Airborne transmission of human-isolated avian H3N8 influenza virus between ferrets.

H3N8 avian influenza viruses (AIVs) in China caused two confirmed human infections in 2022, followed by a fatal case reported in 2023. H3N8 viruses are widespread in chicken flocks; however, the zoonotic features of H3N8 viruses are poorly understood. Here, we demonstrate that H3N8 viruses were able to infect and replicate efficiently in organotypic normal human bronchial epithelial (NHBE) cells and lung epithelial (Calu-3) cells. Human isolates of H3N8 virus were more virulent and caused severe pathology in mice and ferrets, relative to chicken isolates. Importantly, H3N8 virus isolated from a patient with severe pneumonia was transmissible between ferrets through respiratory droplets; it had acquired human-receptor-binding preference and amino acid substitution PB2-E627K necessary for airborne transmission. Human populations, even when vaccinated against human H3N2 virus, appear immunologically naive to emerging mammalian-adapted H3N8 AIVs and could be vulnerable to infection at epidemic or pandemic proportion.

Early T cell activation: integrating biochemical, structural, and biophysical cues.

T cells carry out the formidable task of identifying small numbers of foreign antigenic peptides rapidly and specifically against a very noisy environmental background of endogenous self-peptides. Early steps in T cell activation have thus fascinated biologists and are among the best-studied models of cell stimulation. This remarkable process, critical in adaptive immune responses, approaches and even seems to exceed the limitations set by the physical laws ruling molecular behavior. Despite the enormous amount of information concerning the nature of molecules involved in the T cell antigen receptor (TCR) signal transduction network, and the description of the nanoscale organization and real-time analysis of T cell responses, the general principles of information gathering and processing remain incompletely understood. Here we review currently accepted key data on TCR function, discuss the limitations of current research strategies, and suggest a novel model of TCR triggering and a few promising ways of going further into the integration of available data.

Liquid-to-solid phase transition of oskar ribonucleoprotein granules is essential for their function in Drosophila embryonic development.

Asymmetric localization of oskar ribonucleoprotein (RNP) granules to the oocyte posterior is crucial for abdominal patterning and germline formation in the Drosophila embryo. We show that oskar RNP granules in the oocyte are condensates with solid-like physical properties. Using purified oskar RNA and scaffold proteins Bruno and Hrp48, we confirm in vitro that oskar granules undergo a liquid-to-solid phase transition. Whereas the liquid phase allows RNA incorporation, the solid phase precludes incorporation of additional RNA while allowing RNA-dependent partitioning of client proteins. Genetic modification of scaffold granule proteins or tethering the intrinsically disordered region of human fused in sarcoma (FUS) to oskar mRNA allowed modulation of granule material properties in vivo. The resulting liquid-like properties impaired oskar localization and translation with severe consequences on embryonic development. Our study reflects how physiological phase transitions shape RNA-protein condensates to regulate the localization and expression of a maternal RNA that instructs germline formation.

Strain-level fitness in the gut microbiome is an emergent property of glycans and a single metabolite.

The human gut microbiota resides within a diverse chemical environment challenging our ability to understand the forces shaping this ecosystem. Here, we reveal that fitness of the Bacteroidales, the dominant order of bacteria in the human gut, is an emergent property of glycans and one specific metabolite, butyrate. Distinct sugars serve as strain-variable fitness switches activating context-dependent inhibitory functions of butyrate. Differential fitness effects of butyrate within the Bacteroides are mediated by species-level variation in Acyl-CoA thioesterase activity and nucleotide polymorphisms regulating an Acyl-CoA transferase. Using in vivo multi-omic profiles, we demonstrate Bacteroides fitness in the human gut is associated together, but not independently, with Acyl-CoA transferase expression and butyrate. Our data reveal that each strain of the Bacteroides exists within a unique fitness landscape based on the interaction of chemical components unpredictable by the effect of each part alone mediated by flexibility in the core genome.

Nucleoid Size Scaling and Intracellular Organization of Translation across Bacteria.

The scaling of organelles with cell size is thought to be exclusive to eukaryotes. Here, we demonstrate that similar scaling relationships hold for the bacterial nucleoid. Despite the absence of a nuclear membrane, nucleoid size strongly correlates with cell size, independent of changes in DNA amount and across various nutrient conditions. This correlation is observed in diverse bacteria, revealing a near-constant ratio between nucleoid and cell size for a given species. As in eukaryotes, the nucleocytoplasmic ratio in bacteria varies greatly among species. This spectrum of nucleocytoplasmic ratios is independent of genome size, and instead it appears linked to the average population cell size. Bacteria with different nucleocytoplasmic ratios have a cytoplasm with different biophysical properties, impacting ribosome mobility and localization. Together, our findings identify new organizational principles and biophysical features of bacterial cells, implicating the nucleocytoplasmic ratio and cell size as determinants of the intracellular organization of translation.

A Membraneless Organelle Associated with the Endoplasmic Reticulum Enables 3'UTR-Mediated Protein-Protein Interactions.

Approximately half of human genes generate mRNAs with alternative 3' untranslated regions (3'UTRs). Through 3'UTR-mediated protein-protein interactions, alternative 3'UTRs enable multi-functionality of proteins with identical amino acid sequence. While studying how information on protein features is transferred from 3'UTRs to proteins, we discovered that the broadly expressed RNA-binding protein TIS11B forms a membraneless organelle, called TIS granule, that enriches membrane protein-encoding mRNAs with multiple AU-rich elements. TIS granules form a reticular meshwork intertwined with the endoplasmic reticulum (ER). The association between TIS granules and the ER creates a subcellular compartment-the TIGER domain-with a biophysically and biochemically distinct environment from the cytoplasm. This compartment promotes 3'UTR-mediated interaction of SET with membrane proteins, thus allowing increased surface expression and functional diversity of proteins, including CD47 and PD-L1. The TIGER domain is a subcellular compartment that enables formation of specific and functionally relevant protein-protein interactions that cannot be established outside.

Mechanisms Underlying Vibrio cholerae Biofilm Formation and Dispersion.

Biofilms are a widely observed growth mode in which microbial communities are spatially structured and embedded in a polymeric extracellular matrix. Here, we focus on the model bacterium Vibrio cholerae and summarize the current understanding of biofilm formation, including initial attachment, matrix components, community dynamics, social interactions, molecular regulation, and dispersal. The regulatory network that orchestrates the decision to form and disperse from biofilms coordinates various environmental inputs. These cues are integrated by several transcription factors, regulatory RNAs, and second-messenger molecules, including bis-(3'-5')-cyclic dimeric guanosine monophosphate (c-di-GMP). Through complex mechanisms, V. cholerae weighs the energetic cost of forming biofilms against the benefits of protection and social interaction that biofilms provide.

High-throughput measurement of elastic moduli of microfibers by rope coiling.

There are many fields where it is of interest to measure the elastic moduli of tiny fragile fibers, such as filamentous bacteria, actin filaments, DNA, carbon nanotubes, and functional microfibers. The elastic modulus is typically deduced from a sophisticated tensile test under a microscope, but the throughput is low and limited by the time-consuming and skill-intensive sample loading/unloading. Here, we demonstrate a simple microfluidic method enabling the high-throughput measurement of the elastic moduli of microfibers by rope coiling using a localized compression, where sample loading/unloading are not needed between consecutive measurements. The rope coiling phenomenon occurs spontaneously when a microfiber flows from a small channel into a wide channel. The elastic modulus is determined by measuring either the buckling length or the coiling radius. The throughput of this method, currently 3,300 fibers per hour, is a thousand times higher than that of a tensile tester. We demonstrate the feasibility of the method by testing a nonuniform fiber with axially varying elastic modulus. We also demonstrate its capability for in situ inline measurement in a microfluidic production line. We envisage that high-throughput measurements may facilitate potential applications such as screening or sorting by mechanical properties and real-time control during production of microfibers.

Three-atom-wide gold quantum rods with periodic elongation and strongly polarized excitons.

Atomically precise control over anisotropic nanoclusters constitutes a grand challenge in nanoscience. In this work, we report our success in achieving a periodic series of atomically precise gold quantum rods (abbrev. Au QRs) with unusual excitonic properties. These QRs possess hexagonal close-packed kernels with a constant three-atom diameter but increasing aspect ratios (ARs) from 6.3 to 18.7, all being protected by the same thiolate (SR) ligand. The kernels of the QRs are in a Au1-(Au3)n-Au1 configuration (where n is the number of Au3 layers) and follow a periodic elongation with a uniform Au18(SR)12 increment consisting of four Au3 layers. These Au QRs possess distinct HOMO-LUMO gaps (Eg = 0.6 to 1.3 eV) and exhibit strongly polarized excitonic transition along the longitudinal direction, resulting in very intense absorption in the near-infrared (800 to 1,700 nm). While excitons in gapped systems and plasmons in gapless systems are distinctly different types of excitations, the strongly polarized excitons in Au QRs surprisingly exhibit plasmon-like behaviors manifested in the shape-induced polarization, very intense absorption (~106 M-1 cm-1), and linear scaling relations with the AR, all of which resemble the behaviors of conventional metallic-state Au nanorods (i.e., gapless systems), but the QRs possess distinct gaps and very long excited-state lifetimes (10 to 2,122 ns), which hold promise in applications such as near-infrared solar energy utilization, hot carrier generation and transfer. The observation of plasmon-like behaviors from single-electron transitions in Au QRs elegantly bridges the distinct realms of single-electron and collective-electron excitations and may stimulate more research on excitonics and plasmonics.

The driving force behind tool-stone selection in the African Middle Stone Age.

In the Stone Age, the collection of specific rocks was the first step in tool making. Very little is known about the choices made during tool-stone acquisition. Were choices governed by the knowledge of, and need for, specific properties of stones? Or were the collected raw materials a mere by-product of the way people moved through the landscape? We investigate these questions in the Middle Stone Age (MSA) of southern Africa, analyzing the mechanical properties of tool-stones used at the site Diepkloof Rock Shelter. To understand knapping quality, we measure flaking predictability and introduce a physical model that allows calculating the relative force necessary to produce flakes from different rocks. To evaluate their quality as finished tools, we investigate their resistance during repeated use activities (scraping or cutting) and their strength during projectile impacts. Our findings explain tool-stone selection in two emblematic periods of the MSA, the Still Bay and Howiesons Poort, as being the result of a deep understanding of these mechanical properties. In both cases, people chose those rocks, among many others, that allowed the most advantageous trade-off between anticipated properties of finished tools and the ease of acquiring rocks and producing tools. The implications are an understanding of African MSA toolmakers as engineers who carefully weighed their choices taking into account workability and the quality of the tools they made.

Influence of viral genome properties on polymerase fidelity.

The first step of viral evolution takes place during genome replication via the error-prone viral polymerase. Among the mutants that arise through this process, only a few well-adapted variants will be selected by natural selection, renewing the viral genome population. Viral polymerase-mediated errors are thought to occur stochastically. However, accumulating evidence suggests that viral polymerase-mediated mutations are heterogeneously distributed throughout the viral genome. Here, we review work that supports this concept and provides mechanistic insights into how specific features of the viral genome could modulate viral polymerase-mediated errors. A predisposition to accumulate viral polymerase-mediated errors at specific loci in the viral genome may guide evolution to specific pathways, thus opening new directions of research to better understand viral evolutionary dynamics.

Accurate prediction of antibody function and structure using bio-inspired antibody language model.

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Antibody Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% nonredundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials. The BALMFold structure prediction server is freely available at https://beamlab-sh.com/models/BALMFold.

Nanocolloidal hydrogel mimics the structure and nonlinear mechanical properties of biological fibrous networks.

Fibrous networks formed by biological polymers such as collagen or fibrin exhibit nonlinear mechanical behavior. They undergo strong stiffening in response to weak shear and elongational strains, but soften under compressional strain, in striking difference with the response to the deformation of flexible-strand networks formed by molecules. The nonlinear properties of fibrous networks are attributed to the mechanical asymmetry of the constituent filaments, for which a stretching modulus is significantly larger than the bending modulus. Studies of the nonlinear mechanical behavior are generally performed on hydrogels formed by biological polymers, which offers limited control over network architecture. Here, we report an engineered covalently cross-linked nanofibrillar hydrogel derived from cellulose nanocrystals and gelatin. The variation in hydrogel composition provided a broad-range change in its shear modulus. The hydrogel exhibited both shear-stiffening and compression-induced softening, in agreement with the predictions of the affine model. The threshold nonlinear stress and strain were universal for the hydrogels with different compositions, which suggested that nonlinear mechanical properties are general for networks formed by rigid filaments. The experimental results were in agreement with an affine model describing deformation of the network formed by rigid filaments. Our results lend insight into the structural features that govern the nonlinear biomechanics of fibrous networks and provide a platform for future studies of the biological impact of nonlinear mechanical properties.

Structural and electronic trends of optical cycling centers in polyatomic molecules revealed by microwave spectroscopy of MgCCH, CaCCH, and SrCCH.

The unique optical cycling efficiency of alkaline earth metal-ligand molecules has enabled significant advances in polyatomic laser cooling and trapping. Rotational spectroscopy is an ideal tool for probing the molecular properties that underpin optical cycling, thereby elucidating the design principles for expanding the chemical diversity and scope of these platforms for quantum science. We present a comprehensive study of the structure and electronic properties in alkaline earth metal acetylides with high-resolution microwave spectra of 17 isotopologues of MgCCH, CaCCH, and SrCCH in their 2Σ+ ground electronic states. The precise semiexperimental equilibrium geometry of each species has been derived by correcting the measured rotational constants for electronic and zero-point vibrational contributions calculated with high-level quantum chemistry methods. The well-resolved hyperfine structure associated with the 1,2H, 13C, and metal nuclear spins provides further information on the distribution and hybridization of the metal-centered, optically active unpaired electron. Together, these measurements allow us to correlate trends in chemical bonding and structure with the electronic properties that promote efficient optical cycling essential to next-generation experiments in precision measurement and quantum control of complex polyatomic molecules.

Ultrastrong spinodoid alloys enabled by electrochemical dealloying and refilling.

We present an extreme case of composition-modulated nanomaterial formed by selective etching (dealloying) and electrochemical refilling. The product is a coarse-grain polycrystal consisting of two interwoven nanophases, with identical crystal structures and a cube-on-cube relationship, separated by smoothly curved semicoherent interfaces with high-density misfit dislocations. This material resembles spinodal alloys structurally, but its synthesis and composition modulation are spinodal-independent. Our Cu/Au "spinodoid" alloy demonstrates superior mechanical properties such as near-theoretical strength and single-phase-like behavior, owing to its fine composition modulation, large-scale coherence of crystal lattice, and smoothly shaped three-dimensional (3D) interface morphology. As a unique extension of spinodal alloy, the spinodoid alloy reported here reveals a number of possibilities to modulate the material's structure and composition down to the nanoscale, such that further improved properties unmatchable by conventional materials can be achieved.

Two-dimensional constrained chaos and industrial revolution cycles.

Since the 1760s, at least three industrial revolutions have occurred. To explain this phenomenon, we introduce two-dimensional (2D) constrained chaos. Using a model of innovation dynamics, we show that an industrial-revolution-like technology burst, driven by investment/saving motives for R&D activities, recurs about every one hundred years if the monopolistic use of a new technology lasts about 8 y.

Metabolic homeostasis and growth in abiotic cells.

Metabolism constitutes the core chemistry of life. How it began on the early Earth and whether it had a cellular origin are still uncertain. A leading hypothesis for life's origins postulates that metabolism arose from geochemical CO2-fixing pathways, driven by inorganic catalysts and energy sources, long before enzymes or genes existed. The acetyl-CoA pathway and the reductive tricarboxylic acid cycle are considered ancient reaction networks that hold relics of early carbon-fixing pathways. Although transition metals can promote many steps of these pathways, whether they form a functional metabolic network in abiotic cells has not been demonstrated. Here, we formulate a nonenzymatic carbon-fixing network from these pathways and determine its functional feasibility in abiotic cells by imposing fundamental physicochemical constraints. Using first principles, we show that abiotic cells can sustain a steady carbon-fixing cycle that performs a systemic function over a relatively narrow range of conditions. Furthermore, we find that in all feasible steady states, the operation of the cycle elevates the osmotic pressure, leading to volume expansion. These results suggest that achieving homeostatic metabolic states under prebiotic conditions was possible, but challenging, and volume growth was a fundamental property of early metabolism.

Multiple Origins of Bioluminescence in Beetles and Evolution of Luciferase Function.

Bioluminescence in beetles has long fascinated biologists, with diverse applications in biotechnology. To date, however, our understanding of its evolutionary origin and functional variation mechanisms remains poor. To address these questions, we obtained high-quality reference genomes of luminous and nonluminous beetles in 6 Elateroidea families. We then reconstructed a robust phylogenetic relationship for all luminous families and related nonluminous families. Comparative genomic analyses and biochemical functional experiments suggested that gene evolution within Elateroidea played a crucial role in the origin of bioluminescence, with multiple parallel origins observed in the luminous beetle families. While most luciferase-like proteins exhibited a conserved nonluminous amino acid pattern (TLA346 to 348) in the luciferin-binding sites, luciferases in the different luminous beetle families showed divergent luminous patterns at these sites (TSA/CCA/CSA/LVA). Comparisons of the structural and enzymatic properties of ancestral, extant, and site-directed mutant luciferases further reinforced the important role of these sites in the trade-off between acyl-CoA synthetase and luciferase activities. Furthermore, the evolution of bioluminescent color demonstrated a tendency toward hypsochromic shifts and variations among the luminous families. Taken together, our results revealed multiple parallel origins of bioluminescence and functional divergence within the beetle bioluminescent system.

Rational design of polymer-based particulate vaccine adjuvants.

Vaccination is considered one of the major milestones in modern medicine, facilitating the control and eradication of life-threatening infectious diseases. Vaccine adjuvants are a key component of many vaccines, serving to steer antigen-specific immune responses and increase their magnitude. Despite major advances in the field of adjuvant research over recent decades, our understanding of their mechanism of action remains incomplete. This hinders our capacity to further improve these adjuvant technologies, so addressing how adjuvants induce and control the induction of innate and adaptive immunity is a priority. Investigating how adjuvant physicochemical properties, such as size and charge, exert immunomodulatory effects can provide valuable insights and serve as the foundation for the rational design of vaccine adjuvants. Most clinically applied adjuvants are particulate in nature and polymeric particulate adjuvants present advantages due to stability, biocompatibility profiles, and flexibility in terms of formulation. These properties can impact on antigen release kinetics and biodistribution, cellular uptake and targeting, and drainage to the lymphatics, consequently dictating the induction of innate, cellular, and humoral adaptive immunity. A current focus is to apply rational design principles to the development of adjuvants capable of eliciting robust cellular immune responses including CD8+ cytotoxic T-cell and Th1-biased CD4+ T-cell responses, which are required for vaccines against intracellular pathogens and cancer. This review highlights recent advances in our understanding of how particulate adjuvants, especially polymer-based particulates, modulate immune responses and how this can be used as a guide for improved adjuvant design.

RLBind: a deep learning method to predict RNA-ligand binding sites.

Identification of RNA-small molecule binding sites plays an essential role in RNA-targeted drug discovery and development. These small molecules are expected to be leading compounds to guide the development of new types of RNA-targeted therapeutics compared with regular therapeutics targeting proteins. RNAs can provide many potential drug targets with diverse structures and functions. However, up to now, only a few methods have been proposed. Predicting RNA-small molecule binding sites still remains a big challenge. New computational model is required to better extract the features and predict RNA-small molecule binding sites more accurately. In this paper, a deep learning model, RLBind, was proposed to predict RNA-small molecule binding sites from sequence-dependent and structure-dependent properties by combining global RNA sequence channel and local neighbor nucleotides channel. To our best knowledge, this research was the first to develop a convolutional neural network for RNA-small molecule binding sites prediction. Furthermore, RLBind also can be used as a potential tool when the RNA experimental tertiary structure is not available. The experimental results show that RLBind outperforms other state-of-the-art methods in predicting binding sites. Therefore, our study demonstrates that the combination of global information for full-length sequences and local information for limited local neighbor nucleotides in RNAs can improve the model's predictive performance for binding sites prediction. All datasets and resource codes are available at https://github.com/KailiWang1/RLBind.