Biology subjects

Kim, K. S.

Publications and source records attributed to Kim, K. S..

At least 19 recordsLinked to original sources

bioRxiv2026

Mesoscale Soft Robotics for Mechanically Perturbing and Functionally Monitoring Responses in Human Organoids

Human organoids represent promising models for studies of significance to the biology and medical communities. Of the existing approaches for monitoring organoids, none offers the ability to apply programmable mechanical forces while simultaneously recording multi-modal physiological responses, of relevance to phenomena spanning from traumatic brain injuries to cardiac rhythm disorders. Here, we present a mesoscale soft robotic organoid interface that enables programmable delivery of forces to organoids of diverse shapes, and to map electrophysiological activity and mechanical responses. The platform combines actuation elements with integrated sensors for quantitative measurement and control. Studies using this technology reveal that spheroidal cortical organoids exhibit distinct responses to mechanical trauma, including silencing, recovery, and changes in neuronal firing patterns. Additional experiments on cardiac ring tissues demonstrate that sustained stretching induces beat-to-beat rhythm variability and altered conduction. The results establish a framework for investigating force-triggered transitions between physiological and disease-like states in human tissue models.

bioengineering↗

bioRxiv2026

Evolution of a large and diverse phospholipase gene cluster that defines the plant pathogenic genus Ceratocystis

Many Ceratocystis species cause cankers and unique vascular wilt diseases, often on a broad and unpredictable range of plant hosts. Characteristic necrosis of xylem parenchyma cells and dark staining of surrounding tissue is typically evident, especially in woody hosts. The molecular basis for this unique pathogenicity and host range remains unclear, but bacterial-type phosphatidylinositol phospholipase C (bPI-PLC) genes were recently identified in unusually high copy number in multiple Ceratocystis species, and the PLCs may play a role in host membrane disruption. We produced a high-quality long-read genome assembly of the rapid [O]hia death pathogen, Ceratocystis lukuohia, and identified 81 partial or complete PLC-like genes, each with a unique DNA sequence, encoding signal peptides and a PLC-X domain. The putative translations mostly ranged from 300 to 500 amino acids that differed markedly from the fungal and prokaryotic bPI-PLCs at sites conferring phosphatidylinositol specificity, suggesting a novel family of secreted PLCs (Cer-PLCs). Remarkably, 73 of the full or partial Cer-PLC genes reside in a single 543 kb gene cluster in C. lukuohia. Comparison to an available long-read genome assembly of C. fimbriata revealed a similar Cer-PLC cluster of 61 genes, with a gene order and arrangement broadly similar to that of the C. lukuohia cluster, except for a large inversion at the beginning of the cluster. Differences suggest that the cluster is dynamic, with many apparent indels involving multiple Cer-PLCs. We compared 40 newly-assembled genomes of Ceratocystis strains and eight publicly available genomes and found that the Cer-PLCs comprise a gene family present in all Ceratocystis species but differing greatly in number (26 to 92), with 64 to 92 in species of the highly aggressive Latin American Clade. The two closest relatives of Ceratocystis have Cer-PLCs but not in the gene cluster: Chalaropsis spp. have only one Cer-PLC, and Berkeleyomyces basicola has 25 related Cer-PLCs scattered across multiple contigs. No Cer-PLC was detected in the more-distant members of the Ceratocystidaceae. The unique cluster in Ceratocystis apparently arose through insertion of Cer-PLCs within an ancestral gene cluster with a CeGAL transcription factor, followed by repeated duplications and rapid diversification of Cer-PLCs, perhaps driven by unequal crossover events. This extraordinary expansion, diversification, and maintenance of Cer-PLCs may have played a major role in the evolution of aggressiveness and host range in Ceratocystis. Impact StatementNew strains of Ceratocystis species with expanding host ranges are emerging as important plant pathogens around the world. However, little is known about the basis for the wide variation in host range and aggressiveness of Ceratocystis species. An earlier study had identified a gene family coding for phosphatidylinositol-specific phospholipase C (PI-PLC) in some Ceratocystis species. Our sequence analyses suggest that the coded enzyme is not likely phosphatidylinositol-specific but may have retained capability of degrading plant membranes and may be a major determinant of aggressiveness and host range. The most aggressive species in the genus has up to 92 copies of this unique class of PLCs, defined here as Cer-PLCs, making the expansion of this gene family among the largest known in fungi. Most of the Cer-PLC genes occur in a gene cluster of more than 500 kb, which appears to be under the control of a CeGAL-type transcription factor. Coordinated regulatory control may enable the hyper-production of these membrane-degrading enzymes during pathogenesis. The Cer-PLC gene family occurs in close relatives of Ceratocystis, but the Cer-PLC gene cluster is unique and universal in Ceratocystis. The gene cluster is the largest known for a single gene family, and it is highly dynamic and likely undergoes frequent recombination. Multiple introductions of strains to a new environment could generate very aggressive recombinants that attack previously unrecognized hosts, as appears to be happening with the multiple introductions of the South American species C. manginecans to Asia.

genomics↗

bioRxiv2026

Modeling framework disentangles cerebellar mechanisms in speech feedback control, revealing trade-offs reshaped by degeneration

A central challenge in systems neuroscience is understanding how computational mechanisms--including those implemented within a single brain region--interact to produce behavior. For example, prior work in the literature attributes many computational functions to the cerebellum, but these functions have been tested in isolation and it remains unclear how they jointly contribute to motor control. Here, we test several established hypotheses of cerebellar function: internal modeling, timing of movement dynamics, sensory-error processing, delay processing, and multimodal integration. We first formalize these functions as mechanistic parameters within a computational model of speech motor control. We then use this formalism to investigate the relative contribution of each function to the abnormal speech corrective response seen in adults with cerebellar degeneration during perturbed auditory feedback. We find the following functions explain most of the behavioral differences: internal modeling, timing of movement dynamics, and multimodal integration. We also show that the key mechanisms have a trade-off relationship, and that cerebellar degeneration modulates those trade-off strengths and boundaries. These results both elaborate the mechanistic function of the cerebellum in speech feedback control and, more broadly, demonstrate the promise of using this paradigm to simultaneously test competing theories of neural function underlying behavior.

neuroscience↗

bioRxiv2026

Implicit visuomotor adaptation to clamped feedback is reduced in adults who stutter

It has been demonstrated that people who stutter exhibit atypical motor control not only in speech tasks but also movements in the non-speech effector system, such as finger or arm motion. Notably, studies have reported that people who stutter show limited sensorimotor adaptation (i.e., updating subsequent movements in response to sensory errors) in both speech auditory-motor (i.e., updating speech movements in response to altered auditory feedback) and upper limb visuo-motor (i.e., updating arm movements in response to altered visual feedback) tasks. Given that speech auditory-motor adaptation is mostly if not entirely implicit (i.e., participants are unaware of the learning), it is thought that people who stutter have limited implicit adaptation in the speech effector system. It remains unclear however, whether such limited implicit learning also extends to upper limb visuomotor adaptation. Here, we examined implicit visuomotor learning in adults who stutter through the means of arm reaching adaptation to clamped visual feedback which provides a cursor that is fixed in direction (8{degrees} counterclockwise from targets) regardless of the participants actual hand location. All participants gradually adjusted their reach angle towards the clockwise direction, adapting in response to clamped feedback, but adults who stutter showed less adaptation compared to adults who do not stutter. In addition, computational modeling suggests that this implicit adaptation difficulties in stuttering individuals may reflect reduced error sensitivity. Together, our findings suggest that implicit sensorimotor learning difficulties in adults who stutter may generalize across multiple effector systems, providing important implications for understanding sensorimotor mechanisms underlying stuttering. Significance statementBy employing the clamped visual feedback paradigm during arm reaching movements, we demonstrated that adults who stutter showed less implicit visuomotor adaptation compared to adults who do not stutter. This study provides the first evidence that implicit sensorimotor adaptation limitations in developmental stuttering generalize across multiple effector systems. Our findings not only add to a growing body of evidence that stuttering is associated with domain-general sensorimotor difficulties but also point to specific underlying processes that may lead to stuttering.

neuroscience↗

bioRxiv2026

Dual Oxygen-Partitioned Co-Culture Uncovers Microbe-Specific Epithelial Stress and Homeostatic Programs

Direct epithelial-microbial interactions occur across a steep aerobic-anaerobic interface in the intestine, yet mechanistic analysis has been limited by the difficulty of sustaining oxygen-dependent epithelial cells together with strictly anaerobic microbes in vitro. Here, we establish a dual oxygen-partitioned co-culture system that reproducibly maintains aerobic intestinal epithelial cells and obligate anaerobic gut bacteria, enabling controlled analysis of epithelial responses under physiologically relevant oxygen architecture. Using Mediterraneibacter gnavus and Lacticaseibacillus casei as contrasting microbial partners, we identify distinct epithelial programs. M. gnavus induces epithelial stress characterized by tight-junction disruption, suppression of mitochondrial respiration, and activation of chromatin-associated and innate immune regulatory pathways, whereas L. casei preserves barrier integrity and supports mitochondrial capacity with restrained immune modulation. Integrated transcriptomic and proteomic analyses reveal a shared epithelial energy-conserving response to microbial proximity, upon which microbe-specific stress or homeostatic programs are imposed. In vivo analysis using a dextran sodium sulfate-induced colitis model demonstrates that these epithelial programs become physiologically relevant under inflammatory conditions, with L. casei promoting epithelial repair and immune rebalancing. Together, these findings define oxygen-partitioned epithelial-microbial interactions as a determinant of microbe-specific epithelial states.

microbiology↗

bioRxiv2025

ETV4 restrains the formation of CD74+ cytotoxic exhausted CD8+ T cells

Exhausted CD8+ T (Tex) cells comprise heterogeneous subsets with varying cytotoxic and dysfunctional properties, making inhibitory receptor profiles unreliable indicators of function. Therefore, it is essential to define transcriptional regulators or markers that accurately reflect these states. Here, we identified ETS variant 4 (ETV4) as a transcription factor that restricts cytotoxic Tex differentiation within tumors. ETV4 deficiency promotes the emergence of a CD74+ cytotoxic Tex subset while preserving the progenitor Tex (Tpex) pool. CD74 serves as both a marker and regulator, reinforcing Tpex features and enhancing Tex cytotoxicity. Mechanistically, ETV4 loss derepresses T-bet expression, thereby increasing IFN{gamma} production that induces CD74 expression in a paracrine manner. Single-cell analyses across human cancers revealed that CD74+ Tex cells are enriched for proliferative and metabolic programs and correlate with improved survival. Collectively, we establish the ETV4-CD74 axis as a regulator of Tex fate and promising therapeutic target to augment anti-tumor immunity.

immunology↗

bioRxiv2025

Mechanical environment afforded by engineered polymer hydrogel critically regulates survival of neural stem cells transplanted in the injured spinal cord via Piezo1-mediated mechanotransduction

Neural stem cell (NSC) transplantation is a promising therapeutic approach for spinal cord repair, but poor graft survival remains a critical challenge. Here, we demonstrate that the mechanical properties of the transplantation microenvironment play a crucial role in NSC survival in the injured spinal cord. While our previously engineered imidazole-poly(organophosphazene) (I-5) hydrogel effectively prevented cavity formation by promoting extracellular matrix remodeling, NSCs transplanted with 10% hydrogel exhibited poor survival. Remarkably, increasing the hydrogel concentration to 16%, which created a 5-fold stiffer matrix, significantly enhanced NSC graft survival and synaptic integration. Using in vitro models with controlled substrate stiffness, we found that NSCs on stiffer substrates displayed enhanced adhesion, complex morphology, and increased viability. Importantly, we identified the mechanosensitive ion channel Piezo1 as the key molecular mediator of these stiffness-dependent behaviors. CRISPR/Cas9-mediated Piezo1 gene editing in NSCs significantly reduced graft survival in vivo when transplanted with 16% hydrogel, confirming that Piezo1-mediated mechanotransduction is essential for NSC survival in the injured spinal cord. Our findings reveal a previously unrecognized mechanism governing graft survival in the injured spinal cord and suggest that optimizing the mechanical properties of biomaterial scaffolds or targeting Piezo1-dependent mechanotransduction could substantially improve outcomes of cell-based therapies for neurological disorders.

neuroscience↗

bioRxiv2025

Evaluating the impact of NPC1 SNPs on entry efficiency of Filovirus in vitro: agent-based model approach

The interaction between the Niemann-Pick C1 (NPC1) protein and the glycoprotein (GP) of filoviruses is essential for viral entry into host cells. Single nucleotide polymorphisms (SNPs) in NPC1, which lead to amino acid substitutions, can significantly alter viral entry efficiency. However, the quantitative impact of these SNPs remains unclear. To address this, we investigate in vitro cell-to-cell infection using a plaque assay with vesicular stomatitis virus (VSV) expressing Ebola and Marburg GP. We employe an agent-based model (ABM) to estimate entry efficiency by simulating plaque growth, enabling a comparative analysis of SNP-specific effects on viral entry. Our quantitative analysis reveals that D508N, P424A, and S425L substitutions in NPC1 reduce entry efficiency in both viruses. These findings provide insights into host-pathogen interactions and demonstrate the value of ABM in virology research, potentially guiding therapeutic strategies targeting viral entry mechanisms. Author summaryEbola and Marburg viruses are highly pathogenic filoviruses that cause severe hemorrhagic fever in humans, with case fatality rates reaching around 50%. These viruses pose significant public health challenges due to their potential for large-scale outbreaks. A key step in their infection process is the interaction between the Niemann-Pick C1 (NPC1) protein on host cells and the viral glycoprotein, which facilitates viral entry. Genetic variations in NPC1 caused by single nucleotide polymorphisms (SNPs) can lead to amino acid substitutions, potentially altering the efficiency of viral entry. To better understand this process, we developed an agent-based model, a computational approach that simulates individual cell interactions and provides spatial resolution not achievable with traditional modeling techniques, to simulate viral plaque growth in vitro. By applying this model, we quantified how specific NPC1 substitutions, such as D508N, P424A, and S425L, affect the entry efficiency of Ebola and Marburg viruses. Our findings highlight the potential of computational modeling to uncover the impact of genetic variations on viral infections and provide insights that may inform therapeutic strategies against these deadly viruses.

systems biology↗

bioRxiv2025

Longitudinal analysis of antibody titers after primary and booster mRNA COVID-19 vaccination can identify individuals at risk for breakthrough infection

A key issue in the post-COVID-19 era is the ongoing administration of COVID-19 vaccines. Repeated vaccination is essential for preparing against currently circulating and newly emerging SARS-CoV-2 variants while enabling people to continue with daily life. Optimizing vaccination strategies is crucial to efficiently manage medical resources and establish an effective vaccination framework. Therefore, it is important to quantitatively understand vaccine-induced immunity dynamics and to be able to identify poor responders with lower sustained antibody titers as potential priorities for revaccination. We investigated longitudinal antibody titer data in a cohort of 2,526 people in Fukushima, Japan, from April 2021 to November 2022 for whom basic demographic and health information was available. Using mathematical modeling and machine learning, we stratified the time-course patterns of antibody titers after 2 primary doses and 1 booster dose of mRNA COVID-19 vaccines. We identified 3 notable populations, which we refer to as the durable, the vulnerable, and the rapid-decliner populations, approximately half of which remained in the same population after the booster dose. Notably, the rapid-decliner population experienced earlier infections than the others. Furthermore, when comparing IgG(S) titers, IgA(S) titers, and T-spot counts between participants who experienced breakthrough infections after booster vaccination and those who did not, we found that IgA(S) titers were significantly lower in breakthrough infected participants during the early stage after booster vaccination. Our computational approach is adaptable to various types of vaccinations. This flexibility can inform policy decisions on vaccine distribution to enhance immunity both in future pandemics and in the post-COVID-19 era.

immunology↗

bioRxiv2025

3D markerless tracking of speech movements with submillimeter accuracy

Speech movements are highly complex and require precise tuning of both spatial and timing of oral articulators to support intelligible communication. These properties also make measurement of speech movements challenging, often requiring extensive physical sensors placed around the mouth and face that are not easily tolerated by certain populations such as young children. Recent progress in machine learning-based markerless facial landmark tracking technology demonstrated its potential to provide lip tracking without the need for physical sensors, but whether such technology can provide submillimeter precision and accuracy in 3D remains unknown. Moreover, it is also unclear whether such technology can be applied to track speech movements in young children. Here, we developed a novel approach that integrates Shape Preserving Facial Landmarks with Graph Attention Networks (SPIGA), a facial landmark detector, and CoTracker, a transformer-based neural network model that jointly tracks dense points across a video sequence. We further examined and validated this novel approach by assessing its tracking precision and accuracy. The findings revealed that our approach that integrates SPIGA and CoTracker was more precise ({approx} 0.15 mm in standard deviation) than SPIGA alone ({approx} 0.35 mm). In addition, its 3D tracking performance was comparable to electromagnetic articulography ({approx} 0.29 mm RMSE against simultaneously recorded articulograph data). Importantly, the approach performed similarly well across adults and young children (i.e., 3- and 4-year-olds). Because our framework is built upon open-source pretrained models that are fully trained, it promotes accessibility and open science while saving computing resources. Furthermore, given that this framework combines a landmark detection model (SPIGA) with a tracker model (CoTracker) to improve precision/accuracy, our novel approach serves as a proof-of-concept for enhancing the performance of a wide variety of commonly used markerless tracking applications in biology and neuroscience. Author summaryIn this work, we examined whether machine learning based markerless tracking is feasible for tracking 3D lip movements in adults and young children. We developed a novel approach that integrates a landmark detection model (SPIGA) with a tracker model (CoTracker). Our combined CoTracker-based approach demonstrated submillimeter precision and accuracy desired for speech kinematic recording. In addition, our approach does not involve training and validation for each population (e.g., young children vs. adults), saving time and computing resources. We foresee that the proposed general framework of fusing a landmark detection model with a tracker model can be generalized for a wide variety of tracking applications in biology and neuroscience that require high precision and accuracy, including studying cell behaviors, animal motions, and other types of human movements.

neuroscience↗

bioRxiv2024

Does pre-speech auditory modulation reflect processes related to feedback monitoring or speech movement planning?

Previous studies have revealed that auditory processing is modulated during the planning phase immediately prior to speech onset. To date, the functional relevance of this pre-speech auditory modulation (PSAM) remains unknown. Here, we investigated whether PSAM reflects neuronal processes that are associated with preparing auditory cortex for optimized feedback monitoring as reflected in online speech corrections. Combining electroencephalographic PSAM data from a previous data set with new acoustic measures of the same participants speech, we asked whether individual speakers extent of PSAM is correlated with the implementation of within-vowel articulatory adjustments during /b/-vowel-/d/ word productions. Online articulatory adjustments were quantified as the extent of change in inter-trial formant variability from vowel onset to vowel midpoint (a phenomenon known as centering). This approach allowed us to also consider inter-trial variability in formant production and its possible relation to PSAM at vowel onset and midpoint separately. Results showed that inter-trial formant variability was significantly smaller at vowel midpoint than at vowel onset. PSAM was not significantly correlated with this amount of change in variability as an index of within-vowel adjustments. Surprisingly, PSAM was negatively correlated with inter-trial formant variability not only in the middle but also at the very onset of the vowels. Thus, speakers with more PSAM produced formants that were already less variable at vowel onset. Findings suggest that PSAM may reflect processes that influence speech acoustics as early as vowel onset and, thus, that are directly involved in motor command preparation (feedforward control) rather than output monitoring (feedback control).

neuroscience↗

bioRxiv2024

Bayesian inference of state feedback control parameters for fo perturbation responses in cerebellar ataxia

Behavioral speech tasks have been widely used to understand the mechanisms of speech motor control in healthy speakers as well as in various clinical populations. However, determining which neural functions differ between healthy speakers and clinical populations based on behavioral data alone is difficult because multiple mechanisms may lead to the same behavioral differences. For example, individuals with cerebellar ataxia (CA) produce abnormally large compensatory responses to pitch perturbations in their auditory feedback, compared to controls, but this pattern could have many explanations. Here, computational modeling techniques were used to address this challenge. Bayesian inference was used to fit a state feedback control (SFC) model of voice fundamental frequency (fo) control to the behavioral pitch perturbation responses of individuals with CA and healthy controls. This fitting process resulted in estimates of posterior likelihood distributions of five model parameters (sensory feedback delays, absolute and relative levels of auditory and somatosensory feedback noise, and controller gain), which were compared between the two groups. Results suggest that the CA group may proportionally weight auditory and somatosensory feedback differently from the control group. Specifically, the CA group showed a greater relative sensitivity to auditory feedback than the control group. There were also large group differences in the controller gain parameter, suggesting increased motor output responses to target errors in the CA group. These modeling results generate hypotheses about how CA may affect the speech motor system, which could help guide future empirical investigations in CA. This study also demonstrates the overall proof-of-principle of using this Bayesian inference approach to understand behavioral speech data in terms of interpretable parameters of speech motor control models. Author summaryCerebellar ataxia is a condition characterized by a loss of coordination in the control of muscle movements, including those required for speech, due to damage in the cerebellar region of the brain. Behavioral speech experiments have been used to understand this disorders impact on speech motor control, but the results can be ambiguous to interpret. In this study, we fit a computational model of the neural speech motor control system to the speech data of individuals with cerebellar ataxia and that of healthy controls to determine what differences in model parameters best explain how the two groups differ in their control of vocal pitch. We found that group differences may be explained by increased sensitivity to auditory feedback prediction errors (differences between the actual sound speakers hear of their own speech as they produce it and the sound they expected to hear) and increased motor response in individuals with cerebellar ataxia. These computational results help us understand how cerebellar ataxia impacts speech motor control, and this general approach can also be applied to study other neurological speech disorders.

neuroscience↗

bioRxiv2023

Neurophysiological evidence of sensory prediction errors driving speech sensorimotor adaptation

The human sensorimotor system has a remarkable ability to quickly and efficiently learn movements from sensory experience. A prominent example is sensorimotor adaptation, learning that characterizes the sensorimotor systems response to persistent sensory errors by adjusting future movements to compensate for those errors. Despite being essential for maintaining and fine-tuning motor control, mechanisms underlying sensorimotor adaptation remain unclear. A component of sensorimotor adaptation is implicit (i.e., the learner is unaware of the learning process) which has been suggested to result from sensory prediction errors-the discrepancies between predicted sensory consequences of motor commands and actual sensory feedback. However, to date no direct neurophysiological evidence that sensory prediction errors drive adaptation has been demonstrated. Here, we examined prediction errors via magnetoencephalography (MEG) imaging of the auditory cortex (n = 34) during sensorimotor adaptation of speech to altered auditory feedback, an entirely implicit adaptation task. Specifically, we measured how speaking-induced suppression (SIS)--a neural representation of auditory prediction errors--changed over the trials of the adaptation experiment. SIS refers to the suppression of auditory cortical response to speech onset (in particular, the M100 response) to self-produced speech when compared to the response to passive listening to identical playback of that speech. SIS was reduced (reflecting larger prediction errors) during the early learning phase compared to the initial unaltered feedback phase. Furthermore, reduction in SIS positively correlated with behavioral adaptation extents, suggesting that larger prediction errors were associated with more learning. In contrast, such a reduction in SIS was not found in a control experiment in which participants heard unaltered feedback and thus did not adapt. In addition, in some participants who reached a plateau in the late learning phase, SIS increased (reflecting smaller prediction errors), demonstrating that prediction errors were minimal when there was no further adaptation. Together, these findings provide the first neurophysiological evidence for the hypothesis that prediction errors drive human sensorimotor adaptation.

neuroscience↗

bioRxiv2023

A Normative Framework Dissociates Need and Motivation in Hypothalamic Neurons

Physiological needs evoke motivational drives to produce natural behaviours for survival. However, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components in previous experimental paradigms. Based on classic homeostatic theories, we established a normative framework to derive computational models of neural activity and behaviours for need-encoding and motivation-encoding neurons during events that induce predicted gain or loss. We further developed simple and intuitive experimental paradigms that enabled us to distinguish the distinct roles of subpopulations of neurons in the hypothalamus. Our results show that AgRP neurons and LHLepR neurons are consistent with need and motivation, respectively. Our study provides a parsimonious understanding of how distinct hypothalamic neurons separately encode need and motivation to produce adaptive behaviours for maintaining homeostasis.

neuroscience↗

bioRxiv2023

Virtual biomarkers: predicting immune status using label-free holotomography of individual human monocytes and machine learning analysis

Precise evaluation of immune status is critical for managing diseases such as sepsis, in which the immune system transitions between hyper-inflammatory and immune-suppressed states. However, current biomarkers are limited by low specificity and time-consuming protocols. Here, we present a label-free, imaging-based framework for single-cell immune profiling of human monocytes using three-dimensional holotomography (HT) and deep learning. HT captures subcellular refractive index (RI) distributions of live, unlabeled cells, enabling quantitative extraction of morphological and biophysical features. Using an in vitro LPS-based model, we classified three functional immune states--control, hyper-inflammation, and immune suppression--based on 4,059 holotomograms from 11 donors. Immune state transitions were associated with significant changes in cell volume, surface area, RI variability, and the abundance of lipid droplets. A 3D convolutional neural network trained on HT images achieved 83.7% accuracy for single-cell predictions, increasing to 99.9% with ensemble averaging. This study establishes HT as a scalable, label-free platform for real-time immune monitoring and introduces subcellular RI features as robust correlates of immune dysregulation.

immunology↗

bioRxiv2023

Isolation may select for earlier and higher peak viral load but shorter duration in SARS-CoV-2 evolution

During the COVID-19 pandemic, human behavior change as a result of nonpharmaceutical interventions such as isolation may have induced directional selection for viral evolution. By combining previously published empirical clinical data analysis and multi-level mathematical modeling, we found that the SARS-CoV-2 variants selected for as the virus evolved from the pre-Alpha to the Delta variant had earlier and higher infectious periods but a shorter duration of infection. Selection for increased transmissibility shapes the viral load dynamics, and the isolation measure is likely to be a driver of these evolutionary transitions. In addition, we showed that a decreased incubation period and an increased proportion of asymptomatic infection were also positively selected for as SARS-CoV-2 mutated to the extent that people did not isolate. We demonstrated that the Omicron variants evolved in these ways to adapt to human behavior. The quantitative information and predictions we present here can guide future responses in the potential arms race between pandemic interventions and viral evolution.

evolutionary biology↗

bioRxiv2022

Prediction of elimination of intrahepatic cccDNA in hepatitis B virus-infected patients by a combination of noninvasive viral markers

Evaluation of intrahepatic covalently closed circular DNA (cccDNA) is a key for searching an elimination of hepatitis B virus (HBV) infection. HBV RNA and HBV core-related antigen have been proposed as surrogate markers for evaluating cccDNA activity, although they do not necessarily estimate the amount of cccDNA. Here, we developed a novel multiscale mathematical model describing intra- and inter-cellular viral propagation, based on the experimental quantification data in both HBV-infected cell culture and humanized mouse models. We applied it to HBV-infected patients under treatment and developed a model which can predict intracellular HBV dynamics only by use of noninvasive extracellular surrogate biomarkers. Importantly, the model prediction of the amount of cccDNA in patients over time was confirmed to be well-correlated with the liver biopsy data. Thus, our noninvasive method enables to predict the amount of cccDNA in patients and contributes to determining the treatment endpoint required for elimination of intrahepatic cccDNA.

microbiology↗

bioRxiv2022

Potential anti-monkeypox virus activity of atovaquone, mefloquine, and molnupiravir, and their potential use as treatments

Monkeypox virus (MPXV) is a zoonotic orthopoxvirus that causes smallpox-like symptoms in humans and caused an outbreak in May 2022 that led the WHO to declare global health emergency. In this study, from a screening of approved-drug libraries using an MPXV infection cell system, atovaquone, mefloquine, and molnupiravir exhibited anti-MPXV activity, with 50% inhibitory concentrations of 0.51-5.2 M, which is more potent than cidofovir. Whereas mefloquine was suggested to inhibit viral entry, atovaquone and molnupiravir targeted post-entry process to impair intracellular virion accumulation. Inhibitors of dihydroorotate dehydrogenase, an atovaquones target enzyme, showed conserved anti-MPXV activities. Combining atovaquone with tecovirimat enhanced the anti-MPXV effect of tecovirimat. Quantitative mathematical simulations predicted that atovaquone can promote viral clearance in patients by seven days at clinically relevant drug concentrations. Moreover, atovaquone and molnupiravir exhibited pan-Orthopoxvirus activity against vaccinia and cowpox viruses. These data suggest that atovaquone would be potential candidates for treating monkeypox.

microbiology↗