dataset to analyze synaptic connectivity and functional properties of individual neurons across cortical layers and areas. Our results reveal that neurons with similar responses are preferentially connected both within and across layers and areas -- including feedback connections -- suggesting the universality of the like-to-like connectivity across the visual hierarchy. Using a validated digital twin model, we separated neuronal tuning into feature (what neurons respond to) and spatial (receptive field location) components. We found that only the feature component predicts fine-scale synaptic connections, beyond what could be explained by the physical proximity of axons and dendrites. We also found a higher-order rule where postsynaptic neuron cohorts downstream of individual presynaptic cells show greater functional similarity than predicted by a pairwise like-to-like rule. Notably, recurrent neural networks (RNNs) trained on a simple classification task develop connectivity patterns mirroring both pairwise and higher-order rules, with magnitude similar to those in the MICrONS data. Lesion studies in these RNNs reveal that disrupting like-to-like connections has a significantly greater impact on performance compared to lesions of random connections. These findings suggest that these connectivity principles may play a functional role in sensory processing and learning, highlighting shared principles between biological and artificial systems.

neuroscience↗

bioRxiv2023

Pattern completion and disruption characterize contextual modulation in mouse visual cortex

Vision is fundamentally context-dependent, with neuronal responses influenced not just by local features but also by surrounding contextual information. In the visual cortex, studies using simple grating stimuli indicate that congruent stimuli--where the center and surround share the same orientation--are more inhibitory than when orientations are orthogonal, potentially serving redundancy reduction and predictive coding. Understanding these center-surround interactions in relation to natural image statistics is challenging due to the high dimensionality of the stimulus space, yet crucial for deciphering the neuronal code of real-world sensory processing. Utilizing large-scale recordings from mouse V1, we trained convolutional neural networks (CNNs) to predict and synthesize surround patterns that either optimally suppressed or enhanced responses to center stimuli, confirmed by in v ivo experiments. Contrary to the notion that congruent stimuli are suppressive, we found that surrounds that completed patterns based on natural image statistics were facilitatory, while disruptive surrounds were suppressive. Applying our CNN image synthesis method in macaque V1, we discovered that pattern completion within the near surround occurred more frequently with excitatory than with inhibitory surrounds, suggesting that our results in mice are conserved in macaques. Further, experiments and model analyses confirmed previous studies reporting the opposite effect with grating stimuli in both species. Using the MICrONS functional connectomics dataset, we observed that neurons with similar feature selectivity formed excitatory connections regardless of their receptive field overlap, aligning with the pattern completion phenomenon observed for excitatory surrounds. Finally, our empirical results emerged in a normative model of perception implementing Bayesian inference, where neuronal responses are modulated by prior knowledge of natural scene statistics. In summary, our findings identify a novel relationship between contextual information and natural scene statistics and provide evidence for a role of contextual modulation in hierarchical inference.

neuroscience↗

bioRxiv2023

Dopamine receptor D2 confers colonization resistance via gut microbial metabolites

Abstract/Summary ParagraphThe gut microbiome plays major roles in modulating host physiology. One such function is colonization resistance, or the ability of the microbial collective to protect the host against enteric pathogens1-3, including enterohemorrhagic Escherichia coli (EHEC) serotype O157:H7, an attaching and effacing (AE) food-borne pathogen that causes severe gastroenteritis, enterocolitis, bloody diarrhea, and acute renal failure (hemolytic uremic syndrome)4,5. Although gut microbes can provide colonization resistance by outcompeting some pathogens or modulating host defense provided by the gut barrier and intestinal immune cells, this phenomenon remains poorly understood. Emerging evidence suggests that small-molecule metabolites produced by the gut microbiota may mediate this process6. Here, we show that tryptophan (Trp)-derived metabolites produced by the gut bacteria protect the host against Citrobacter rodentium, a murine AE pathogen widely used as a model for EHEC infection7,8, by activation of the host neurotransmitter dopamine receptor D2 (DRD2) within the intestinal epithelium. We further find that these Trp metabolites act through DRD2 to decrease expression of a host actin regulatory protein involved in C. rodentium and EHEC attachment to the gut epithelium via formation of actin pedestals. Previously identified mechanisms of colonization resistance either directly affect the pathogen by competitive exclusion or indirectly by modulation of host defense mechanisms9,10, so our results delineate a noncanonical colonization resistance pathway against AE pathogens featuring an unconventional role for DRD2 outside the nervous system in controlling actin cytoskeletal organization within the gut epithelium. Our findings may inspire prophylactic and therapeutic approaches for improving gut health and treating gastrointestinal infections, which afflict millions globally.

microbiology↗

bioRxiv2023

The prospect of universal coronavirus immunity: a characterization of reciprocal and non-reciprocal T cell responses against SARS-CoV2 and common human coronaviruses

T cell immunity plays a central role in clinical outcomes of Coronavirus Infectious Disease 2019 (COVID-19). Therefore, T cell-focused vaccination or cellular immunotherapy might provide enhanced protection for immunocompromised patients. Pre-existing T cell memory recognizing SARS-CoV2 antigens antedating COVID-19 infection or vaccination, may have developed as an imprint of prior infections with endemic non-SARS human coronaviruses (hCoVs) OC43, HKU1, 229E, NL63, pathogens of "common cold". In turn, SARS-CoV2-primed T cells may recognize emerging variants or other hCoV viruses and modulate the course of subsequent hCoV infections. Cross-immunity between hCoVs and SARS-CoV2 has not been well characterized. Here, we systematically investigated T cell responses against the immunodominant SARS-CoV2 spike, nucleocapsid and membrane proteins and corresponding antigens from - and {beta}-hCoVs among vaccinated, convalescent, and unexposed subjects. Broad T cell immunity against all tested SARS-CoV2 antigens emerged in COVID-19 survivors. In convalescent and in vaccinated individuals, SARS-CoV2 spike-specific T cells reliably recognized most SARS-CoV2 variants, however cross-reactivity against the omicron variant was reduced by approximately 50%. Responses against spike, nucleocapsid and membrane antigens from endemic hCoVs were more extensive in COVID-19 survivors than in unexposed subjects and displayed cross-reactivity between - and {beta}-hCoVs. In some, non-SARS hCoV-specific T cells demonstrated a prominent non-reciprocal cross-reactivity with SARS-CoV2 antigens, whereas a distinct anti-SARS-CoV2 immunological repertoire emerged post-COVID-19, with relatively limited cross-recognition of non-SARS hCoVs. Based on this cross-reactivity pattern, we established a strategy for in-vitro expansion of universal anti-hCoV T cells for adoptive immunotherapy. Overall, these results have implications for the future design of universal vaccines and cell-based immune therapies against SARS- and non-SARS-CoVs.

immunology↗

bioRxiv2022

RecA balances genomic stability and evolution using many successive mismatch tolerant homology tests

A double-strand break (DSB) must usually be repaired with as little alteration to the genome as possible, though some rare alterations provide valuable genomic evolution. In E.coli, a DSB undergoes resection to give 3 ssDNA tails. These invading strand tails are loaded with RecA protein and then rapidly search the genome for the corresponding (allelic) partner. Thus, a searching ssDNA/RecA filament must almost never make stable non-allelic contact; therefore, it has been puzzling that RecA forms stable products that join partially homologous sequences. Homology testing by RecA family proteins begins with an 8-bp test, followed by successive homology tests of base pair triplets. Here we introduce a highly simplified homology recognition model to highlight how mismatch sensitivity could affect non-allelic pairing in bacterial genomes. The model predicts that even if each triplet test accepts 2 mismatches, RecA can have [~] 95% probability of establishing allelic pairing after a DSB in E. coli; however, that accuracy requires homology testing {gap}50 contiguous base pairs, consistent with the homology lengths probed in vivo. In contrast, if no mismatches are accepted testing 14 bp is sufficient, and testing more base pairs does not reduce non-allelic pairing because bacterial genomes contain long repeats.

biophysics↗

bioRxiv2022

A Community Challenge to Predict Clinical Outcomes After Immune Checkpoint Blockade in Non-Small Cell Lung Cancer

PurposePredictive biomarkers of immune checkpoint inhibitors (ICIs) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from the Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled the assessment of predictive models by using data from two randomized controlled clinical trials (RCTs) of ICIs in first-line metastatic NSCLC. MethodsParticipants developed and trained models using public resources. These were evaluated with data from the CheckMate 026 trial (NCT02041533), according to the model-to-data paradigm to maintain patient confidentiality. The generalizability of the models with the best predictive performance was assessed using data from the CheckMate 227 trial (NCT02477826). Both trials were phase III RCTs with a chemotherapy control arm, which supported the differentiation between predictive and prognostic models. Isolated model containers were evaluated using a bespoke strategy that considered the challenges of handling transcriptome data from clinical trials. ResultsA total of 59 teams participated, with 417 models submitted. Multiple predictive models, as opposed to a prognostic model, were generated for predicting overall survival, progression-free survival, and progressive disease status with ICIs. Variables within the models submitted by participants included tumor mutational burden (TMB), programmed death ligand 1 (PD-L1) expression, and gene-expression-based signatures. The bestperforming models showed improved predictive power over reference variables, including TMB or PD-L1. ConclusionThis DREAM Challenge is the first successful attempt to use protected phase III clinical data for a crowdsourced effort towards generating predictive models for ICIs clinical outcomes and could serve as a blueprint for similar efforts in other tumor types and disease states, setting a benchmark for future studies aiming to identify biomarkers predictive of ICIs efficacy. Context summaryO_ST_ABSKey objectiveC_ST_ABSNot all patients with non-small cell lung cancer (NSCLC) eligible for immune checkpoint inhibitor (ICIs) respond to treatment, but accurate predictive biomarkers of ICIs clinical outcomes are currently lacking. This crowdsourced initiative enabled the robust assessment of predictive models using data from two randomized clinical trials of first-line ICI in metastatic NSCLC. Knowledge generatedModels submitted indicate that a combination of programmed death ligand 1 (PD-L1), tumor mutational burden (TMB), and immune gene signatures might be able to identify patients more likely to respond to ICIs. TMB and PD-L1 seemed important to predict progression-free survival and overall survival. Mechanisms including apoptosis, T-cell crosstalk, and adaptive immune resistance appeared essential to predict response. Relevance

cancer biology↗

bioRxiv2022

ApoE isoforms differentially regulate neuronal membrane proteasomes to shift the threshold for pathological aggregation of endogenous Tau

Neuroproteasomes are a subset of 20S proteasomes that are localized to the neuronal plasma membrane and degrade newly synthesized proteins. To date, the molecular composition of neuroproteasomes is undefined, and moreover, whether neuroproteasomes can influence protein aggregation with relevance to neurodegenerative disorders remains unexplored. Using a Cre-dependent conditional knock-in mouse line to endogenously tag the proteasome, we find that neuroproteasomes co-purify with ApoE, the most significant risk factor for late-onset Alzheimers Disease (AD). We discover that neuroproteasome membrane localization is differentially modulated by ApoE isoforms (E4<E3<E2) in vitro, in vivo, and in human postmortem samples. We synthesized selective, neuroproteasome-specific inhibitors and discovered that neuroproteasome inhibition induces aggregation of endogenous mouse and human Tau, without the need for seeding or pathogenic mutations. Using hApoE-KI/hTau-KI crosses, we find that ApoE isoforms differentially shift the aggregation threshold for Tau. Neuroproteasome inhibition in vivo is sufficient to induce sarkosyl-insoluble and Thioflavin-S positive endogenous Tau aggregates in only three days, which are completely abrogated by co-application of cycloheximide. Newly synthesized Tau levels increase threefold after neuroproteasome inhibition, leading us to posit that newly synthesized Tau is uniquely susceptible to aggregation due to neuroproteasome dysfunction. Overall, our data define neuroproteasomes as a pivotal proteostasis mechanism underlying the formation of endogenous Tau aggregates, which is directly regulated by the largest genetic risk factor for late-onset Alzheimers Disease.

neuroscience↗

bioRxiv2022

Running ahead of evolution - AI based simulation for predicting future high-risk SARS-CoV-2 variants

The never-ending emergence of SARS-CoV-2 variations of concern (VOCs) has challenged the whole world for pandemic control. In order to develop effective drugs and vaccines, one needs to efficiently simulate SARS-CoV-2 spike receptor binding domain (RBD) mutations and identify high-risk variants. We pretrain a large protein language model with approximately 408 million protein sequences and construct a high-throughput screening for the prediction of binding affinity and antibody escape. As the first work on SARS-CoV-2 RBD mutation simulation, we successfully identify mutations in the RBD regions of 5 VOCs and can screen millions of potential variants in seconds. Our workflow scales to 4096 NPUs with 96.5% scalability and 493.9x speedup in mixed precision computing, while achieving a peak performance of 366.8 PFLOPS (reaching 34.9% theoretical peak) on Pengcheng Cloudbrain-II. Our method paves the way for simulating coronavirus evolution in order to prepare for a future pandemic that will inevitably take place. Our models are released at https://github.com/ZhiweiNiepku/SARS-CoV-2_mutation_simulation to facilitate future related work. JustificationWe develop a novel multi-constraint variation prediction framework to simulate SARS-CoV-2 RBD mutations, reaching a peak performance of 366.8 PFLOPS with 96.5% scalability and achieving 493.9x speedup. Our method facilitates the prediction and prioritization of future high-risk variants for the early deployment of drugs and vaccines. Performance attributes O_TBL View this table: org.highwire.dtl.DTLVardef@1b1873aorg.highwire.dtl.DTLVardef@25314eorg.highwire.dtl.DTLVardef@1c80130org.highwire.dtl.DTLVardef@1c61b21org.highwire.dtl.DTLVardef@11f21c5_HPS_FORMAT_FIGEXP M_TBL C_TBL Overview of the problemCoronavirus Disease 2019 (COVID-19) has spread rapidly to more than 200 countries or regions since December 2019. Due to its high infectivity, there have been over 645 million confirmed cases, including approximately 6.6 million deaths, reported by the World Health Organization (WHO) as of December 20221. In addition to being a serious threat to human health, COVID-19 has had a catastrophic impact on the global economy.

bioinformatics↗

bioRxiv2022

Evaluation of antibody kinetics and durability in health subjects vaccinated with inactivated COVID-19 vaccine (CoronaVac): A cross-sectional and cohort study in Zhejiang, China

BackgroundAlthough inactivated COVID-19 vaccines are proven to be safe and effective in the general population, the dynamic response and duration of antibodies after vaccination in the real world should be further assessed. MethodsWe enrolled 1067 volunteers who had been vaccinated with one or two doses of CoronaVac in Zhejiang Province, China. Another 90 healthy adults without previous vaccinations were recruited and vaccinated with three doses of CoronaVac, 28 days and 6 months apart. Serum samples were collected from multiple timepoints and analyzed for specific IgM/IgG and neutralizing antibodies (NAbs) for immunogenicity evaluation. Antibody responses to the Delta and Omicron variants were measured by pseudovirus-based neutralization tests. ResultsOur results revealed that binding antibody IgM peaked 14-28 days after one dose of CoronaVac, while IgG and NAbs peaked approximately 1 month after the second dose then declined slightly over time. Antibody responses had waned by month 6 after vaccination and became undetectable in the majority of individuals at 12 months. Levels of NAbs to live SARS-CoV-2 were correlated with anti-SARS-CoV-2 IgG and NAbs to pseudovirus, but not IgM. Homologous booster around 6 months after primary vaccination activated anamnestic immunity and raised NAbs 25.5-fold. The NAb inhibition rate subsequently rose to 36.0% for Delta (p=0.03) and 4.3% for Omicron (p=0.004), and the response rate for Omicron rose from 7.9% (7/89) to 17.8% (16/90). ConclusionsTwo doses of CoronaVac vaccine resulted in limited protection over a short duration. The homologous booster slightly increased antibody responses to the Delta and Omicron variants; therefore, the optimization of booster procedures is vital. FundingKey Research and Development Program of Zhejiang Province; Key Program of Health Commission of Zhejiang Province/ Science Foundation of National Health Commission; Major Program of Zhejiang Municipal Natural Science Foundation.

immunology↗

bioRxiv2022

The mechanism of nicotinamide phosphoribosyltransferase whereby positive allosteric modulation elevates cellular NAD+

In aging and disease, cellular NAD+ is depleted by catabolism to nicotinamide (NAM) and NAD+ supple-mentation is being pursued to enhance human healthspan and lifespan. Activation of nicoti namide phosphoribosyl -transferase (NAMPT), the rate-limiting step in NAD+ biosynthesis, has potential to increase salvage of NAM. Novel NAMPT positive allosteric modulators (N-PAMs) were discovered in addition to demonstration of NAMPT activati on by biogenic phenols. The mechanism of activation was revealed through synthesis of novel chemical probes, new NAMPT co-crystal structures, and enzyme kinetics. Binding to a rear channel in NAMPT regulates NAM binding and turnover, with biochemical observations being replicated by NAD+ measurements in human cells. The mechanism of action of N-PAMs identifies, for the first time, the role of the rear channel in regulation of NAMPT turnover coupled to feedback inhibition by NAM. N-PAM inhibition of low affinity, non-productive NAM binding via the rear channel, causes a right-shif t in KI(NAM) that accompanies an increase in enzyme activity. Conversion of an N-PAM to a high-affinity l igand blocks both high and low affinity NAM binding, ablating enzyme activity. In the presence of an N-PAM, NAMPT boosts NAD+ biosynthesis at higher NAM concentrations, in addition to relieving inhibition by NAD+. Since cellular stress often leads to enhanced catabolism of NAD+ to NAM, this mechanism is relevant to supporting cellular N AD+ levels in aging and disease. The tight regulation of cellular NAMPT is differentially regulated by N-PAMs and other activators, indicating that different classes of pharmacological activators may be engineered for cell and tissue selectivity.

biochemistry↗

bioRxiv2022

Molecular and genetic mechanisms conferring dissolution of dioecy in Diospyros oleifera Cheng

Dioecy, a sexual system of single-sex (gynoecious/androecious) individuals, is rare in flowering plants. This rarity may be a result of the frequent transition from dioecy into systems with co-sex individuals. Here, we report potential molecular and genetic mechanisms that underlie the dissolution of dioecy to monoecy and andro(gyno)monoecy, based on multiscale genome-wide investigations of 150 accessions of Diospyros oleifera. All co-sex D. oleifera plants, including monoecious and andro(gyno)monoecious individuals, possessed the male determinant gene OGI, implying that genetic factors control gynoecia development in genetically male D. oleifera. In both single- and co-sex plants, female function was expressed in the presence of a genome-wide decrease in methylation levels, along with sexually distinct regulatory networks of smRNAs and their targets. Furthermore, a genome-wide association study (GWAS) identified a genomic region and a DUF247 gene cluster strongly associated with the monoecious phenotype, as well as several regions that may contribute to andromonoecy. Collectively, our findings imply stable breakdown of the dioecious system in D. oleifera, presumably a result of the genomic features of the sex-linked region.

plant biology↗

bioRxiv2022

Mechanosensitive channel-based optical membrane tension biosensor

Plasma membrane tension functions as a global physical organizer of cellular activities. Technical limitations of current membrane tension measurement techniques have hampered in-depth investigation of cellular membrane biophysics and the role of plasma membrane tension in regulating cellular processes. Here, we develop an optical membrane tension biosensor by repurposing an E. coli mechanosensitive channel via insertion of circularly permuted GFP (cpGFP), which undergoes a large conformational rearrangement associated with channel activation and thus fluorescence intensity changes under increased membrane tension.

biophysics↗

bioRxiv2022

Viral proteins and virus-like particles of the LTR5_Hs endogenous retrovirus in human primordial germ cell-like cells

The hominoid-specific endogenous retrovirus LTR5_Hs is transcriptionally activated in human primordial germ cell-like cells (hPGCLCs), a pluripotent stem cell-derived cell culture model of PGCs. Here, taking the unique advantage of our novel cell culture method to obtain large amounts of pure hPGCLCs, we performed proteomics profiling of hPGCLCs and detected various viral proteins produced from the LTR5_Hs RNA via ribosomal frameshifting. We also present transmission electron microscopy images of 100-nm diameter virus-like particles (VLPs) assembled at the surface of hPGCLCs. Compared to hPGCLCs, expression of LTR5_Hs RNA is far weaker in human seminomas, the germ cell tumors resembling PGCs. Re-analysis of published single cell RNA-seq data of human embryos revealed strong activation of LTR5_Hs in migrating PGCs but suppressed in PGCs upon they reach the gonadal anlagen. In the microfluidics-supported polarized embryoids mimicking peri-implantation stages of human embryos, LTR5_Hs RNA was detected by RNA in situ hybridization in NANOG+/TFAP2C+/SOX17+ cells resembling freshly emerged PGCs. These results support that human germ cells produce LTR5_Hs proteins and VLPs during their earliest stages of normal development until their settlement in the gonadal anlagen. SUMMARY STATEMENTThe hominoid-specific endogenous retrovirus LTR5_Hs is activated in a cell culture model resembling early-stage human primordial germ cells, producing not only viral RNA but also retrovirus proteins and virus-like particles.

developmental biology↗

bioRxiv2022

Diversity and ecology of Caudoviricetes phages with genome terminal repeats in fecal metagenomes from four Dutch cohorts

The human gut harbors numerous viruses infecting the human host, microbes and other inhabitants of the gastrointestinal tract. Most of these viruses remain undiscovered, and their influence on human health is unknown. Here we characterize viral genomes in gut metagenomic data from 1,950 individuals from four population and patient cohorts. We focus on a subset of viruses that is highly abundant in the gut, remains largely uncharacterized, and allows confident complete genome identification - phages that belong to the class Caudoviricetes and possess genome terminal repeats. We detect 1,899 species-level units belonging to this subset, 19% of which do not have complete representative genomes in major public gut virome databases. These units display diverse genomic features, are predicted to infect a wide range of microbial hosts, and on average account for < 1% of metagenomic reads. Analysis of longitudinal data from 338 individuals shows that the composition of this fraction of the virome remained relatively stable over a period of 4 years. We also demonstrate that 54 species-level units are highly prevalent (detected in > 5% of individuals in a cohort). Finally, we find 34 associations between highly prevalent phages and human phenotypes, 24 of which can be explained by the relative abundance of potential hosts.

microbiology↗

bioRxiv2022

Nardilysin-Regulated Scission Mechanism Activates Polo-like Kinase 3 to Suppress the Development of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) develops through step-wise genetic and molecular alterations including Kras mutation and inactivation of apoptotic pathways. Here, we find that development of anoikis resistance and metastasis of KrasG12D-driven PDAC in mice is accelerated by deleting Plk3, explaining the often reduced Plk3 expression in human PDAC. Importantly, a 41 kDa Plk3 (p41Plk3) that contained the entire kinase domain at the N-terminus (1-353 aa) is activated by scission of the precursor p72Plk3 at Arg354 by metalloendopeptidase Nardilysin (NRDC), and the resulting p32Plk3 C-terminal Polo-box domain (PBD) was quickly removed by proteasome degradation preventing the p41Plk3 inhibition by PBD. We found that p41Plk3 is the activated form of Plk3 that regulates a feedforward mechanism to promote anoikis and suppress PDAC and metastasis. p41Plk3 phosphorylates c-Fos on Thr164, which in turn, induces expression of Plk3 and pro-apoptotic genes. These findings uncovered an NRDC-regulated post-translational mechanism (PTM) that activates Plk3, establishing a prototypic regulation by scission mechanism.

cancer biology↗