Biology subjects

Kotani, H.

Publications and source records attributed to Kotani, H..

12 recordsLinked to original sources

bioRxiv2026

Rapid enhancement of antibiotic resistance and divergent remodeling of gene expression in single cells of bacteria

Exposing bacterial cell populations to antibiotics often results in the emergence of descendants with enhanced resistance. Phenotypic heterogeneity and global physiological responses are thought to contribute to resistance evolution. However, identifying the specific stages of drug exposure where phenotypic heterogeneity and physiological responses play critical roles remains elusive. Using long-term single-cell lineage tracking of an Escherichia coli resistance model, here we reveal that resistance-enhanced cells emerge rapidly within a few generations in a clonal bacterial cell population under chloramphenicol (Cp) exposure and stably transmit the enhanced resistance for hundreds of generations in the presence of Cp. High expression of a resistance protein was advantageous during the initial period of drug exposure, but conferred only a marginal fitness advantage during the period of resistance enhancement. Transcriptomic profiles of resistance-enhanced cell populations were lineage-specific, suggesting that multiple gene expression states can support enhanced resistance. Altogether, these results suggest that an interplay between initial phenotypic heterogeneity and divergent remodeling of gene expression drives the rapid acquisition of enhanced antibiotic resistance.

microbiology↗

bioRxiv2026

Closed-loop steering locates an evolutionary barrier to multidrug resistance in Escherichia coli

Resistance to one drug often raises susceptibility to another; such collateral sensitivity is expected to constrain multidrug resistance. This is hard to test: failure to reach a state is indistinguishable from never having been driven toward it. We therefore recorded the change we imposed: a closed-loop system updated each lineage's drug environment daily based on its measured distance to a target. Steered toward triple chloramphenicol-norfloxacin-kanamycin resistance for 70 days, 52 Escherichia coli lineages gained substantial resistance without converging on the target. The mismatch between imposed and observed movement mapped accessibility, locating a region immediately before the target where progress was reproducibly slowed. Crossing it was associated not with broad resistance mutations shared by most lineages, but with recurrent mutations upstream of the efflux pump gene cmr, which raised chloramphenicol resistance threefold without detectable cost. Progression toward multidrug resistance was therefore constrained without being prevented, at a location consistent with a known physiological trade-off; recording the imposed change makes accessibility measurable during evolution.

evolutionary biology↗

bioRxiv2026

Attenuated adaptive growth of interpersonal synchrony in autism

During social interactions, people continuously align their movements and rhythms, a process known as interpersonal synchrony that supports rapport, mutual understanding, and smooth communication. In autism spectrum disorder (ASD), previous studies have often reported atypical or reduced synchrony, but most have relied on aggregate or session-averaged measures that may miss how coordination develops over time. It therefore remains unclear whether interactional differences in autism reflect a general reduction in synchrony or altered temporal dynamics of interpersonal coordination. We examined the temporal dynamics of head-movement synchrony during a structured face-to-face communication task, comparing non-autistic dyads (two typically developing [TD] partners) with mixed-neurotype dyads (one TD speaker paired with one autistic listener), using gyroscope-based tracking and time-resolved trajectory modelling. Phase-based synchrony, indexed by the phase-locking value (PLV), was lower overall in mixed-neurotype dyads. Critically, time-resolved analyses revealed a marked group difference in synchrony trajectories: non-autistic dyads showed progressive, adaptive growth in synchrony over the interaction, whereas mixed-neurotype dyads showed a significantly attenuated, flatter pattern. These findings suggest that autism may involve altered temporal organization of social coordination rather than simply reduced synchrony overall. Lay AbstractWhen we talk with someone, we often naturally match their body language and rhythms without even realizing it. This physical "syncing up" helps us feel connected, builds trust and shared understanding, and makes communication flow easily. Research shows that autistic people might sync their movements differently during conversations compared to non-autistic people. However, past studies usually just measured an overall average of this syncing across a whole interaction. This approach misses how human interactions actually unfold over time. We wanted to know: do autistic people just sync less overall, or does their syncing change differently as the conversation goes on? To find out, we used small motion sensors to track the head movements of adults having structured face-to-face conversations and compared two types of pairs: non-autistic pairs, where both people were non-autistic, and mixed-neurotype pairs, where one non-autistic speaker talked to one autistic listener. We found a notable difference in how the two groups interacted over time. For the non-autistic pairs, the physical syncing grew progressively stronger as the conversation progressed; they progressively "tuned in" to each other. In contrast, mixed-neurotype pairs showed a flatter pattern--their level of syncing stayed relatively constant from start to finish without that same gradual build-up. These findings are important because they suggest that differences in autistic communication are not simply a "lack" or "deficit" in social coordination. Instead, autistic individuals have a distinct style of interacting--one that maintains social engagement without relying on the progressive build-up of physical syncing that non-autistic people use. Taken together, our results highlight the importance of examining how interactions evolve over time to better understand the different ways autistic and non-autistic people communicate.

neuroscience↗

bioRxiv2026

MDA5 multimerization on LINE RNA drives pathogenic extracellular immune complexes in autoimmunity

Autoantibodies are hallmarks of many autoimmune diseases, but their potential pathogenic roles, particularly for those targeting intracellular proteins, remain unclear. Anti-MDA5-positive dermatomyositis (anti-MDA5 DM) is characterized by autoantibodies against the intracellular protein MDA51,2, a conserved innate immune receptor that recognizes viral dsRNA by forming filaments3. Here, using four patient-derived monoclonal autoantibodies (mAbs), we reconstitute and define the molecular architecture, biogenesis, and immunological activity of pathogenic MDA5 immune complexes. Our cryo-EM analysis revealed that these mAbs bind dsRNA-scaffolded MDA5 filaments in at least two distinct binding modes, each exhibiting striking epitope convergence using germline-encoded residues. Extracellular immune complexes formed between mAbs and filamentous, but not monomeric, MDA5 potently activate multiple innate immune pathways, with the magnitude of activation determined by antibody binding mode and immune complex stoichiometry. Antibody bivalency further crosslinks MDA5 filaments into higher-order aggregates with heightened immunostimulatory activity, demonstrating an active role of autoantibodies in shaping immune complex architecture. Analysis of patient plasma reveals elevated levels of extracellular MDA5 filaments and identifies LINE retroelement-derived dsRNA as a structural scaffold. Notably, MDA5 immune complexes induce endogenous LINE dsRNA expression, likely promoting additional MDA5 filament formation and extracellular release through inflammatory cell death. These data thus support a self-amplifying inflammatory cycle as a pathogenic mechanism for anti-MDA5 DM. Collectively, our study defines a broadly applicable architectural principle, in which higher-order organization and binding modes of autoantibodies--beyond antibody affinity or nucleic acid presence alone--govern innate immune activation.

biochemistry↗

bioRxiv2025

Context-dependent activation and evolutionary buffering of a mating pheromone in fission yeast

The evolution of mating signals drives reproductive isolation and speciation across diverse lineages. However, how short peptide pheromones, typically subject to strong structural constraints, achieve functional diversification remain unclear. In the fission yeast Schizosaccharomyces pombe, a previously established library of 153 single-amino acid variants of the mating pheromone M-factor was applied to large-scale competition assays under varied mating conditions. Mutations deleterious under standard conditions became advantageous at specific environmental pH levels, demonstrating context-dependent pheromone function activation. Synthetic peptide assays confirmed that certain substitutions act as environmental molecular switches. Comparative analysis with the closely related Schizosaccharomyces octosporus species identified a permissive mutation that mitigates the effects of otherwise inactivating changes, enabling an evolutionary route without intermediate fitness loss. Our findings reveal how short peptide signals evolve via environmentally contingent activation and compensatory interactions, offering a mechanistic framework for understanding the ecological and evolutionary dynamics of mating communication.

evolutionary biology↗

bioRxiv2025

The Th1/Th17 axis regulates chimeric antigen receptor (CAR) T cell therapy toxicities

CAR-T therapy has led to significant improvements in patient survival. However, a subset of patients experience high-grade toxicities, including cytokine release syndrome (CRS) and immune cell-associated hematologic toxicity (ICAHT). We utilized IL-2R knockout mice to model cytokine toxicities with elevated levels of IL6, IFN{gamma}, and TNF and increased M1-like macrophages. Onset of CRS was accompanied by a reduction in peripheral blood neutrophils due to disruption of bone marrow neutrophil homeostasis characterized by an increase in apoptotic neutrophils and a decrease in proliferative and mature neutrophils. Both non-tumor-bearing and E-ALL tumor-bearing mice recapitulated the co-occurrence of CRS and neutropenia. IFN{gamma}-blockade alleviated CRS and neutropenia without affecting CAR-T efficacy. Mechanistically, a Th1-Th17 imbalance was observed to drive co-occurrence of CRS and neutropenia in an IFN{gamma}-dependent manner leading to decreased IL-17A and G-CSF, neutrophil production, and neutrophil survival. In patients, we observed an increase in the IFN{gamma}-to-IL-17A ratio in the peripheral blood during high-grade CRS and neutropenia. We have uncovered a biological basis for ICAHT and provide support for the use of IFN{gamma}-blockade to reduce CRS and neutropenia. Statement of SignificanceDespite clinical success of CAR-T therapy, patients develop toxicities such as cytokine release syndrome and neutropenia, whose co-occurrence impacts their survival and quality-of-life. We recapitulate these toxicities in mice to discover their co-occurrence is driven by Th1-Th17 imbalance following CAR-T administration, which can be prevented via IFN{gamma} blockade.

cancer biology↗

bioRxiv2023

Non-monotonic Relationship between Mutation Rate and Speed of adaptation under Antibiotic Exposure in Escherichia coli

The mutation is a fundamental source of biological evolution that create genetic variation in populations. Mutations can create new advantageous traits, but also potentially interfere with pre-existing organismal functions. Therefore, organisms may have evolved their mutation rates to appropriate levels to maintain or improve their fitness. In this study, we aimed to experimentally quantify the relationship between mutation rate and the speed of antibiotic resistance evolution. We conducted experimental evolution using twelve Escherichia coli mutator strains with increased mutation rates and five antibiotics. Our results showed that the highest mutation rate did not necessarily lead to the highest speed of adaptation, indicating a non-monotonic relationship between the speed of drug resistance evolution and mutation rate as expected. Moreover, this relationship was observed to differ among drugs, with significant differences in peak size observed between bacteriostatic and bactericidal antibiotics. We also successfully reproduced the mutation-rate dependence of the speed of adaptation using numerical simulation of a population dynamics model. These findings offer significant insights into the mutation rates evolution concomitant with the development of antibiotic resistance.

evolutionary biology↗

bioRxiv2022

Multi-dimensional antibiotic resistance time series reveals the phenotype-based fitness landscape for Escherichia coli

The fitness landscape represents the complex relationship between genotype or phenotype and fitness under a given environment, the structure of which allows the explanation and prediction of evolutionary trajectories. Although previous studies have constructed fitness landscapes based on comprehensively studying the mutations in specific genes, the high dimensionality of genotypic changes prevents us from developing a fitness landscape capable of predicting evolution for the whole cell. Herein, we address this problem by inferring the fitness landscape for antibiotic resistance evolution by quantifying the phenotypic changes, that is, multi-dimensional time-series measurements of the drug resistance profile. Using the time-series data of drug resistance for multiple drugs, we inferred that the fitness landscape underlies the evolution dynamics of resistance. We showed that different peaks of the landscape correspond to different drug resistance mechanisms, thus supporting the validity of the inferred fitness landscape. We further discuss how inferred phenotype-fitness landscapes could contribute to the prediction and control of evolution. This approach bridges the gap between phenotypic/genotypic changes and fitness while contributing to a better understanding of drug resistance evolution.

evolutionary biology↗

bioRxiv2022

Purifying selection enduringly acts on the sequence evolution of highly expressed proteins in Escherichia coli

The evolutionary speed of a protein sequence is constrained by its expression level, with highly expressed proteins evolving relatively slowly. This negative correlation between expression levels and evolutionary rates (known as the E-R anticorrelation) has already been widely observed in past macroevolution between species from bacteria to animals. However, it remains unclear whether this seemingly general law also governs recent evolution, including past and de novo, within a species. However, the advent of genomic sequencing and high-throughput phenotyping, particularly for bacteria, has revealed fundamental gaps between the two evolutionary processes and has provided empirical data opposing the possible underlying mechanisms which are widely believed. These conflicts raise questions about the generalization of the E-R anticorrelation and the relevance of plausible mechanisms. To explore the ubiquitous impact of expression level on molecular evolution, and to test the relevance of the possible underlying mechanisms, we analyzed the genome sequences of 99 strains of Escherichia coli for microevolution in nature. We also analyzed genomic mutations accumulated under laboratory conditions as a model of de novo microevolution. Here, we show that the E-R anticorrelation is significant in both past and de novo microevolution in E. coli. Our data also confirmed ongoing purifying selection acting on highly expressed genes. Ongoing selection included codon-level purifying selection, supporting the relevance of the underlying mechanisms. However, their contributions to the constraints in recent evolution might be smaller than previously expected from past macroevolution.

evolutionary biology↗

bioRxiv2020

Circumstances and factors of sleep-related sudden infant deaths in Japan

Background Sudden unexpected death in infancy (SUDI) comprises both natural and unnatural causes of death. However, a few epidemiological surveys have investigated SUDI in Japan.Objective This retrospective study was conducted to investigate the recent trends of circumstances and risk factors of sleep-related SUDI cases.Methods Forensic pathology sections from eight universities participated in the selection of subjects from 2013 to 2018. Data obtained from the checklist form were analyzed based on information at postmortem.Results There were 259 SUDI cases consisting of 145 male infants and 114 female infants with a mean birth weight of 2888 ± 553 and 2750 ± 370 g, respectively. Deaths most frequently occurred among infants at 1 month of age (18%). According to population-based analyses, the odds ratio (95% confidence interval) of mother’s age ≤19 years was 11.1 (6.9–17.7) compared with ages 30–39. The odds ratio for the fourth- and later born infants was 5.2 (3.4–7.9) compared with the frequency of first-born infants. The most frequent time of day for discovery was between 7 and 8 o’clock. Co-sleeping was recorded for 61%, and the prone position was found for 40% of cases at discovery. Mother’s smoking habit exhibited an adds ratio of 4.5 (2.9–5.8).Conclusion This study confirmed the trends that have been observed for sudden infant death syndrome; particularly, very high odds ratios were evident for teenage mothers and later birth order in comparison with those in other developed countries. The child of a young mother tended to die within 2 months of age. To our knowledge, this is the first report of an extensive survey of sleep-related SUDI in Japan.View Full Text

pathology↗

bioRxiv2020

High-throughput laboratory evolution and evolutionary constraints in Escherichia coli

Understanding the constraints that shape the evolution of antibiotic resistance is critical for predicting and controlling drug resistance. Despite its importance, however, a systematic investigation for evolutionary constraints is lacking. Here, we performed a high-throughput laboratory evolution of Escherichia coli under the addition of 95 antibacterial chemicals and quantified the transcriptome, resistance, and genomic profiles for the evolved strains. Using interpretable machine learning techniques, we analyzed the phenotype-genotype data and identified low dimensional phenotypic states among the evolved strains. Further analysis revealed the underlying biological processes responsible for these distinct states, leading to the identification of novel trade-off relationships associated with drug resistance. We also report a novel constraint that leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space and lead to a better understanding of evolutionary constraints for antibiotic resistance.

evolutionary biology↗

bioRxiv2017

High-Throughput Laboratory Evolution Of Escherichia coli Under Multiple Stress Environments

Bacterial cells have a remarkable capacity to adapt and to evolve to environmental changes. Although many mutations contributing to adaptive evolution have been identified, the relationship between the mutations and the phenotypic changes responsible for fitness gain has yet to be fully elucidated. For a better understanding of phenotype-genotype relationship in evolutionary dynamics, we performed high-throughput laboratory evolution of Escherichia coli under various stress conditions using an automated culture system. One measure of phenotype, transcriptome analysis, revealed that the expression changes which occurred during the evolution were generally similar among the strains evolved in the same stress environment. We also found several genes and gene functions for which mutations were commonly fixed in the strains resistant to the same stress, and whose effects on resistance were verified experimentally. We demonstrated that the integration of transcriptome and genome data enables us to extract the mechanisms for stress resistance.\n\nAuthor summaryUnderstanding the relationship between phenotypic and genetic changes is a fundamental goal in evolutionary biology, which can provide insights into the past and future evolutionary trajectories. Evolution of microorganisms in a laboratory has been the primary approach to clarify the mappings of phenotypic and genotypic changes. Here, we performed high-throughput laboratory evolution with bacteria using an automated culture system, to quantify phenotypic and genotypic changes occurred under various stress conditions. We identified various stress-specific gene expression changes and mutations, and contributions of them to fitness gain were validated. These results demonstrated that the integration of phenotypic and genotypic changes makes it possible to extract the mechanisms for stress resistance evolution, which will contribute to bioengineering applications.

evolutionary biology↗