Biology subjects

Sung, J.

Publications and source records attributed to Sung, J..

At least 19 recordsLinked to original sources

bioRxiv2026

FateDriver: Weakly supervised dual-view graph learning for transition-specific prioritization of candidate regulators in cellular reprogramming

Cellular reprogramming supports regenerative medicine, yet the endogenous regulators of a specified source-to-target transition remain incompletely defined. Existing computational methods rank candidate regulators from network topology, trajectory dynamics, or cell-state labels, leaving unused the factors experimentally delivered to induce the transition. We present FateDriver, a weakly supervised dual-view graph neural network that jointly represents cells and genes from single-cell transcriptomes, treats the delivered factors as sparse gene-level labels, and ranks the remaining genes for a specified transition under a positive--unlabeled formulation. Across two OSKM datasets and one GMT dataset, FateDriver ranked first or second among six methods in recovering externally curated reference genes, exceeded a supervision-matched non-graph model despite weaker co-expression with the delivered factors, and achieved the highest recovery of protein targets of pluripotency-inducing chemical cocktails in both OSKM datasets. Holding either the source or the endpoint fixed yielded distinct candidate programs, including a DDX58--interferon axis associated with cells lacking endogenous pluripotency markers. Applying the same framework to candidate source--target pairs prioritized distinct candidate origins for two in vivo partially reprogrammed intestinal populations. FateDriver converts sparse experimental knowledge into transition-specific hypotheses for regulator prioritization from single-cell trajectories.

bioinformatics↗

bioRxiv2026

Genus-wide re-speciation of Corynebacterium and genomic characterisation of 87 sinus isolates resolves taxonomic conflicts and identifies four candidate novel species

Corynebacterium species are common members of the sinonasal microbiome and have shown conflicting associations with sinus health and chronic rhinosinusitis (CRS) in genus-level surveys. To better resolve the taxonomy and species-level functions of sinus corynebacteria, we generated complete long-read genome assemblies for 87 isolates, sourced from the middle meatus of 71 patients (51 with CRS, 20 healthy controls). We re-derived species boundaries de novo across the whole genus by average nucleotide identity (ANI), clustering 4,661 quality-filtered genomes retrieved from public databases and delineating higher-order species complexes. Our re-speciation assigned a species to 282 unlabelled corynebacteria, and corrected taxonomy for 266 NCBI accessions. We identified four novel candidate species from our isolate collection, and 39 public genomes fell within these species' boundaries. Whole-genome assignment reclassified 41 of our 87 isolates relative to mass-spectrometry (MALDI-TOF MS) identification, which only resolved to the species-complex level. Comparison of genome annotation characterised accessory functions that partitioned along species-complex lines, including glycogen and glycan utilisation, fatty-acid biosynthesis, cofactor (biotin and thiamine) auxotrophy, and iron-acquisition systems. Virulence and antimicrobial-resistance determinants were sparse, and the diphtheria toxin gene was universally absent. Acquired antimicrobial resistance was enriched on plasmids, whilst virulence genes were depleted from horizontally transferred compartments. Contrary to its frequent report in sinus microbiome studies, no C. tuberculostearicum genome publicly accessible via NCBI was found to be isolated from the sinonasal tract. Continued genome-level interrogation of Corynebacterium and contribution of sinus-commensals to reference databases will improve species-level understanding of the role of corynebacteria in the sinonasal microbiome.

microbiology↗

bioRxiv2026

A Disease-Agnostic Nasal Microbiome Wellness Index for Standardized Assessment of Upper-Airway Respiratory Health

BackgroundUpper-airway and respiratory conditions impose a large and growing global burden, yet there is no standardized way to assess whether a nasal microbiome is "healthy". Currently, monitoring remains reactive, beginning only after symptoms manifest. The nasal cavity is well suited to proactive monitoring: it shapes respiratory health and pathogen colonization resistance, and can be sampled non-invasively and repeatedly. To address this gap, we introduce the Nasal Microbiome Wellness Index (NMWI), a disease-agnostic, continuous score of nasal microbiome health derived from LASSO-penalized logistic regression. Rather than counting taxa, it learns which taxa (and in what balance) characterize a healthy nose and returns the predicted log-odds that a profile resembles a healthy state. The index was trained on 1654 nasal 16S rRNA gene amplicon sequencing samples (589 healthy, 1065 non-healthy) pooled from 27 publicly available studies, uniformly reprocessed through a single computational pipeline. ResultsThe NMWI comprises an interpretable signature of 24 taxa whose combined relative abundances determine the health-associated log-odds. Health-associated genera such as Corynebacterium and Cutibacterium raised the score, while dysbiosis-associated genera such as Pseudomonas and Escherichia-Shigella lowered it. The NMWI substantially outperformed the Shannon, Simpson, and Chao1 diversity indices, which showed negligible, directionally inconsistent separation between healthy and non-healthy samples (|Cliffs{delta} | = 0.01-0.20), whereas the NMWI produced large, consistent separation ({delta} = 0.65). It achieved a balanced accuracy of 74.37% on the training data (resubstitution estimate), and 73.43% under repeated 10-times 10-fold cross-validation. Performance remained stable at mean balanced accuracy of 73.82% under a leave-one-study-out framework, reflecting cross-study generalizability. In independent external cohorts, the balanced accuracy was 71.49%, and leave-one-disease-out analysis (in which each disease condition was withheld from training) showed a mean balanced accuracy of 63.92% across unseen conditions, consistent with a disease-agnostic design. The index also generalized across heterogeneous datasets spanning multiple 16S rRNA gene hypervariable regions--to our knowledge the first demonstration of such cross-study, cross-region transferability for the nasal cavity. ConclusionsThe NMWI distills a complex nasal microbial profile into a single interpretable score computed directly from the 16S rRNA gene data that dominate existing nasal research, making it immediately applicable to published and future datasets without re-sequencing. By replacing descriptive, diversity-based comparison with a quantitative standard, it offers a reproducible, open-source foundation for cross-study benchmarking, individual-level phenotyping, and longitudinal respiratory wellness monitoring.

bioinformatics↗

bioRxiv2026

Diversity and evolution of the transcriptional regulatory networks of Pseudomonas strains revealed using machine learning

The genus Pseudomonas consists of diverse and ecologically significant species that form close associations with both plants and animals. This genus is widely studied due to the clinically relevant Pseudomonas aeruginosa, model plant pathogen Pseudomonas syringae, and non-pathogenic, industrially relevant Pseudomonas putida. The different metabolic and physiological capabilities of these species are enabled by their unique genetic makeup as well as varying regulatory mechanisms. To study the transcriptional basis for the diversity of the three species, we applied independent component analysis to strain-specific RNA-seq datasets to identify independently modulated gene sets (iModulons) and their condition-specific activity levels. We then mapped iModulons across strains based on their similarity in orthologous gene membership. Through comparison of iModulon gene membership and activities, we find that: (i) iModulons reveal shared and unique regulatory modalities across strains; (ii) unique adaptations in common functions, such as translation and pyoverdine production/uptake, manifest through both differential iModulon gene membership and condition-specific activation states in each strain; (iii) iModulons facilitate comparison of stress responses at the systems level; and (iv) iModulons highlight unique virulence factor enrichment and host-specific adaptations in human and plant pathogens. Altogether, comparing the modularized transcriptomes of the three strains provides unique and comprehensive insights into their differential evolution. ImportanceClosely related bacterial species often have vastly different metabolic and physiological capabilities, yet the regulatory mechanisms underlying these adaptations remain poorly understood. Here, we compare the transcriptional regulatory networks of three representative Pseudomonas strains through cross-strain iModulon analysis. By comparing both iModulon gene composition and activity across strains, we identify conserved regulatory modules alongside lineage-specific adaptations in functions associated with virulence, translation, iron acquisition, motility, and stress responses. Our results demonstrate that iModulons provide a genome-scale framework for comparing transcriptional regulation across closely related organisms, revealing regulatory innovations that are not apparent from genome comparisons alone. This work establishes a scalable approach for studying the evolution of bacterial transcriptional regulatory networks and the regulatory basis of niche specialization.

systems biology↗

bioRxiv2026

Efficient base editing and development in human embryos without chromosomal alterations

Cas9-based tools enable the introduction of genetic lesions to investigate DNA repair outcomes and edit the genome at disease-relevant loci. DNA double-strand breaks (DSBs) induced by CRISPR/Cas9 result in frequent aneuploidy and large deletions, revealing a repair deficiency in early human embryos and limiting the clinical application of this technology. Here we evaluated the DNA repair outcomes of DNA nicks and mismatches introduced using base editors in human embryos at two targets, PCSK9 and HBG. Editing was efficient and, unlike Cas9-induced DSBs, did not result in either chromosomal abnormalities or large deletions. Small insertions or deletions after base editing were rare, and off-target activity was dependent on the guide RNA. Delivering the base editor as a protein at fertilization or at the pronuclear stage allowed normal development to the blastocyst stage and the derivation of edited stem cell lines. In stark contrast, introduction of the editor as RNA resulted in early embryo arrest. Our results demonstrated that, unlike DSBs, DNA nicks and mismatches are efficiently repaired in human embryos, allowing specific on-target changes without genotoxic consequences.

genetics↗

bioRxiv2026

IFITM1 inhibits Henipavirus membrane fusion by trapping ephrinB2 receptors in fusion-unfavorable membrane nanodomains.

Nipah (NiV) and Hendra (HeV) viruses are prototype henipaviruses (HNV) within the family of Paramyxoviridae. They are highly pathogenic zoonotic paramyxoviruses that cause fatal encephalitis in humans, with case fatality rates of 40-70%. These viruses use the receptor-binding protein (G) to engage host receptors ephrinB2 and/or ephrinB3, while the fusion protein (F) drives membrane fusion leading to virus entry and cell-cell fusion. Interferon-inducible transmembrane (IFITM) proteins restrict the infection of many unrelated viruses at virus entry. We show that the knockdown of IFITM1 enhances HNV entry and cell-cell fusion in both human epithelial and endothelial cells, while overexpression of IFITM1 inhibits both. Using single-molecule localization microscopy, we observed that IFITM1 forms nanoclusters on the plasma membrane that are enhanced upon interferon stimulation. IFITM1 clusters spatially co-occur with GM1-enriched, raft-like membrane domains. Notably, IFITM1 interacts with ephrinB2, and redistributes ephrinB2 into larger and denser clusters, potentially within GM1-enriched regions. Using single-particle tracking, we further show that ephrinB2s lateral diffusion on the plasma membrane is confined by IFITM1, and this confinement is not reversed by amphotericin B, a membrane-permeabilizing agent that increases membrane fluidity. Our data suggest that IFITM1 sequesters ephrinB2 in fusion-unfavorable membrane domains, thereby enhancing the energy barrier for virus-cell membrane fusion and decreasing the virus-receptor encounters. SignificanceNipah (NiV) and Hendra (HeV) viruses are zoonotic paramyxoviruses that cause fatal encephalitis in humans. Here, we show that IFITM1 inhibits NiV and HeV entry at the surface of epithelial and endothelial cells. We report that IFITM1 restricts NiV entry by sequestering the host receptor ephrinB2 in membrane domains that are energetically unfavorable for virus-cell membrane fusion. IFITM1 also restricts ephrinB2 lateral diffusion on the plasma membrane, thereby reducing productive virus-receptor encounters. Notably, amphotericin B treatment, which increases membrane fluidity, did not rescue IFITM1-mediated confinement of ephrinB2 or restore NiV entry. Our data reveal a new mechanism by which IFITM1 restricts NiV infection, suggesting that its antiviral activity extends beyond simply altering membrane fluidity.

microbiology↗

bioRxiv2026

Cellular Chemical Dynamics Governing Signal Transduction and Adaptive Gene Expression: Beyond Classical Kinetics

Cellular adaptation is inherently nonstationary processes with complex stochastic dynamics1-5. Despite remarkable progress in quantitative biology6-11, a quantitative understanding of the cell adaptation dynamics in terms of the underlying cellular network remains elusive. Here, we present the next-generation chemical dynamics model and theory for cellular networks, providing an effective, quantitative description of the adaptive gene expression dynamics in living cells responding to external stimuli. Unlike conventional kinetics, chemical dynamics of cellular network modules are characterized by their reaction-time distributions, rather than by rate coefficients12. For a general model of cell signal transduction and adaptive gene expression, we derive exact analytical expressions for the time-dependent mean and variance of protein numbers produced in response to external stimuli, validated by accurate stochastic simulations. These results provide a unified, quantitative explanation of the stochastic responses of diverse E. coli genes to antibiotic stress and transcriptional induction. Our analysis reveals existence of a general quadratic relationship between the mean and variance of activation times across diverse genes. The gene activation process influences transient dynamics of downstream protein levels, but not their steady-state levels. In contrast, post-translational maturation process affects both transient dynamics and steady-state variability of mature protein levels. This finding indicates that the gene expression variability measured by fluorescent reporter proteins depends on the maturation time of the reporters. This work suggests a new direction for the development of digital twins of living cells.

biophysics↗

bioRxiv2025

The landscape of allele-specific expression in human kidneys

Allele-specific expression (ASE), the preferential expression of one gene copy, is a key mechanism of genomic regulation. However, its role in human kidney disease remains poorly understood. In this study, we generated a high-quality, genome-wide ASE map using paired whole-genome sequencing and RNA-seq from microdissected glomerular (GLOM) and tubulointerstitial (TUBE) compartments of patients with proteinuric kidney disease. We showed that the majority of common ASE events were deterministic and sequence-mediated. We also found that diseased kidneys exhibited significantly more ASE in GLOM than TUBE, compared to controls. Unexpectedly, higher ASE in GLOM than TUBE was significantly associated with improved kidney disease outcomes in the disease cohort. Differential gene expression analysis suggested this was the result of an active, protective transcriptional response, including ribosome and ATP synthesis upregulation, rather than pathogenic dysregulation. Our work reveals glomerular ASE as a marker of adaptive transcriptional activity in proteinuric kidney disease.

genomics↗

bioRxiv2025

Clonal dynamics of monozygotic twinning in early human embryogenesis

Monozygotic twins are derived from the split of a single zygote early in embryogenesis. Although it was hypothesized that the timing of twining is overall associated with fetal membrane configuration of twins, i.e., chorionicity and amnionicity, our understanding of early embryonic clonal dynamics underlying human twinning is limited. Here we explored the segregations of early embryonic lineages in 7 dichorionic diamniotic (DCDA), 7 monochorionic diamniotic (MCDA), 8 monochorionic monoamniotic (MCMA) monozygotic twins, and 1 dichorionic triamniotic (DCTA) monozygotic triplets, using post-zygotic early embryonic mutations (EEMs) as endogenous lineage barcodes. Patterns of the early lineage distributions among monozygotic twins revealed three apparent clonal categories, referred to as para-identical, sub-identical, and full-identical twins, which largely correlated with the amnionicity of the twins. Rather, despite conventional wisdom, chorionicity was not substantially associated with early clonal compositions, but with blood exchanges in utero. In sub-identical twins, where one co-twin was clonally a part of the other, our data suggested that the foundation of the latter co-twin was established after acquisition of a median of 6 additional post-zygotic mutations (range: 2-13), corresponding to [~]5 early cell divisions. Additional in-depth analysis on the matched placenta from an MCDA twin suggested that separation of two co-twins can precede the separation of the placenta and embryonic proper, and a single chorion can be formed even with multiclonal origin. Our findings provide insights into the clonal dynamics, twinning processes, and cell fate decisions in early human embryogenesis.

genomics↗

bioRxiv2025

Revealing Transcriptomic Responses in Escherichia coli During Early Antibiotic Exposure

The earliest responses of pathogenic bacteria to antibiotics can affect the outcome of an infection. While long-term adaptations have been extensively studied, the immediate transcriptional changes that unfold immediately following antibiotic exposure remain poorly understood. Here, we applied iModulon analysis to time-resolved transcriptomic data from Escherichia coli exposed to subinhibitory concentrations of two antibiotics (ampicillin and ciprofloxacin), capturing transcriptional regulatory changes occurring within the first 30 minutes of exposure. This analysis reveals an integrated, three-phase response: an immediate and sustained primary response that broadly activates stress programs, a transient secondary response that restores redox balance, and a tertiary response that supports long-term survival through metabolic remodeling and antibiotic-specific defenses. These results highlight a coordinated and dynamic regulatory strategy describing how metabolic, redox, and stress responses are integrated to manage the physiological challenges of antibiotic stress. By disentangling these overlapping transcriptional regulatory programs, this work offers a genome-scale understanding of how survival mechanisms unfold during the critical moments following antibiotic exposure. The study opens new directions for investigating early survival mechanisms and the possible identification of new targets to disrupt the initial adaptation process. ImportanceInitial bacterial responses to antibiotics are important for survival and can influence the development of tolerance and resistance. Yet this period remains poorly understood, in part because the transcriptional responses that unfold within minutes of antibiotic exposure are complex and difficult to interpret. In this study, we applied novel data generation and data analytics approaches to untangle the complexity of the initial response of Escherichia coliI to two antibiotics. We reveal a three-phase process that explains how E. coli coordinates stress responses, maintains redox homeostasis, and establishes longer-term defenses. The novel transcriptomic analytics elucidate independently regulated sets of genes that constitute cellular processes. By identifying all such cellular processes that react over the initial time scale, we can deconvolute the response based on first principles of cellular physiology.

systems biology↗

bioRxiv2025

PHLAME: A benchmark for continuous evaluation of host phenotype prediction from shotgun metagenomic data

Predicting host phenotypes from shotgun metagenomic data is essential for translating microbiome research into clinical practice)Despite the development of numerous computational tools for this task, researchers often default to traditional machine learning methods such as Random Forest)This hesitancy to adopt newer methods stems from their complexity as well as the lack of standardized evaluations, as most tools are assessed on different datasets and compared against a limited set of methods)Here, we introduce LAMPP, a standardized benchmark for evaluating methods for predicting host phenotypes from gut metagenomic data)LAMPP features a diverse range of prediction tasks and enables consistent, comparative assessments across prediction tools)Our systematic evaluation of existing tools shows that classic machine learning methods (e.g., Random Forest) perform competitively, offering both ease of use and state-of-the-art results)At the same time, it demonstrates that microbiome-based phenotype prediction remains a challenging problem)By providing a consistent platform for ongoing evaluation and access to raw sequencing data, LAMPP motivates the development of novel prediction pipelines from raw sequencing data to phenotype prediction, including novel sample representation and data augmentation strategies)LAMPP is publicly available for ongoing benchmarking at https://lampp.yassourlab.com/.

bioinformatics↗

bioRxiv2025

Proteomic analysis of exosomes from lymphatic affluents reveals their implications in developing premetastatic niche in melanoma.

Melanoma is an aggressive form of skin cancer that often spreads via lymphatic pathways to regional and distant sites. Melanoma-derived lymphatic exosomes play a crucial role in forming a tumor-supportive environment for metastasis, or premetastatic niche, within the first tumor draining lymph node, also known as the sentinel lymph node (SLN). Therefore, analyzing the proteomic content of tumor-draining lymphatic exosomes that deliver oncogenic molecules to the SLN is important in understanding the premetastatic niche. To reveal the proteomic landscape of lymphatic exosomes, we performed multidimension liquid chromatography-tandem mass spectrometry with multiplexing (18-samples) using tandem mass tag (TMT) labeling to profile the lymphatic exosomal proteomes obtained from afferent lymphatic channels leading to the SLN of patients with melanoma (n=6), control afferent lymphatic channels from prophylactic mastectomy (n=3) and non-cancer post-operative lymphatic fluid (n=9). Lymphatic fluid from postoperative lymphadenectomy drains served as another control to filter out non-melanoma alteration in lymph that may be related to the procedure of surgical resection and wound healing process. Our proteomic analysis identified 3929 proteins in the lymphatic exosomes, of which 968 were unique proteins absent from the current exosomal database. Interestingly, melanoma lymphatic exosomes possess distinctive proteomic cargo, which is significantly associated with cancer-associated and cellular structural remodeling pathways (FDR <0.05). Moreover, proinflammatory wound healing pathways are predominantly present in melanoma and postoperative lymph fluid compared to normal control afferent lymphatic channels. We identified a total of 17 uniquely modulated proteins in melanoma compared to control and postoperative lymph, which are critically involved in the process of melanoma tumorigenesis. At least ten upregulated proteins strongly correlate with each other at the gene expression levels in melanoma tumors compared to controls and may serve as a signature panel for melanoma (p = 2.13 x 10-58). In summary, this study represents the first comparative analysis of the lymphatic exosomal proteome and highlights distinct exosomal proteins that may support premetastatic niche formation in the SLN.

cancer biology↗

bioRxiv2025

DSB repair kinetics impair CRISPR-Cas9 editing in human embryos

Cas9 provides a powerful tool to interrogate DNA repair and to introduce targeted genetic modifications. However, a major challenge of Cas9-based editing in human embryos is the occurrence of chromosomal abnormalities caused by Cas9 cleavage. Furthermore, mosaicism - different genetic outcomes in different cells, prevent accurate genotyping using a single embryo biopsy. Through timed analysis of editing outcomes during the first cell cycle and timed inhibition of Cas9 using AcrIIA4, we show that most edits occur at least 12 hours post Cas9 injection and therefore after the first S-phase. This timing limits the ability to achieve uniform editing across cells. We found that segmental chromosomal abnormalities and the consequential loss of heterozygosity are common at Cas9 cleavage sites throughout the genome, including at MYBPC3 and at CCR5 loci, for which this has not previously been reported. Surprisingly, inhibiting Cas9 activity 8-12 hours before mitosis does not eliminate chromosomal aneuploidies. This suggests that double-strand break (DSB) repair in human embryos is exceedingly slow, with breaks remaining unrepaired for many hours. Thus, the timing of DSB induction and repair relative to the first S-phase and the first mitosis is intrinsically limiting to preventing mosaicism and maintaining genome stability in embryonic gene editing.

developmental biology↗

bioRxiv2024

Inhibition of nitric oxide synthase transforms carotid occlusion-mediated benign oligemia into de novo large cerebral infarction

It remains unclear why unilateral proximal carotid artery occlusion (UCAO) causes benign oligemia, without progressing to cerebral infarction, in mice, yet leads to a wide variety of outcomes (ranging from asymptomatic to death) in humans. We hypothesized that inhibition of NOS both transforms UCAO-mediated oligemia into full infarction and expands pre-existing infarction. In support, intraperitoneal administration of N{omega}-nitro-L-arginine methyl ester (L-NAME) followed by UCAO induced large-arterial infarction in mice, unlike UCAO alone. Six-hour laser-speckle-contrast imaging detected spreading ischemia in mice with infarction as assessed at 24h. In agreement with vasoconstriction/microthrombus formation shown by intravital microscopy, the NO-donor, molsidomine and the endothelial-NOS- activating antiplatelet, cilostazol, attenuated or prevented progression to infarction. Moreover, UCAO without L-NAME caused infarction in mice with hyperglycemia and hyperlipidemia, which, in turn, were associated with greater symmetric dimethylarginine (SDMA) levels. Further, increased levels of glucose and cholesterol associated with significantly larger infarct volumes in 438 consecutive patients with UCAO-mediated infarction. Lastly, Mendelian randomization identified a causative role of NOS inhibition, particularly in elevated SDMA concentration, in ischemic stroke risk. Therefore, NOS activity is a key factor determining the fate of hypoperfused brain following acute carotid occlusion, where SDMA could be a potential risk predictor.

neuroscience↗

bioRxiv2024

Modeling gene-environment interactions in Parkinson's Disease: Helicobacter pylori infection of Pink1-/- mice induces CD8 T cell-dependent motor and cognitive dysfunction.

Parkinsons disease (PD) is a chronic neurodegenerative disorder characterized by progressive loss of motor function. Diagnosis occurs late: after motor symptom development downstream of the irreparable loss of a large proportion of the dopaminergic neurons in the substantia nigra of the brain. Understanding PD pathophysiology in its pre-motor prodromal phase is needed for earlier diagnosis and intervention. Genetic risk factors, environmental triggers, and dysregulated immunity have all been implicated in PD development. Here, we demonstrate in a mouse model deficient in the PD-associated gene Pink, that infection with the human PD-associated gastric bacterium Helicobacter pylori leads to development of motor and cognitive signs resembling prodromal features of PD. This was also associated with proliferation and activation of primary mitochondria-reactive CD8 T cells and infiltration of CD8 T cells into the brain. Development of the motor and cognitive phenotypes in the infected Pink1-/- mice was abrogated when CD8 T cells were depleted prior to infection. We anticipate that this new model, which integrates genetic PD susceptibility, a PD-relevant environmental trigger, and specific immune changes that are required for symptom development, will be a valuable tool for increasing our understanding of this complex disease.

immunology↗

bioRxiv2023

Whole-genome sequences reveal zygotic composition in chimeric twins

The monochorionic placenta in dizygotic twins allows in utero exchange of embryonic cells, resulting in chimerism in the twins. In practice, this chimerism is incidentally identified on mixed ABO blood types or in the presence of cells with a discordant sex chromosome. Here, we applied whole-genome sequencing to one triplet and one twin families to precisely understand their zygotic compositions, using millions of genomic variants as barcodes of zygotic origins. Peripheral blood showed asymmetrical contributions from two sister zygotes, where one of the zygotes was the major clone in both twins. Single-cell RNA sequencing of peripheral blood tissues further showed differential contributions from the two sister zygotes across blood cell types. In contrast, buccal tissues were pure in genetic composition, suggesting that in utero cellular exchanges were confined to the blood tissues. Our study illustrates the cellular history of twinning during human development, which is critical for managing the health of chimeric individuals in the era of genomic medicine.

genomics↗

bioRxiv2023

Gut Microbiome Wellness Index 2 for Enhanced Health Status Prediction from Gut Microbiome Taxonomic Profiles

Recent advancements in human gut microbiome research have revealed its crucial role in shaping innovative predictive healthcare applications. We introduce Gut Microbiome Wellness Index 2 (GMWI2), an advanced iteration of our original GMWI prototype, designed as a robust, disease-agnostic health status indicator based on gut microbiome taxonomic profiles. Our analysis involved pooling existing 8069 stool shotgun metagenome data across a global demographic landscape to effectively capture biological signals linking gut taxonomies to health. GMWI2 achieves a cross-validation balanced accuracy of 80% in distinguishing healthy (no disease) from non-healthy (diseased) individuals and surpasses 90% accuracy for samples with higher confidence (i.e., outside the "reject option"). The enhanced classification accuracy of GMWI2 outperforms both the original GMWI model and traditional species-level -diversity indices, suggesting a more reliable tool for differentiating between healthy and non-healthy phenotypes using gut microbiome data. Furthermore, by reevaluating and reinterpreting previously published data, GMWI2 provides fresh insights into the established understanding of how diet, antibiotic exposure, and fecal microbiota transplantation influence gut health. Looking ahead, GMWI2 represents a timely pivotal tool for evaluating health based on an individuals unique gut microbial composition, paving the way for the early screening of adverse gut health shifts. GMWI2 is offered as an open-source command-line tool, ensuring it is both accessible to and adaptable for researchers interested in the translational applications of human gut microbiome science.

bioinformatics↗

bioRxiv2023

Microglial P2Y6 calcium signaling promotes phagocytosis and shapes neuroimmune responses in epileptogenesis

Microglial calcium signaling is rare in a baseline state but shows strong engagement during early epilepsy development. The mechanism and purpose behind microglial calcium signaling is not known. By developing an in vivo UDP fluorescent sensor, GRABUDP1.0, we discovered that UDP release is a conserved response to seizures and excitotoxicity across brain regions. UDP signals to the microglial P2Y6 receptor for broad increases in calcium signaling during epileptogenesis. UDP-P2Y6 signaling is necessary for lysosome upregulation across limbic brain regions and enhances production of pro-inflammatory cytokines--TNF and IL-1{beta}. Failures in lysosome upregulation, observed in P2Y6 KO mice, can also be phenocopied by attenuating microglial calcium signaling in Calcium Extruder ("CalEx") mice. In the hippocampus, only microglia with P2Y6 expression can perform full neuronal engulfment, which substantially reduces CA3 neuron survival and impairs cognition. Our results demonstrate that calcium activity, driven by UDP-P2Y6 signaling, is a signature of phagocytic and pro-inflammatory function in microglia during epileptogenesis.

neuroscience↗