生物学最新文献

Dermatophytosis afflicts approximately 25% of the global population, representing a critical public health burden. Trichophyton mentagrophytes (T. mentagrophytes), a predominant zoonotic dermatophyte, is a significant contributor to disease morbidity. While the transcriptomic response of keratinocytes-the primary barrier of the skin-to T. mentagrophytes infection is well characterized, the genome-wide translational regulatory mechanisms remain unknown. Here, we employed parallel ribosome profiling (Ribo-seq) and RNA sequencing (RNA-seq) to dissect the genome-wide transcriptional and translational landscape of human keratinocytes during T. mentagrophytes infection. Our analysis revealed extensive but distinct reprogramming at both transcriptional (3,189 differentially expressed genes) and translational (295 differentially translated genes) levels, with only minimal overlap (5.8% of upregulated genes and 0.8% of the downregulated genes), indicating prevalent post-transcriptional control. We further identified and characterized a vast non-canonical translatome, including 17,564 upstream ORFs (uORFs), 188,357 downstream ORFs (dORFs), and 185,704 lncRNA-derived ORFs (lncORFs). Strikingly, both translatable uORFs and dORFs were associated with significantly enhanced translation efficiency (TE) of their host genes, a phenomenon conserved under infection. Moreover, we demonstrated that miRNAs coordinately repress target gene expression at both transcriptional and translational levels. Functional interactions revealed that the presence of translated uORFs or dORFs could significantly attenuate miRNA-mediated TE suppression. This study provides the first comprehensive map of the keratinocyte translatome during fungal infection, establishing uORFs and dORFs as critical dual-layer regulators in the host anti-fungal defense.

In E. coli endoribonuclease RNase E (Rne) plays a central role in RNA processing and decay. Rne consists of an N-terminal catalytic domain (NTD) and a C-terminal scaffolding domain, separated by a membrane targeting sequence (MTS). While the scaffolding domain represents a hub for interaction, only few proteins are known to bind the Rne-NTD. One example is protein RapZ, which forms a transient complex with the Rne-NTD to target a small RNA to decay. Here, we screened a genomic bacterial two-hybrid library for proteins binding to the Rne N-terminal half including the MTS. We identified fragments of 43 proteins, of which 15 were validated to bind Rne as full-length proteins. We distinguished three groups: Group I likely uses a membrane domain to bind a segment in Rne that contains the MTS. Group II proteins are cytoplasmic and bind the Rne-NTD. Group III proteins bind the Rne-NTD and additionally the MTS region, indicating two distinct interaction surfaces. RNA-seq revealed that overproduction of three group II proteins including YegJ generates similar effects on the transcriptome. Genes carrying Rne cleavage sites were enriched among downregulated genes but depleted from upregulated genes, suggesting altered RNA decay. Interestingly, strong overexpression of yegJ destabilizes rRNA and arrests growth. Apparently, YegJ damages the membrane, granting periplasmic RNase I and presumably also Rne access to cytoplasmic rRNA. We present a catalogue of proteins likely binding the Rne N-terminal half, which may provide a valuable resource for further investigation of these interactions and their roles.

Determining optimal antibiotic dosing strategies is complex. Clinically, some antibiotics work best in continuous low doses, while others require high repeated pulses. However, a rational understanding of the best approach depending on the specific pairing of antibiotics and bacterial species remains unclear. Using mathematical models, we analyze bacterial populations under two strategies-constant concentration and repeated dosing-with fixed pharmacodynamic and pharmacokinetic properties. Our results reveal that the shape of the dose‒response curve, which measures the bacterial net growth rate against the antibiotic concentration, is crucial. Specifically, its concavity determines the best strategy. In cases where the curve exhibits multiple concavities, additional factors, such as the tolerable dosing range, influence the regimen. These findings challenge the universal application of 'hit hard and hit early', as some recommended schedules include lower, constant doses. This work contributes to the literature on rational antibiotic prescription, aiming to minimize antibiotic use and combat antimicrobial resistance.

HNRNPA2B1 contains two RRM domains and has been investigated for its possible role as an m⁶A reader protein. The targetome of HNRNPA2B1 was shown to overlap with the m⁶A methylation motif, but further investigations of its binding affinity for m⁶A-containing RNAs have been less clear on the relative selectivity of HNRNPA2B1 for methylated transcripts. Our computational and experimental studies depict that when an m⁶A modification is positioned in between the two RRM domains, and in the context of the GGACU motif that can be written by methyltransferases, the binding affinity is nearly identical and slightly less favourable to the unmodified sequence. Our study suggests that HNRNPA2B1 is not a (selective) reader but has high affinity for m⁶A in a sequence-dependent manner. This can be attributed to the strong interactions conferred by AGG and UAG motifs rather than adenine or m⁶A in the GGACU motif which are predicted to interact weakly, intercalating between the two RRMs or positioned outwards. Overall, our findings highlight the higher complexity of HNRNPA2B1 and RRM recognition properties compared to well-studied YTH domains in the recognition of m⁶A, as well as modified and unmodified sequences.

Rhizopus microsporus is an opportunistic fungal pathogen and a prominent etiological agent of mucormycosis, a life-threatening invasive fungal infection. In this study, we investigated the role of choC, a gene encoding a putative phospholipid methyltransferase involved in phosphatidylcholine (PC) biosynthesis through the Bremer-Greenberg pathway. Deletion of choC using CRISPR-Cas9 led to severe defects in growth and asexual development, which persisted even at 37°C, a temperature relevant to host infection. Supplementation with choline or its precursor PDEA restored growth, confirming the importance of choC in maintaining PC levels. Lipidomic and transcriptomic analyses revealed broad disruptions in PC and phosphatidylethanolamine (PE) levels, glycerol-3-phosphate and fatty acid metabolism, endoplasmic reticulum (ER) stress responses, and vesicle trafficking. Notably, ΔchoC mutants exhibited reduced melanin and chitin content, while ergosterol levels remained unaffected, indicating specific impairment in cell envelope assembly. In a murine infection model, the ΔchoC mutant showed attenuated virulence, linking lipid imbalance to impaired host adaptation. Together, these findings highlight choC as a key regulator of membrane homeostasis and fungal pathogenicity. As the methylation-dependent PC synthesis pathway is barely present in human tissues, choC represents a promising target for selective antifungal therapies.

We extend the predator-prey model developed by Ackleh et al. [Persistence and stability analysis of discrete-time predator-prey models: A study of population and evolutionary dynamics. J. Differ. Equ. Appl. 2019;25:1568-1603] to incorporate the evolution of a predator's resistance to toxicant effects. We consider three cases: (1) lethal effects, where the toxicant directly influences the predator's survival; (2) sublethal effects, where the toxicant impacts the predator's fecundity, and (3) mixed effects, where the toxicant impacts both vital rates. For the first two cases, we derive conditions for existence and stability of model equilibria and for system persistence. These cases are also analyzed numerically to further understand the system dynamics. Overall, we find that evolution of a predator to resist a toxicant may allow for predator survival when otherwise it would have faced extinction. However, evolution in response to lethal effects can generate multiple boundary equilibria, leading to alternative stable states. When this occurs, evolution in response to a toxicant may result in the extinction of the predator while, without evolution, the predator survives.

Using an appropriate mathematical model, this study aims to examine the transmission dynamics and optimal control of hepatitis B virus spreading, employing the Beddington-DeAngelis incidence function, a hybrid method of 4th order Runge-Kutta method (RK4) and feed-forward neural network (FFNN), as the integration of epidemiological models with neural network is particularly important for representing disease propagation. The well-posedness, local and global stability conditions are obtained using the threshold parameter. Some sensitive epidemic parameters and their relative impacts are quantified. Based on the local and global properties of the model and sensitivity analysis, a control problem is formulated to control the infection by minimizing the HBV-infected population and maximizing the recovered population using three control measures. Finally, a hybrid method of supervised FFNN and RK4 with two hidden layers is used to effectively approximate the temporal dynamics of HBV transmission and verify the theoretical results, as well as the effects of controls.

Severe fever with thrombocytopenia syndrome (SFTS), caused by Dabie bandavirus (SFTS virus, SFTSV), poses a growing public health concern in East Asia. Limited genomic data from Shandong Province have restricted understanding of viral evolution, while codon usage bias, a key factor in viral fitness and host adaptation, remains uncharacterized. In this study, we analyzed codon usage patterns in SFTSV strains from Shandong using newly 152 sequenced samples and publicly available genomes. Phylogenetic analysis identified seven genotypes, with genotype A being dominant. Viral genomes showed higher adenine (A) and guanine (G) content and a tendency to use G or cytosine (C) at the third codon position. Relative synonymous codon usage analysis demonstrated gene-specific preferences for codons ending in G/C. Effective number of codons values indicated weak overall codon usage bias. Further analyses suggested that both mutation pressure and natural selection influence codon usage, with natural selection playing the dominant role (52.8-91.4%), particularly in the nucleoprotein (91.4%) and nonstructural genes (89.5%). Codon adaptation index analysis across 12 host species indicated stronger codon adaptation to humans and Gallus gallus, implying higher viral replication efficiency in these hosts. Overall, codon usage bias is primarily driven by natural selection rather than mutation pressure. These findings improve understanding of SFTSV molecular evolution and may inform strategies for surveillance, vaccine design, and host-specific intervention.

We study periodic dynamics and error-threshold behavior in a delayed quasispecies model consisting of a master sequence $\left(x_0\right)$ and two mutant populations $(x_1,x_2)$. The system, formulated as delay differential equations with time-periodic replication rates, yields new conditions for the existence and absence of $T$-periodic solutions. Using topological degree arguments, we show that when mutation probabilities $\left(Q_{\mathrm{ji}}\right)$ lie strictly between 0 and 1 and at least one fitness function $\left(f_j\right)$ is periodic, the system supports nontrivial positive periodic orbits, with or without backward mutations. This shows that fluctuating environments, such as circadian or treatment-induced cycles, can sustain oscillatory genotype distributions. Conversely, if mutations are strictly unidirectional and the master sequence is consistently dominated in fitness, no positive $T$-periodic orbit arises. In this regime, the master sequence decays monotonically to extinction without time delays, while time delays induce non-monotonic decay, recovering the classical error-threshold phenomenon and linking it to cancer-related quasispecies dynamics.

Heart failure arises from maladaptive remodelling driven by genetic and epigenetic networks. Using a systems genetics framework, we mapped how DNA variants and CpG methylation shape cardiac transcriptomes during beta adrenergic stress in the Hybrid Mouse Diversity Panel, a cohort of over 100 fully inbred mouse strains. Expression QTLs (eQTLs), methylation QTLs (mQTLs) and methylation-driven eQTLs (emQTLs) were generated from over 13k expressed genes and 200k hypervariable CpGs in left ventricles. We discovered hundreds of regulatory 'hotspots' that control large portions of the genome, including several that regulate over 10% of the transcriptome and/or methylome. Approximately 16% of these hotspots overlapped with prior GWAS or EWAS signals. We focus on a hotspot on chromosome 12 and identify the serpine peptidase inhibitor Serpina3n, as the most likely driver gene in this hotspot. Experimental knockdown of Serpina3n in neonatal rat ventricular cardiomyocytes blunted hypertrophy induced by a variety of hypertrophic signals, while altering predicted target expression and modulating the activity of Nppa and Nppb. Together, these findings position Serpina3n as a major regulator of stress-responsive cardiac gene programs, highlighting how integration of genetic and epigenetic signals can pinpoint key drivers of heart failure.