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Putative drivers of maritime Antarctic soil resistomes in the early 21st century:A baseline for monitoring environmental change and human influence
No full textAntibiotic resistance genes (ARGs) are present in all ecosystems and encode the defences that microorganisms have naturally evolved to defend themselves against antimicrobial agents. The use and synthesis of antibiotics by humans, however, has led to a proliferation of ARGs, resulting in their consideration as emerging environmental pollutants, even in some of the most pristine terrestrial ecosystems on Earth. Here we used shotgun metagenomics to characterise the abundance and diversity of ARGs in 29 maritime Antarctic soils collected in the 2007-2008 austral summer that varied in edaphic conditions and levels of human visitation. In total, 1831 ARGs were identified, spanning 29 naturally occurring ARGs that confer resistance to either single or multiple drug classes, such as glycopeptide, fluoroquinolone and tetracycline. The ARG profiles were not significantly associated with predicted levels of human visitation and harboured novel and potentially ancient ARGs, suggesting that these soils were relatively pristine. Furthermore, we observed that the abundance and diversity of ARGs was strongly associated with soil pH and mean annual surface air temperature (MASAT), as well as moisture content, C:N ratio, DOC and Mg concentration, albeit to a lesser extent. Our study provides a useful baseline for future studies, greatly expands the geographical coverage of Antarctic soil resistomes, and highlights putative environmental drivers of ARGs for the early 21st century including pH and MASAT, the latter of which is predicted to rise towards the end of this century.</p
Advances, challenges and prospects of holistic Multi-Omic approaches for enhanced protection against parasitic nematodes in food crops
No full textBackground and Aims: Plant parasitic nematodes (PPNs) are among the most damaging biotic stress, causing significant economic losses in staple food crops globally. Understanding the complex plant-nematode interaction mechanisms at molecular, cellular, physiological, and biochemical levels is important to minimise PPN-related crop damage. While plants have evolved diverse internal defence mechanisms to counteract the detrimental impacts of PPNs, relying solely on inherent mechanisms is often inadequate to avert yield loss. Advances in omics technologies have revolutionized the identification and characterization of molecular regulators involved in nematode resistance in plants. This review summarizes how multi-omic approaches are used to inform and develop protective strategies against cyst nematodes (CNs), root-knot nematodes (RKNs) and root-lesion nematodes (RLNs) in important food crops. Results: Multi‑Omic approaches have enabled the identification and characterization of molecular regulators, including resistance genes, quantitative trait loci (QTLs), marker-trait associations (MTAs) and nematode effectors, involved in plant responses to PPNs. These approaches provide a comprehensive view of the signalling pathways, transcriptional reprogramming and metabolic changes that occur during nematode infection. The integration of omics data has improved our understanding of the complex plant–nematode interaction and has informed the development of novel, targeted approaches for nematode management in food crops. Conclusion: Multi‑omics represents a powerful tool for understanding the plant–nematode interactions by uncovering the molecular basis of resistance to CNs, RKNs and RLNs. Advancing this knowledge will facilitate the development of durable and sustainable approaches to minimize PPN‑related crop damage and enhance food security.</p
Putative drivers of maritime Antarctic soil resistomes in the early 21st century:A baseline for monitoring environmental change and human influence
No full textAntibiotic resistance genes (ARGs) are present in all ecosystems and encode the defences that microorganisms have naturally evolved to defend themselves against antimicrobial agents. The use and synthesis of antibiotics by humans, however, has led to a proliferation of ARGs, resulting in their consideration as emerging environmental pollutants, even in some of the most pristine terrestrial ecosystems on Earth. Here we used shotgun metagenomics to characterise the abundance and diversity of ARGs in 29 maritime Antarctic soils collected in the 2007-2008 austral summer that varied in edaphic conditions and levels of human visitation. In total, 1831 ARGs were identified, spanning 29 naturally occurring ARGs that confer resistance to either single or multiple drug classes, such as glycopeptide, fluoroquinolone and tetracycline. The ARG profiles were not significantly associated with predicted levels of human visitation and harboured novel and potentially ancient ARGs, suggesting that these soils were relatively pristine. Furthermore, we observed that the abundance and diversity of ARGs was strongly associated with soil pH and mean annual surface air temperature (MASAT), as well as moisture content, C:N ratio, DOC and Mg concentration, albeit to a lesser extent. Our study provides a useful baseline for future studies, greatly expands the geographical coverage of Antarctic soil resistomes, and highlights putative environmental drivers of ARGs for the early 21st century including pH and MASAT, the latter of which is predicted to rise towards the end of this century.</p
Advances, challenges and prospects of holistic Multi-Omic approaches for enhanced protection against parasitic nematodes in food crops
No full textBackground and Aims: Plant parasitic nematodes (PPNs) are among the most damaging biotic stress, causing significant economic losses in staple food crops globally. Understanding the complex plant-nematode interaction mechanisms at molecular, cellular, physiological, and biochemical levels is important to minimise PPN-related crop damage. While plants have evolved diverse internal defence mechanisms to counteract the detrimental impacts of PPNs, relying solely on inherent mechanisms is often inadequate to avert yield loss. Advances in omics technologies have revolutionized the identification and characterization of molecular regulators involved in nematode resistance in plants. This review summarizes how multi-omic approaches are used to inform and develop protective strategies against cyst nematodes (CNs), root-knot nematodes (RKNs) and root-lesion nematodes (RLNs) in important food crops. Results: Multi‑Omic approaches have enabled the identification and characterization of molecular regulators, including resistance genes, quantitative trait loci (QTLs), marker-trait associations (MTAs) and nematode effectors, involved in plant responses to PPNs. These approaches provide a comprehensive view of the signalling pathways, transcriptional reprogramming and metabolic changes that occur during nematode infection. The integration of omics data has improved our understanding of the complex plant–nematode interaction and has informed the development of novel, targeted approaches for nematode management in food crops. Conclusion: Multi‑omics represents a powerful tool for understanding the plant–nematode interactions by uncovering the molecular basis of resistance to CNs, RKNs and RLNs. Advancing this knowledge will facilitate the development of durable and sustainable approaches to minimize PPN‑related crop damage and enhance food security.</p
Multifunctional Gelatin-Based Smart Films Integrating Thermochromic Encryption, Temperature-Regulated Photothermal Management, Reprocessability, and Biodegradability for Sustainable Applications
Full text linkMultifunctional gelatin-based smart films are engineered by incorporating hyperbranched polyglycerol (HBPG) as a plasticizer, dialdehyde β-cyclodextrin (Da-β-CD) as a crosslinker, and thermochromic microcapsules (TCMs). Structural analyses, including FTIR, XPS, and NMR, confirm the formation of covalent Schiff base linkages between Da-β-CD and gelatin, alongside hydrogen bonding reorganization facilitated by HBPG. The optimized film (GHBT2-CD) exhibits enhanced tensile strength (28.7 MPa), hydrophobicity (water contact angle of 116°), UV-blocking capability (>97%), and complete (100%) bacterial inhibition. Crucially, these films demonstrate programmable thermochromism for multilevel information encryption, enabling features such as laser-writing, temperature-gated message display (e.g., “SUST” decryption), and numeral switching (9→7→8) using TCMs with distinct transition temperatures (18°C, 28°C, and 38°C). Furthermore, they achieve dual-modal encryption by combining the intrinsic fluorescence of gelatin (emission at 340 nm) with thermochromism, which enables four-state displays (e.g., showing “Accept”). Additionally, the films provide self-adaptive temperature regulation: their black state below 28°C significantly boosts solar heating (achieving a ΔT of +27°C in a 4°C ambient environment), while their pale-yellow state above 28°C mitigates overheating (keeping the surface below 56°C in a 30°C ambient), an effect augmented by the phase-change latent heat buffering of the TCMs. Finally, the films embody closed-loop sustainability. The presence of dynamic Schiff base and hydrogen bond networks enables over 91% self-healing efficiency using stimuli like water, heat, or vapor, facilitates physical reprocessing, and allows for tunable degradation rates dependent on pH or soil conditions (complete degradation within 24 h at pH = 2, and within 12 days in sludge). This work pioneers an all-in-one smart materials platform that bridges optical security, thermal management, and the principles of a circular economy.</p
Predicting beef diet nutritional composition and intake from rumen metagenomic profiles
Full text linkKnowledge of diet composition and intake levels in beef cattle is valuable for post hoc feed traceability and for more accurate modelling of the diet impact on methane emissions and performance traits. However, a direct measure of this information can be costly and labour-intensive and is not always feasible. In this study, rumen metagenomic data combined with machine learning algorithms were used to predict diet type, nutritional composition, and intake levels. An external validation to assess the generalizability of the models was also performed. Rumen samples were collected from 142 animals belonging to two breeds, Luing (n = 70) and Charolais crossbred (n = 72), with 425.6 ± 43.5 d old and 461.9 ± 70.2 kg body weight. The animals participated in a 56-d feeding trial and were assigned to diets differing in forage-to-concentrate ratio, with 72 animals receiving a concentrate-based diet and 70 receiving a forage-based diet. Liquid ruminal contents were collected immediately postmortem and subsequently subjected to metagenomic sequencing. Based on these sequences, the relative abundance of microbial genes (MGs), microbial genera (MTs), and phyla were determined. The log-ratio between the abundances of Verrucomicrobia and Chlorobi discriminated diet type with an average classification accuracy of 0.86 ± 0.05, while using the log-ratio transformed abundances of 4769 MTs and MGs as predictors reached 0.90 ± 0.05. All this microbiome information was used in a random forest model to predict continuous values for nutritional diet components starch, crude protein, neutral and acid detergent fibre, and metabolizable and gross energy with external validation prediction accuracy values between 0.77 and 0.83. Microbiome features important for prediction of diet components such as fibre and starch included Mitsuokella, Selenomonas, and MGs involved in flagellar assembly and aminoacyl-tRNA biosynthesis. Microbiome data were more informative for predicting the feed composition than the amount of feed consumed, which reached a prediction accuracy of 0.27 ± 0.12 for dry matter intake (DMI). However, microbiome data can still be used as a screening tool to classify DMI into low, medium, or high with a classification accuracy of 0.74. Incorporating dietary information into linear phenotypic and genetic models to predict methane production (MP) and DMI reduced root mean square error (RMSE) by 26.9% and 9.6%, respectively, in the phenotypic model. In the genetic model, only MP showed a reduction in RMSE, with a 31% improvement. These findings highlight rumen microbiome data as a valuable tool for the post hoc prediction of feed composition in beef cattle
A genetic analysis of the causes of lamb mortality determined by an on-farm postmortem procedure
Full text linkLamb mortality is a major challenge in sheep production with significant implications for animal welfare and farm profitability. This study investigated the causes of lamb mortality within the first three days of life in a lowland outdoor lambing flock in the Scottish Borders, UK, over three lambing seasons (2021−2023). Dead lambs were collected from the pastures during checking rounds three times a day, and simple on-farm postmortems were conducted once a day. A total of 468 lamb postmortem examinations were conducted to classify the most likely cause of death as dystocia, starvation/mismothering/exposure (SME), stillbirth, other, or unknown causes. Overall mortality to three days of age was 12 %, with SME (28 %) and stillbirth (27 %) the most common causes, followed by dystocia (13 %). Single and triplet born lambs (p < 0.01) were most likely to die from dystocia compared to other litter sizes and the risk of death from SME increased with litter size (p < 0.01). Direct lamb heritability estimates for death by dystocia and stillbirth were moderate (0.31 and 0.27, respectively), indicating potential for improvement via genetic selection. However, heritability for SME was not significant, highlighting the increased influence of environmental factors for this cause of lamb death. The findings demonstrate that the use of simple postmortems could be used to increase the accuracy of selection for lamb survival in breeding programmes, through the integration of breeding values for specific causes of death. This would be most applicable in well-recorded nucleus flocks that are well connected to the rest of the breeding programme.</p
FEC Check: Development of a decision support tool to aid interpretation of gastrointestinal nematode faecal egg counts in sheep.
Full text linkBackground: Gastrointestinal nematode infections are ubiquitous in grazing livestock worldwide impacting animal health and production. Faecal egg count (FEC) is an accessible diagnostic test that can guide the need for treatment. However, interpretation of FECs can be challenging. Methods: A prototype decision support tool (DST) was developed using a ‘traffic light’-style gradient of potential clinical impact on sheep FEC results. Focus groups were conducted with farmers, livestock advisors and veterinary clinicians to examine the barriers to FEC uptake and provide feedback on the prototype tool. Results: Barriers to uptake for FEC testing included timeliness of reporting, lack of perceived need and knowledge gaps. The DST was well received at all focus groups, with simplicity and ease of use identified as key principles to drive uptake. At the 12 months post-launch, the DST had 1916 users. Limitations: Engagement with stakeholders with less familiarity with FECs may improve usability for a wider audience. Conclusion: The final DST developed here represents a practical resource to improve the interpretation of FEC results reported by farmers and other stakeholders. The initial uptake observed within the first year since launch is promising for the wider adoption of evidence-based parasite management.</p
Vertical Stratification Drives Divergent Spatial Trade-Offs Among Xylem Cell Types in Angiosperm Trees of a Mountain Forest in Eastern China
Full text linkVertical stratification in forests acts as an ecological filter, driving woody plants to evolve specialized survival strategies. Angiosperms, in particular, develop secondary xylem with three interdependent functions—water transport, mechanical support, and storage. Trade-offs between these functions vary with resource heterogeneity and environmental pressures. Balancing these functions is based on trade-offs in xylem structure, particularly in the xylem space allocation of vessels, fibers, and parenchyma fractions. However, how plants optimize these trade-offs along forest vertical strata remains unexplored. Anatomical methods were used to determine the fractions of vessels, fibers, and parenchyma in the secondary xylem of 119 individuals within a multilayered forest in eastern China. Ternary plots and standardized major axis analyses were employed to evaluate variations in trade-offs between vessel and fiber fractions, and between parenchyma and fiber fractions across different vertical strata. We found that trade-offs in spatial allocation among cell types occur in all vertical strata. For the fiber—vessel trade-off, canopy and understory trees followed a similar pattern, but canopy trees consistently maintained a higher vessel fraction. In contrast, the fiber—parenchyma trade-off was markedly stronger in understory trees. Our results illustrate that forest vertical stratification significantly influences trade-offs in xylem cell allocation, suggesting functional trade-offs of xylem depend on forest strata. These findings will help clarify how trees adapt to stresses associated with vertical forest strata
Constraints on the expansion of organic farming in highly productive regions
No full textCONTEXT: Uptake of organic farming falls short of stated sustainability targets, particularly in highly productive regions where adoption could mitigate environmental impacts of intensive farming. Several hypotheses have been advanced to explain the constraints on adoption, but these have not been assessed within an integrative, interdisciplinary framework.OBJECTIVE: The objective was to develop a conceptual framework linking existing hypotheses on the constraints to the uptake of organic farming in highly productive agricultural regions, to review the supporting evidence and, based on this, to propose solutions for increasing adoption.METHOD: An interdisciplinary team developed a nested hierarchical framework of ecological, agronomic, and socio-economic processes influencing adoption of organic farming. They critically examined existing literature in relation to hypotheses and identified potential solutions to enhance adoption.RESULTS AND CONCLUSIONS: We present a nested hypothesis hierarchy of interrelated constraints on organic conversion with special relevance to low uptake in highly productive regions dominated by arable crops. Certification constraints reflect fundamental needs for agroecological solutions for crop protection and nutrient supply, which are difficult to address in the absence of animal husbandry. The certification constraints give rise to agronomic constraints, driven by the greater divergence between organic and conventional crop rotations in such regions. While agronomic constraints are solvable, their solutions are limited by socio-economic constraints, including higher knowledge demands and opportunity costs for organic farmers, which current area-based policy-payments do not fully offset. Our review finds evidence for all constraint types, however, in highly productive areas the certification constraint need for alternative nutrient resources dominates, with downstream consequences for agronomic and socio-economic constraints. We demonstrate how our framework can guide solutions across the nested hierarchy: alleviating certification constraints through ecological intensification and alternative nutrient sources; addressing agronomic constraints by diversifying crop rotations; and overcoming socio-economic constraints by strengthening extension services and improving the spatial targeting of policy payments. Finally, we argue that persistent knowledge gaps call for stronger trans-disciplinary research to bridge the scale-related disconnect between academic research and farmer needs, as general approaches and small-scale experiments often fail to inform on-the-ground implementation.SIGNIFICANCE: Given that expansion of organic farming in the EU is stalling, there is substantial interest in identifying strategies to enhance its uptake, particularly in regions where adoption remains limited. This study provides a basis for future research, informing management decisions, and guiding policy development for fostering the expansion of organic farming, and hence advance the overarching goal of increasing agriculture’s sustainability