Spatio-temporal distribution and international context of bovine viral diarrhoea virus genetic diversity in France.

Bovine viral diarrhoea (BVD) is one of the most economically damaging livestock enzootic diseases in the world. BVD aetiological agents are three pestiviruses (BVDV-1, -2 and HoBi-like pestivirus), which exhibit high genetic diversity and complex transmission cycles. This considerably hampers the management of the disease, which is why eradication plans have been implemented in several countries. In France, a national plan has been in place since 2019. Our understanding of its impact on the distribution of BVDV genotypes is limited by the availability of French genetic data. Here, we conducted a molecular epidemiology study to refine our knowledge of BVDV genetic diversity in France, characterise its international relationships, and analyse national spatio-temporal genotypic distribution. We collated 1037 BVDV-positive samples throughout France between 2011 and 2023, with a greater sampling effort in two major cattle production areas. We developed a high-throughput sequencing protocol which we used to complete the 5'UTR genotyping of this collection. We show that two main BVDV-1 genotypes, 1e and 1b, account for 88% of genotyped sequences. We also identified seven other BVDV-1 genotypes occurring at low frequencies and three BVDV-2 samples (genotype 2c). Phylogenetic analyses indicate different worldwide distribution patterns between the two main BVDV-1 genotypes. Their relative frequencies present no major changes in France since the 1990s and few variations at the national scale. We also found some degree of local spatial structuring in western France. Overall, our results demonstrate the potential of large-scale sequence-based surveillance to monitor changes in the epidemiological situation of enzootic diseases.

Coconut milk allergenicity: Insight into reducing the affinity of coconut globulin to immunoglobulin E by atmospheric cold plasma.

Atmospheric cold plasma (ACP) presents a promising method for the sterilization of coconut milk and exhibits a modifying effect on coconut globulin (CG), the primary allergen in coconut milk. This study investigated the potential role of ACP treatment in mitigating the allergenic properties of coconut milk by examining changes in protein structure. ACP treatment induced structural alterations in CG, disrupting binding sites with immunoglobulin E (IgE). Consequently, this led to a reduction in the affinity between CG and IgE, evidenced by a decrease in Ka from 2.17 × 104/M to 0.64 × 104/M, thereby diminishing IgE-mediated allergic reactions. The findings from allergenic and cellular models further corroborated that ACP treatment decreased the allergenicity of CG by 55.18%, while inhibiting degranulation and the release of allergic mediators. This study presents an innovative methodology for producing hypoallergenic coconut milk, thereby expanding the applicability of ACP technology within the food industry.

[Population structure and fruiting ability of Rosa persica]. / 单叶蔷薇种群结构与结实能力.

We analyzed age structure and dynamics, spatial distribution patterns, and reproductive capabilities of four Rosa persica populations in Xinjiang, to evaluate the survival status of the species and explore the reasons behind its endangerment. The results showed that the populations had fewer individuals in the youngest (Ⅰ) and oldest (Ⅵ-Ⅷ) age classes, with a predominance of middle-aged individuals, resulting in an irregular pyramid-shaped distribution, described as "high in the middle, low on both sides". The populations were generally growing, but were susceptible to external environmental disturbances (Vpi'＞0, Pmax＞0). The mortality rate (qx) and vanish rate (Kx) peaked at age Ⅴ, leading to a sharp decline in plant abundance. The life expectancy (ex) decreased progressively with the increases of age class, reaching its lowest at age Ⅷ, which indicated minimal vitality at this stage. A time sequence analysis predicted a future dominance of individuals at age Ⅴ-Ⅷ, suggesting an aging trend. Spatially, the four populations were predominantly clumped, with the intensity of clumping ranked from highest to lowest as P4, P3, P1, and P2. P3 and P4 exhibited better reproductive capabilities than P1 and P2. There was a significant positive correlation between hundred-fruit weight and plant height and crown width, and between total seed number and crown width and hundred-fruit weight.

Genetic and phenotypic evidence suggest the existence of indigenous olive population of wild var. sylvestris in the Carmel coast, southern Levant.

BACKGROUND: Populations of Olea europaea subsp. europaea var. sylvestris, the ancestor of cultivated olives, are scattered across the Mediterranean Basin. However, after millennia of possible hybridization with cultivated varieties, the genetic identity of many of these populations remain questionable. In the southern Levant, the plausible primary domestication center of olives, many of the naturally growing olive (NGOs) are considered feral, having developed from nearby olive groves. Here, we investigated the genetic identity of NGOs population in the Carmel region, hypothesizing that their specific location, which limit anemophily, provided an opportunity for the persistence of genuine var. sylvestris. RESULTS: We mapped more than 1,000 NGOs on the Kurkar ridge along the Carmel coast, within and outside the residential area of Atlit and used simple sequence repeats of 14 loci to assess the spatial genetic structure of 129 NGOs. Genetic diversity parameters and genetic distances between NGO and cultivated olives, as well as phenotypic and morphometric analyses of their oil content and pits, respectively, indicated the presence of a genuine var. sylvestris population. However, NGOs within the residential area of Atlit and old settlements showed an intermediate admix genetic structure, indicating on hybridization with local varieties, a consequence of their proximity to cultivated trees. CONCLUSIONS: Integrating the results of genetic and phenotypic analyses we provide crucial evidence of the presence of a genuine var. sylvestris population in the southern Levant, in close geographical proximity to archaeological sites with the earliest evidence of olive exploitation in the ancient world. We supplement the results with recommendations for a conservation program that combines municipal requirements and the urgent need to preserve the largest population of var. sylvestris in the southern Levant.

The influence of social and spatial processes on the epidemiology of environmentally transmitted pathogens in wildlife: implications for management.

Social and spatial structures of host populations play important roles in pathogen transmission. For environmentally transmitted pathogens, the host space use interacts with both the host social structure and the pathogen's environmental persistence (which determines the time-lag across which two hosts can transmit). Together, these factors shape the epidemiological dynamics of environmentally transmitted pathogens. While the importance of both social and spatial structures and environmental pathogen persistence has long been recognized in epidemiology, they are often considered separately. A better understanding of how these factors interact to determine disease dynamics is required for developing robust surveillance and management strategies. Here, we use a simple agent-based model where we vary host mobility (spatial), host gregariousness (social) and pathogen decay (environmental persistence), each from low to high levels to uncover how they affect epidemiological dynamics. By comparing epidemic peak, time to epidemic peak and final epidemic size, we show that longer infectious periods, higher group mobility, larger group size and longer pathogen persistence lead to larger, faster growing outbreaks, and explore how these processes interact to determine epidemiological outcomes such as the epidemic peak and the final epidemic size. We identify general principles that can be used for planning surveillance and control for wildlife host-pathogen systems with environmental transmission across a range of spatial behaviour, social structure and pathogen decay rates. This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Local and regional processes drive distance decay in structure in a spatial multilayer plant-pollinator network.

Understanding spatial variation in species distribution and community structure is at the core of community ecology. Nevertheless, the effect of distance on metacommunity structure remains little studied. We examine how plant-pollinator community structure changes across geographical distances at a regional scale and disentangle its underlying local and regional processes. We use a multilayer network to represent linked plant-pollinator communities as a metacommunity in the Canary Islands. We used modularity (i.e. the extent to which the community is partitioned into groups of densely interacting species) to quantify distance decay in structure across space. In multilayer modularity, the same species can belong to different modules in different communities, and modules can span communities. This enabled quantifying how similarity in module composition varied with distance between islands. We developed three null models, each controlling for a separate component of the multilayer network, to disentangle the role of species turnover, interaction rewiring and local factors in driving distance decay in structure. We found a pattern of distance decay in structure, indicating that islands tended to share fewer modules with increasing distance. Species turnover (but not interaction rewiring) was the primary regional process triggering distance decay in structure. Local interaction structure also played an essential role in determining the structure similarity of communities at a regional scale. Therefore, local factors that determine species interactions occurring at a local scale drive distance decay in structure at a regional scale. Our work highlights the interplay between local and regional processes underlying community structure. The methodology, and specifically the null models, we developed provides a general framework for linking communities in space and testing different hypotheses regarding the factors generating spatial structure.

Evaluation of thermal effects on urban road spatial structure: A case study of Xuzhou, China.

Urban heat islands (UHI) are important environmental issue in cities where urban spatial structure has been proven to play an important role in alleviating UHI effects. The relationship between land surface temperature and urban spatial structures has been explored, providing strong support for their cooling effects. Urban roads are the skeleton of urban spatial structures, with obvious spatial structure characteristics; however, research on the relationship between roads and the thermal environment has been mostly focused at the micro and meso level, lacking exploration at the macro spatial structure scale. Xuzhou-a typical average-sized city in China-was selected as the research object and the road system as the carrier. The thermal environmental effects of road elements such as their structural attributes, geometric attributes and unique construction attributes were quantitatively analyzed using geographically weighted regression analysis. The results revealed that 1) the contribution of roads in the study area to the UHI effect is relatively stable; therefore, this area should become an important cooling space to decompose UHI patch connectivity and thus decrease the UHI effect. 2) the self-organizing structural characteristics of urban roads affect their thermal environments where in the straightness of the road structure and road thermal environment showed a clear overall negative correlation And 3) the length and width of the road segments had negative and positive effects on the thermal environment, respectively. The green coverage of the roads has a global negative effect on the thermal environment, but shows obvious spatial non-stationarity. Therefore, green measures must be implemented in different regions. The results here provide a quantitative basis for urban road system planning and urban form management and control that incorporates thermal environment improvements, as well as a reference for the study of urban thermal environments under different spatial forms and planning control systems in other countries and regions.

The co-location of CD14+APOE+ cells and MMP7+ tumour cells contributed to worse immunotherapy response in non-small cell lung cancer.

Intra-tumour immune infiltration is a crucial determinant affecting immunotherapy response in non-small cell lung cancer (NSCLC). However, its phenotype and related spatial structure have remained elusive. To overcome these restrictions, we undertook a comprehensive study comprising spatial transcriptomic (ST) data (28 712 spots from six samples). We identified two distinct intra-tumour infiltration patterns: immune exclusion (characterised by myeloid cells) and immune activation (characterised by plasma cells). The immune exclusion and immune activation signatures showed adverse and favourable roles in NSCLC patients' survival, respectively. Notably, CD14+APOE+ cells were recognised as the main cell type in immune exclusion samples, with increased epithelial‒mesenchymal transition and decreased immune activities. The co-location of CD14+APOE+ cells and MMP7+ tumour cells was observed in both ST and bulk transcriptomics data, validated by multiplex immunofluorescence performed on 20 NSCLC samples. The co-location area exhibited the upregulation of proliferation-related pathways and hypoxia activities. This co-localisation inhibited T-cell infiltration and the formation of tertiary lymphoid structures. Both CD14+APOE+ cells and MMP7+ tumour cells were associated with worse survival. In an immunotherapy cohort from the ORIENT-3 clinical trial, NSCLC patients who responded unfavourably exhibited higher infiltration of CD14+APOE+ cells and MMP7+ tumour cells. Within the co-location area, the MK, SEMA3 and Macrophage migration inhibitory factor (MIF) signalling pathway was most active in cell‒cell communication. This study identified immune exclusion and activation patterns in NSCLC and the co-location of CD14+APOE+ cells and MMP7+ tumour cells as contributors to immune resistance.

3D printing for constructing biocarriers using sodium alginate/ε-poly-l-lysine ink: Enhancing microbial enrichment for efficient nitrogen removal in wastewater.

The microbial enrichment of traditional biocarriers is limited due to the inadequate consideration of spatial structure and surface charging characteristics. Here, capitalizing on the ability of 3D printing technology to fabricate high-resolution materials, we further designed a positively charged sodium alginate/ε-poly-l-lysine (SA/ε-PL) printing ink, and the 3D printed biocarriers with ideal pore structure and rich positive charge were constructed to enhance the microbial enrichment. The rheological and mechanical tests confirmed that the developed SA/ε-PL ink could simultaneously satisfy the smooth extrusion for printing process and the maintenance of 3D structure. The utilization of the ε-PL secondary cross-linking strategy reinforced the 3D mechanical structure and imparted the requisite physical properties for its application as a biocarrier. Compared with traditional sponge carriers, 3D printed biocarrier had a faster initial attachment rate and a higher biomass of 14.58 ± 1.18 VS/cm3, and the nitrogen removal efficiency increased by 53.9 %. Besides, due to the superior electrochemical properties and biocompatibility, the 3D printed biocarriers effectively enriched the electroactive denitrifying bacteria genus Trichococcus, thus supporting its excellent denitrification performance. This study provided novel insights into the development of new functional biocarriers in the wastewater treatment, thereby providing scientific guidance for practical engineering.

Influence of Solvent Polarity on the Conformer Ratio of Bicalutamide in Saturated Solutions: Insights from NOESY NMR Analysis and Quantum-Chemical Calculations.

The study presents a thorough and detailed analysis of bicalutamide's structural and conformational properties. Quantum chemical calculations were employed to explore the conformational properties of the molecule, identifying significant energy differences between conformers. Analysis revealed that hydrogen bonds stabilise the conformers, with notable variations in torsion angles. Conformers were classified into 'closed' and 'open' types based on the relative orientation of the cyclic fragments. NOE spectroscopy in different solvents (CDCl3 and DMSO-d6) was used to study the conformational preferences of the molecule. NOESY experiments provided the predominance of 'closed' conformers in non-polar solvents and a significant presence of 'open' conformers in polar solvents. The proportions of open conformers were 22.7 ± 3.7% in CDCl3 and 59.8 ± 6.2% in DMSO-d6, while closed conformers accounted for 77.3 ± 3.7% and 40.2 ± 6.2%, respectively. This comprehensive study underscores the solvent environment's impact on its structural behaviour. The findings significantly contribute to a deeper understanding of conformational dynamics, stimulating further exploration in drug development.

Signatures of selective sweeps in continuous-space populations.

Selective sweeps describe the process by which an adaptive mutation arises and rapidly fixes in the population, thereby removing genetic variation in its genomic vicinity. The expected signatures of selective sweeps are relatively well understood in panmictic population models, yet natural populations often extend across larger geographic ranges where individuals are more likely to mate with those born nearby. To investigate how such spatial population structure can affect sweep dynamics and signatures, we simulated selective sweeps in populations inhabiting a two-dimensional continuous landscape. The maximum dispersal distance of offspring from their parents can be varied in our simulations from an essentially panmictic population to scenarios with increasingly limited dispersal. We find that in low-dispersal populations, adaptive mutations spread more slowly than in panmictic ones, while recombination becomes less effective at breaking up genetic linkage around the sweep locus. Together, these factors result in a trough of reduced genetic diversity around the sweep locus that looks very similar across dispersal rates. We also find that the site frequency spectrum around hard sweeps in low-dispersal populations becomes enriched for intermediate-frequency variants, making these sweeps appear softer than they are. Furthermore, haplotype heterozygosity at the sweep locus tends to be elevated in low-dispersal scenarios as compared to panmixia, contrary to what we observe in neutral scenarios without sweeps. The haplotype patterns generated by these hard sweeps in low-dispersal populations can resemble soft sweeps from standing genetic variation that arose from substantially older alleles. Our results highlight the need for better accounting for spatial population structure when making inferences about selective sweeps.

Theoretical analyses for the evolution of biogenic volatile organic compounds (BVOC) emission strategy.

Plants emit biogenic volatile organic compounds (BVOCs) as signaling molecules, playing a crucial role in inducing resistance against herbivores. Neighboring plants that eavesdrop on BVOC signals can also increase defenses against herbivores or alter growth patterns to respond to potential risks of herbivore damage. Despite the significance of BVOC emissions, the evolutionary rationales behind their release and the factors contributing to the diversity in such emissions remain poorly understood. To unravel the conditions for the evolution of BVOC emission, we developed a spatially explicit model that formalizes the evolutionary dynamics of BVOC emission and non-emission strategies. Our model considered two effects of BVOC signaling that impact the fitness of plants: intra-individual communication, which mitigates herbivore damage through the plant's own BVOC signaling incurring emission costs, and inter-individual communication, which alters the influence of herbivory based on BVOC signals from other individuals without incurring emission costs. Employing two mathematical models-the lattice model and the random distribution model-we investigated how intra-individual communication, inter-individual communication, and spatial structure influenced the evolution of BVOC emission strategies. Our analysis revealed that the increase in intra-individual communication promotes the evolution of the BVOC emission strategy. In contrast, the increase in inter-individual communication effect favors cheaters who benefit from the BVOCs released from neighboring plants without bearing the costs associated with BVOC emission. Our analysis also demonstrated that the narrower the spatial scale of BVOC signaling, the higher the likelihood of BVOC evolution. This research sheds light on the intricate dynamics governing the evolution of BVOC emissions and their implications for plant-plant communication.

The evolutionary cost of homophily: social stratification facilitates stable variant coexistence and increased rates of evolution in host-associated pathogens.

Coexistence of multiple strains of a pathogen in a host population can present significant challenges to vaccine development or treatment efficacy. Here we discuss a novel mechanism that can increase rates of long-lived strain polymorphism, rooted in the presence of social structure in a host population. We show that social preference of interaction, in conjunction with differences in immunity between host subgroups, can exert varying selection pressure on pathogen strains, creating a balancing mechanism that supports stable viral coexistence, independent of other known mechanisms. We use population genetic models to study rates of pathogen heterozygosity as a function of population size, host population composition, mutant strain fitness differences and host social preferences of interaction. We also show that even small periodic epochs of host population stratification can lead to elevated strain coexistence. These results are robust to varying social preferences of interaction, overall differences in strain fitnesses, and spatial heterogeneity in host population composition. Our results highlight the role of host population social stratification in increasing rates of pathogen strain diversity, with effects that should be considered when designing policies or treatments with a long-term view of curbing pathogen evolution.

Collective intelligence facilitates emergent resource partitioning through frequency-dependent learning.

Deciding where to forage must not only account for variations in habitat quality but also where others might forage. Recent studies have suggested that when individuals remember recent foraging outcomes, negative frequency-dependent learning can allow them to avoid resources exploited by others (indirect competition). This process can drive the emergence of consistent differences in resource use (resource partitioning) at the population level. However, indirect cues of competition can be difficult for individuals to sense. Here, we propose that information pooling through collective decision-making-i.e. collective intelligence-can allow populations of group-living animals to more effectively partition resources relative to populations of solitary animals. We test this hypothesis by simulating (i) individuals preferring to forage where they were recently successful and (ii) cohesive groups that choose one resource using a majority rule. While solitary animals can partially avoid indirect competition through negative frequency-dependent learning, resource partitioning is more likely to emerge in populations of group-living animals. Populations of larger groups also better partition resources than populations of smaller groups, especially in environments with more choices. Our results give insight into the value of long- versus short-term memory, home range sizes and the evolution of specialization, optimal group sizes and territoriality. This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.

Formation of Amyloid-Like Conformational States of ß-Structured Membrane Proteins on the Example of OMPF Porin from the Yersinia pseudotuberculosis Outer Membrane.

The work presents results of the in vitro and in silico study of formation of amyloid-like structures under harsh denaturing conditions by non-specific OmpF porin of Yersinia pseudotuberculosis (YpOmpF), a membrane protein with ß-barrel conformation. It has been shown that in order to obtain amyloid-like porin aggregates, preliminary destabilization of its structure in a buffer solution with acidic pH at elevated temperature followed by long-term incubation at room temperature is necessary. After heating at 95°C in a solution with pH 4.5, significant conformational rearrangements are observed in the porin molecule at the level of tertiary and secondary structure of the protein, which are accompanied by the increase in the content of total ß-structure and sharp decrease in the value of characteristic viscosity of the protein solution. Subsequent long-term exposure of the resulting unstable intermediate YpOmpF at room temperature leads to formation of porin aggregates of various shapes and sizes that bind thioflavin T, a specific fluorescent dye for the detection of amyloid-like protein structures. Compared to the initial protein, early intermediates of the amyloidogenic porin pathway, oligomers, have been shown to have increased toxicity to the Neuro-2aCCL-131™ mouse neuroblastoma cells. The results of computer modeling and analysis of the changes in intrinsic fluorescence during protein aggregation suggest that during formation of amyloid-like aggregates, changes in the structure of YpOmpF affect not only the areas with an internally disordered structure corresponding to the external loops of the porin, but also main framework of the molecule, which has a rigid spatial structure inherent to ß-barrel.

Blessing or curse? The role of digital technology innovation in carbon emission efficiency.

Digital technology advancement provides a significant impetus to achieve China's "dual-carbon" goals, yet it also gives rise to a series of challenges. Therefore, studying the relationship between digital technology innovation and carbon emission efficiency is of paramount importance. This study theoretically analyzes and empirically tests the influence of digital technology innovation (DTI) on total factor carbon emission efficiency (TFCE) using panel data from 268 Chinese cities between 2006 and 2021. The results indicate that: (1) DTI exhibits a "U-shaped" pattern on urban TFCE, with a decrease followed by an increase. (2) Conventional technological innovation (TI) also displays a "U-shaped" relationship with TFCE, with the turning point occurring earlier than that of DTI. DTI surpasses TI in bringing about later-stage improvements in carbon emission efficiency. (3) Mechanism tests reveal that digital technology innovation indirectly affects TFCE through energy effects, technological effects, structural effects, and regulatory effects. (4) The impact of DTI on urban TFCE varies significantly due to differences in geographical location and resource endowments. (5) The development of urban polycentricity advances the turning point at which DTI enhances TFCE while amplifying both the initial "pro-carbon" effect and the subsequent "carbon reduction" effect of DTI. (6) DTI has a spatial spillover effect on urban TFCE. This study provides empirical evidence and policy recommendations for policymakers to advance the digitalization, greening, and decarbonization transformation of cities.

Multiscale selection in spatially structured populations.

The spatial structure of populations is key to many (eco-)evolutionary processes. In such cases, the strength and sign of selection on a trait may depend on the spatial scale considered. An example is the evolution of altruism: selection in local environments often favours cheaters over altruists, but this can be outweighed by selection at larger scales, favouring clusters of altruists over clusters of cheaters. For populations subdivided into distinct groups, this effect is described formally by multilevel selection theory. However, many populations do not consist of non-overlapping groups but rather (self-)organize into other ecological patterns. We therefore present a mathematical framework for multiscale selection. This framework decomposes natural selection into two parts: local selection, acting within environments of a certain size, and interlocal selection, acting among them. Varying the size of the local environments subsequently allows one to measure the contribution to selection of each spatial scale. To illustrate the use of this framework, we apply it to models of the evolution of altruism and pathogen transmissibility. The analysis identifies how and to what extent ecological processes at different spatial scales contribute to selection and compete, thus providing a rigorous underpinning to eco-evolutionary intuitions.

The Stability of Competitive Metacommunities Is Insensitive to Dispersal Connectivity in a Fluctuating Environment.

AbstractMaintaining the stability of ecological communities is critical for conservation, yet we lack a clear understanding of what attributes of metacommunity structure control stability. Some theories suggest that greater dispersal promotes metacommunity stability by stabilizing local populations, while others suggest that dispersal synchronizes fluctuations across patches and leads to global instability. These effects of dispersal on stability may be mediated by metacommunity structure: the number of patches, the pattern of connections across patches, and levels of spatiotemporal correlation in the environment. Thus, we need theory to investigate metacommunity dynamics under different spatial structures and ecological scenarios. Here, we use simulations to investigate whether stability is primarily affected by connectivity, including dispersal rate and topology of connectivity network, or by mechanisms related to the number of patches. We find that in competitive metacommunities with environmental stochasticity, network topology has little effect on stability on the metacommunity scale even while it could change spatial diversity patterns. In contrast, the number of connected patches is the dominant factor promoting stability through averaging stochastic fluctuations across more patches, rather than due to more habitat heterogeneity per se. These results broaden our understanding of how metacommunity structure changes metacommunity stability, which is relevant for designing effective conservation strategies.

Spatiotemporal variations and influencing factors of methane emissions from livestock in China: A spatial econometric analysis.

In recent years, China has been implementing policies to improve the livestock industry in response to the global trend toward green and low-carbon development. These policies include the establishment of demonstration zones for high-standard agriculture, the relocation of farms to the north, etc. This study aims to investigate the impact of changes in the spatial structure of the livestock industry on methane emissions. It used panel data from 31 provinces in China from 2001 to 2021 and applied the IPCC methodology to quantify methane emissions at both the national and provincial levels. In addition, a spatial econometric model was used to analyze the impact of changes in the spatial structure of the livestock industry on methane emissions. The results show that methane from livestock in China decreased from 13.85 million tons in 2001 to 11.82 million tons in 2021. In addition, methane emissions from livestock in China show a significant spatial gradient and correlation. The Southwest has the highest methane emissions, accounting for 24 % of the total emissions. After controlling for spatial correlation and other factors in the model, it was found that the spatial structure of the livestock industry has a different influence on methane emissions both in the province and in neighboring provinces. To improve methane emission efficiency in the future, policies such as establishing functional zones for livestock farming, strengthening technological innovation and sharing for green development in agriculture, and promoting the optimization of agricultural and rural management structures should be implemented.

Emergent antibiotic persistence in a spatially structured synthetic microbial mutualism.

Antibiotic persistence (heterotolerance) allows a subpopulation of bacteria to survive antibiotic-induced killing and contributes to the evolution of antibiotic resistance. Although bacteria typically live in microbial communities with complex ecological interactions, little is known about how microbial ecology affects antibiotic persistence. Here, we demonstrated within a synthetic two-species microbial mutualism of Escherichia coli and Salmonella enterica that the combination of cross-feeding and community spatial structure can emergently cause high antibiotic persistence in bacteria by increasing the cell-to-cell heterogeneity. Tracking ampicillin-induced death for bacteria on agar surfaces, we found that E. coli forms up to 55 times more antibiotic persisters in the cross-feeding coculture than in monoculture. This high persistence could not be explained solely by the presence of S. enterica, the presence of cross-feeding, average nutrient starvation, or spontaneous resistant mutations. Time-series fluorescent microscopy revealed increased cell-to-cell variation in E. coli lag time in the mutualistic co-culture. Furthermore, we discovered that an E. coli cell can survive antibiotic killing if the nearby S. enterica cells on which it relies die first. In conclusion, we showed that the high antibiotic persistence phenotype can be an emergent phenomenon caused by a combination of cross-feeding and spatial structure. Our work highlights the importance of considering spatially structured interactions during antibiotic treatment and understanding microbial community resilience more broadly.