Biology subjects

Furusawa, C.

Publications and source records attributed to Furusawa, C..

At least 19 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

Genome reduction increases endosymbiont sensitivity and promotesmutualism evolution

Endosymbiosis is a major source of biological innovation, enabling hosts to explore new ecological niches. While genome reduction in endosymbionts is well documented, its impact on the evolutionary transition from parasitism to mutualism remains unclear. Regulatory genes are lost disproportionately as bacterial genomes shrink, as we confirm in endosymbiont-containing lineages. We therefore model metabolic competition between hosts and endosymbionts, representing endosymbiont genome size by the number of independently regulated sets of reactions. In our simulations, hosts that grow poorly alone adapt best when harboring moderately genome-reduced endosymbionts rather than large-genome ones. This advantage goes beyond the lower resource use of smaller endosymbionts. By decomposing endosymbiont metabolic responses to changes in host-provided metabolites into "adaptability" and "sensitivity," we demonstrate that moderate genome reduction increases the sensitivity of endosymbionts to host metabolic conditions, rendering them more exploitable through host evolution. This suggests that genome reduction plays a more constructive role in mutualism evolution than previously appreciated, facilitating host-level selection for exploitable endosymbionts rather than being merely a passive consequence of endosymbiosis. Our systems-level approach, focusing on regulatory capacity rather than specific gene functions, provides a general framework for understanding how genome reduction affects the evolutionary trajectory from parasitic to mutualistic endosymbionts, and may help explain the frequent replacement of highly reduced endosymbionts in nature.

evolutionary biology↗

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

Lineage-Independent Modular Evolution of Carbon-Source Utilization

Metabolic phenotypes vary within microbial species, yet how such variation is organized remains unclear. Diversification in carbon-source utilization, in particular, often appears idiosyncratic, showing weak correspondence to phylogeny or simple gene content. Here, we combine quantitative growth phenotyping of natural Escherichia coli isolates across 32 carbon sources with diversification observed during de novo laboratory evolution, together with a reaction-level description of metabolic similarity. Despite deep phylogenetic divergence, growth-rate profiles varied independently of lineage. Instead, growth rates across carbon sources covaried in recurrent modular patterns aligned with similarities in required metabolic reactions. Closely analogous modular relationships re-emerged during de novo evolution, indicating parallel diversification across evolutionary contexts. Growth-rate variation in natural and experimentally evolved datasets collapsed onto a shared low-dimensional variance structure. Together, our results indicate that quantitative metabolic phenotypes vary along a limited set of recurring, module-linked axes, providing an organizational perspective on intraspecific metabolic diversity despite weak phylogenetic signal.

evolutionary biology↗

bioRxiv2026

Decoding Anadara shell morphology with deep learning

Accurate shell shape quantification is critical for studying biodiversity and evolution, yet intraspecific variability in bivalves makes morphology-based identification difficult. Traditional methods, including landmark-based analyses and elliptic Fourier descriptors, suffer either from subjectivity in homologous point selection or from limited use of contour information. Here, we introduce Morpho-VAE, a deep generative framework integrating a variational autoencoder with a supervised classifier, to analyze shell images of five Anadara species. Morpho-VAE outperforms conventional approaches in species classification by embedding morphological variation into a low-dimensional space where species cluster distinctly. To highlight species-specific morphological patterns, we develop a patch masking assay, revealing the hinge line as a shared morphological marker across species and species-specific regions near the umbo and anterior ventral margin. The decoder further enables morphological visualization via image reconstruction and interpolation. Our results show that Morpho-VAE can automatically extract species-defining morphological patterns from raw images, providing complementary or novel insights beyond traditional morphometric methods.

biophysics↗

bioRxiv2026

Elucidating the Bell-Shaped Dependence of Protein Translation Activity on EF-Tu Concentration in a Reconstituted Cell-Free System Using a Mechanistic Model

Protein synthesis in cell-free protein synthesis systems often exhibits non-intuitive input-output relationships. In the PURE system, a reconstituted cell-free system, protein production peaked at low elongation factor Tu (EF-Tu) concentrations and decreased at higher concentrations, resulting in a characteristic bell-shaped profile. Here, we investigated the origin of this behavior using a detailed mechanistic model of translation in the PURE system, designated as ePURE, which describes reaction dynamics of hundreds of molecular species and reactions. Our computational analysis suggested that excess EF-Tu sequesters the initiator tRNA (tRNAfMet) into non-productive EF-Tu{middle dot}GTP{middle dot}Met-tRNAfMet complexes, thereby depleting the pool of initiator tRNA available for translation initiation. This suppression arises from competition for a limited molecular resource rather than from direct inhibition. Based on this mechanism, we predicted that increasing the concentrations of tRNAfMet and methionyl-tRNA formyl-transferase would eliminate the bell-shaped dependence, and experimentally confirmed this prediction. Under these modified conditions, the bell-shaped response disappeared and protein production was enhanced. These findings demonstrate how mechanistic computational models can reveal hidden constraints underlying non-intuitive input-output relationships in complex biochemical networks and guide the rational optimization of cell-free protein synthesis systems.

synthetic biology↗

bioRxiv2026

Adhesion and polarity-driven morphogenesis: Mechanismsand constraints in tissue formation

Embryonic development in multicellular organisms exhibits diverse morphogenetic patterns, which can generally be categorized into fundamental types such as monolayer and multilayer spheres, as well as cell masses. Furthermore, we identify two distinct processes for the formation of spherical structures. These basic patterns are thought to be governed by the microscopic properties of intercellular adhesion. However, the specific mechanisms linking the microscopic factors to the emergence of distinct macroscopic morphogenetic patterns remain poorly understood. In this study, we explore how different morphogenetic patterns arise by employing a computational model that incorporates intercellular adhesion and polarity. Our results demonstrate that all fundamental morphogenetic patterns can be generated through the interplay of two key parameters: the strength of cell polarity and the regulation of polarity via mechanical signals. Furthermore, analytical discussions reveal partial mechanisms underlying the formation of these patterns. These findings highlight the critical role of physical constraints in morphogenesis and suggest potential applications in the design principles for artificial tissues and organoids. Author summaryLiving organisms build their bodies through morphogenesis, during which cells autonomously arrange themselves into functional structures such as sheets, tubes, and spheres. From simple monolayered spheres to complex multilayered tissues organized by adhesion, it remains unclear how such diverse forms arise. Here, we mathematically modeled a population of proliferating cells governed only by two microscopic factors: the strength of polarity-dependent adhesion and the time scale at which polarity is regulated by cell-cell contact. Surprisingly, we found that this minimal model reproduces five basic morphological types observed in living embryos, including monolayer/multilayer structures and two distinct modes of cavity formation: by wrapping around or by inflating from the inside. Systematic simulations revealed that these macroscale outcomes are determined solely by two parameters controlling polarity strength and its regulation, suggesting that simple physical rules underlie diverse developmental architectures. Analysis of the model uncovers phase transitions between the five morphogenetic types and reveals how varying polarity and adhesion can recapitulate features of real embryogenesis. Our work proposes a unified framework that connects microscopic polarity mechanics to diverse developmental morphologies and provides a foundation for future applications in organoid design and tissue engineering.

biophysics↗

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

Analysis of Metabolic Stability under Environmental Perturbations Using a Kinetic Model

Cells robustly maintain metabolic function despite environmental fluctuations affecting reaction kinetics, yet kinetic models often exhibit fragility. We investigated this discrepancy by examining the effects of temperature changes on a kinetic model of Escherichia coli central metabolism. A gradual temperature decrease caused an abrupt transition to a state with sharply reduced ATP production efficiency, triggered by an elevated ATP/ADP ratio creating a glycolysis bottleneck. Introducing a rapid ATP-ADP exchange reaction prevented this ATP/ADP ratio surge and sustained high ATP production efficiency across temperatures. Furthermore, altering enzyme abundances similarly maintained high ATP production, with predicted enzyme regulation aligning with experimental observations in E. coli at low temperatures. Our findings indicate that balancing key cofactors, such as the ATP/ADP ratio, is crucial for preserving metabolic stability under environmental perturbations.

systems biology↗

bioRxiv2025

Host range and ARG dissemination are shaped by distinct survival strategies of conjugative plasmids

Horizontal gene transfer is a major driver of bacterial evolution and the global dissemination of antibiotic resistance genes (ARGs). Conjugative plasmids play a crucial role in ARG spread across hosts within their host range, yet the genetic and functional determinants shaping plasmid host range remain poorly understood. Here, we systematically analyzed the gene content of conjugative/mobilizable plasmids from public databases and found that two distinct survival strategies were enriched in different host-range groups: a "stealth" strategy, which minimizes host fitness costs by employing a global regulator h-ns, was particularly enriched in broad-host-range plasmids, whereas an "aggressive" strategy, which protects plasmids by actively inhibiting host response including SOS response by encoding the SOS inhibitor psiB, was more common in narrow-host-range plasmids. Plasmids employing either strategy constituted the majority of all conjugative plasmids analyzed, and accumulated significantly more ARGs than plasmids with neither strategy. Our data further suggested that stealth plasmids facilitate the acquisition of emerging ARGs, while aggressive plasmids amplify the copy number of established ARGs. This "stealth-first" model successfully recapitulated historical ARG dissemination patterns. These findings provide critical insights into the relationship between plasmid survival strategies and host range, advancing our understanding of the global patterns underlying plasmid-mediated ARG transmission. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/655438v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@bb692dorg.highwire.dtl.DTLVardef@1f639f1org.highwire.dtl.DTLVardef@562f75org.highwire.dtl.DTLVardef@45e1e4_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Population dynamics of generalist/specialist strategies in the feast-famine cycle

Microbial populations exhibit a broad spectrum of nutrient utilization strategies, ranging from those utilizing diverse nutrients, called "generalists," to those being highly adapted to specific nutrients, called "specialists." Identifying the conditions for the diversification of nutrient utilization strategies is one of the central questions in ecology. Previous theoretical studies have shown that trade-offs among different resource utilization functions in which cells cannot utilize broad types of substrates at nearly optimal efficiency are crucial for the emergence of diverse strategies. Additionally, in natural settings, nutrient availability often fluctuates over time, imposing another trade-off on the cells. Cells that grow rapidly under nutrient-rich conditions tend to have a higher death rate under nutrient-poor conditions, leading to a growth-death trade-off. This additional trade-off can contribute to the emergence of diverse strategies. Here, we introduce a mathematical model that simultaneously incorporates the resource-use trade-off and the growth-death trade-off. Nutrient supply was modeled as discrete stochastic events, mimicking temporal changes in nutrient availability. We show that the phenotype with a higher ratio of growth rate to death rate dominates the population; that is, the strength of the growth-death trade-off is a major determinant of whether generalists or specialists are dominant. We also found that a sparse and uncertain nutrient supply favors specialists, increasing their temporally averaged abundance. Our findings reveal that accounting for temporal environmental variation and the resulting growth-death trade-off is crucial for understanding the drivers of diversification in microbial nutrient utilization strategies. Author summaryMicrobial strategies for choosing the nutrients to utilize are highly diverse. In our study, we explored why some microbes become generalists able to use a variety of nutrients, whereas others specialize in only a few nutrients. These strategies often result from metabolic trade-offs during nutrient processing. However, in fluctuating environmental conditions, it is important to consider additional trade-offs; under nutrient-rich conditions, they can grow quickly, but this often comes at the cost of being more vulnerable when nutrients are scarce. To investigate how these trade-offs affect the emergence of generalists and specialists, we developed a simple model called the feast-famine cycle that mimics the natural cycles of plenty and scarcity of nutrients. Our work shows that the trade-off between growth and death rates is crucial for determining whether a generalist or specialist strategy is dominant. We highlight the importance of trade-offs in response to environmental changes in shaping microbial adaptive strategies.

ecology↗

bioRxiv2025

Carbon source diversity shapes bacterial interspecies interactions

Bacterial communities exhibit various classes of interspecies interactions, ranging from cooperative to competitive. As these interaction classes play a crucial role in determining characteristics of bacterial communities, including species composition and community stability, understanding of the mechanisms that shape them is warranted. While several studies have suggested that cooperative interactions are rare, a study focused on single-carbon-source environments reported them to be relatively common. This discrepancy highlights the potential role of carbon source diversity in shaping interaction classes, although the quantitative relationship remains unclear. To elucidate this relationship, we examined 896 interspecies interactions among 28 synthetic bacterial pairs, isolated from various environments, under 32 conditions with varying levels of carbon source diversity. As a result, we frequently observed cooperative interactions in single-carbon-source environments, with the interactions shifting to competitive as the carbon source diversity increased. Further analyses suggested that this shift was driven by intensified resource competition in more complex media. Our findings provide new insights into how environmental factors, particularly carbon source diversity, shape bacterial interactions in synthetic communities, offering potential strategies for manipulating bacterial communities in ecological and biotechnological contexts.

microbiology↗

bioRxiv2025

Repeatability of protein structural evolution following convergent gene fusions

Convergent evolution of proteins provides insights into repeatability of genetic adaptation. While local convergence of proteins at residue or domain level has been characterized, global structural convergence by inter-domain/molecular interactions remains largely unknown. Here we present structural convergent evolution on fusion enzymes of aldehyde dehydrogenases (ALDHs) and alcohol dehydrogenases (ADHs). We discovered BdhE (bifunctional dehydrogenase E), an enzyme clade that emerged independently from the previously known AdhE family through distinct gene fusion events. AdhE and BdhE showed shared enzymatic activities and non-overlapping phylogenetic distribution, suggesting common functions in different species. Cryo-electron microscopy revealed BdhEs form donut-like homotetramers, contrasting AdhEs helical homopolymers. Intriguingly, despite distinct quaternary structures and >70% unshared amino acids, both enzymes form resembled dimeric structure units by ALDH-ADH interactions via convergently elongated loop structures. These findings suggest convergent gene fusions recurrently led to substrate channeling evolution to enhance two-step reaction efficiency. Our study unveils structural convergence at inter-domain/molecular level, expanding our knowledges on patterns behind molecular evolution exploring protein structural universe.

evolutionary biology↗

bioRxiv2024

Congruence between noise and plasticity in protein expression

Gene expression responds to various perturbations, such as mutations, environmental changes, and stochastic perturbations. The variability in gene expression levels differs among genes, influencing the availability of adaptive variants or mutants and thereby affecting nongenetic and genetic adaptations. Different types of variability are interdependent, suggesting global canalization/decanalization against different perturbations and a common underlying mechanism. Despite this, the relationship between plasticity (variability in response to environmental changes) and noise (variability among cells under the same conditions) in gene expression remains debatable. Previous studies reported a positive correlation between plasticity and noise, but these variabilities are often measured at different levels: plasticity at the mRNA level and noise at the protein level. This methodological discrepancy complicates the understanding of their relationship. We investigated this by measuring protein expression levels of essential and nonessential genes in Escherichia coli. Using flow cytometry, we quantified noise and plasticity from the same dataset. Essential genes exhibited lower noise and plasticity than nonessential genes. Nonessential genes showed a positive correlation between noise and plasticity, while essential genes did not. This study provides empirical evidence of essentiality-dependent coupling between noise and plasticity in protein expression, highlighting the organization of different types of variabilities.

systems biology↗

bioRxiv2024

Laboratory evolution of the bacterial genome structure through insertion sequence activation

The genome structure critically impacts bacterial physiology, ecology, and evolution. However, its evolution, driven by transposons called insertion sequences (IS), has been challenging to track in laboratories due to its slow pace. Here, we accelerated this process by introducing multiple copies of a high-activity IS into Escherichia coli. Mimicking bursts of IS copies in host-restricted endosymbionts and pathogens, we evolved the bacteria under relaxed neutral conditions. Within ten weeks, we observed a median of 24.5 IS insertions per genome, comparable to a decade of wild-type evolution. Long-read sequencing revealed extensive IS-mediated genome rearrangements, resulting in novel IS variants and genome size changes exceeding {+/-}5 %. By achieving such drastic genome evolution under relaxed selection, our study establishes a baseline for assessing the fitness effects of IS insertions, genome size changes, and rearrangements. This work paves the way for experimentally studying bacterial genome structure evolution, complementing analyses of genome structures in nature.

microbiology↗

bioRxiv2024

Promoter constrains evolution of expression levels of essential genes inEscherichia coli

Variability in expression levels in response to random genomic mutations varies among genes, influencing both the facilitation and constraint of phenotypic evolution in organisms. Despite its importance, both the underlying mechanisms and evolutionary origins of this variability remain largely unknown due to the mixed contributions of cis- and trans-acting elements. To address this issue, we focused on the mutational variability of cis-acting elements, that is, promoter regions, in Escherichia coli. Random mutations were introduced into the natural and synthetic promoters to generate mutant promoter libraries. By comparing the variance in promoter activity of these mutant libraries, we found no significant difference in mutational variability in promoter activity between promoter groups, suggesting the absence of a signature of natural selection for mutational robustness. In contrast, the promoters controlling essential genes exhibited a remarkable bias in mutational variability, with mutants displaying higher activities than the wild types being relatively rare compared to those with lower activities. Our evolutionary simulation on a rugged fitness landscape provided a rationale for this vulnerability. These findings suggest that past selection created non-uniform mutational variability in promoters biased toward lower activities of random mutants now constrain future evolution of downstream essential genes toward higher expression levels.

evolutionary biology↗

bioRxiv2024

Genetic properties underlying transcriptional variability in Escherichia coli

AbstractThe rate and direction of phenotypic evolution depend on the availability of phenotypic variants induced genetically or environmentally. It is widely accepted that organisms do not display uniform phenotypic variation, with certain variants arising more frequently than others in response to genetic or environmental perturbations. Previous studies have suggested that gene regulatory networks channel both environmental and genetic influences. However, how the gene regulatory networks influence phenotypic variation remains unclear. To address this, we characterize transcriptional variations in Escherichia coli under environmental and genetic perturbations. Based on the current understanding of transcriptional regulatory networks, we identify genetic properties that explain gene-to-gene differences in transcriptional variation. Our findings highlight the role of gene regulatory networks in shaping the shared phenotypic variability across different perturbations.

evolutionary biology↗

bioRxiv2023

Perturbation-response analysis of in silico metabolic dynamics: Hard-coded responsiveness in the cofactor and network sparsity

Homeostasis is a fundamental characteristic of living systems. Unlike rigidity, homeostasis necessitates that systems respond flexibly to diverse environments. Understanding the dynamics of biochemical systems when subjected to perturbations is essential for the development of a quantitative theory of homeostasis. In this study, we analyze the response of bacterial metabolism to externally imposed perturbations using kinetic models of Escherichia colis central carbon metabolism in nonlinear regimes. We found that three distinct kinetic models consistently display strong responses to perturbations; In the strong responses, minor initial discrepancies in metabolite concentrations from steady-state values amplify over time, resulting in significant deviations. This pronounced responsiveness is a characteristic feature of metabolic dynamics, especially since such strong responses are seldom seen in toy models of the metabolic network. Subsequent numerical studies show that adenyl cofactors consistently influence the responsiveness of the metabolic systems across models. Additionally, we examine the impact of network structure on metabolic dynamics, demonstrating that as the metabolic network becomes denser, the perturbation response diminishes--a trend observed commonly in the models. To confirm the significance of cofactors and network structure, we constructed a simplified metabolic network model, underscoring their importance. By identifying the structural determinants of responsiveness, our findings offer implications for bacterial physiology, the evolution of metabolic networks, and the design principles for robust artificial metabolism in synthetic biology and bioengineering.

systems biology↗