Emerging infectious disease: An underappreciated area of strategic concern for food security

Microbial laden mobile phones from international conference attendees pose potential risks to public health and biosecurity

INTRODUCTION

Mobile phones, contaminated with pathogenic microorganisms, have the potential to act as "trojan horses". The microbial signatures present on their surfaces most probably vary across different geographical regions. As a result, mobile phones belonging to international conference attendees may serve as a model for global microbial dissemination, posing potential risks to public health and biosecurity.

AIM

This study aimed to profile the microbes present on mobile phones belonging to delegates attending an international scientific conference through use of metagenomic shotgun DNA sequencing.

METHODS

Twenty mobile phones, representing ten different geographical zones from around the world, were swabbed and pooled together into ten geographical-specific samples for high definition next-generation DNA sequencing. WONCA council members were invited to participate and provided verbal consent. Following DNA extraction, next generation sequencing, to a depth of approximately 10Gbp per sample, was undertaken on a v1.5 Illumina NovaSeq6000 system. Bioinformatic analysis was performed via the CosmosID platform.

RESULTS

A total of 2204 microbial hits were accumulated across 20 mobile phones inclusive of 882 bacteria, 1229 viruses, 88 fungi and 5 protozoa. Of particular concern was the identification of 65 distinct antibiotic resistance genes and 86 virulence genes. Plant, animal and human pathogens, including ESKAPE and HACEK bacteria were found on mobile phones.

DISCUSSION/CONCLUSION

Mobile phones of international attendees are contaminated with many & varied microorganisms. Further research is required to characterize the risks these devices pose for biosecurity and public health. Development of new policies which appropriately address and prevent such risks maybe warranted.

Serological and Molecular Evidence of Bovine Leukemia Virus in Sheep Populations in the South of Iran

Bovine leukemia virus (BLV) is a neoplastic lymphosarcoma affecting cattle worldwide. Sheep, as one of the multiple host species for BLV, can transmit the virus to various animals and potentially to humans. Recognizing a gap in research, particularly in southern Iran, where the prevalence of BLV in sheep populations has not been investigated, this study aimed to fill this gap. One hundred blood samples were collected from seven flocks of sheep in the Fars province, Shiraz, southern Iran. Our study specifically investigated the prevalence of BLV in sheep populations in southern Iran, using serological and molecular analyses. Anti-gp51 IgG antibodies and proviral DNA were detected using ELISA and nested PCR, respectively. In this study, 37% of the 100 sheep tested positive for BLV IgG antibodies from the Fars province in southern Iran. The gag BLV gene with a band length of 385 bp was detected in 3% (3/100) of the samples. In this study, we examined the evidence of BLV in sheep from southern Iran. Control measures are needed to reduce infection in definitive hosts.

A preliminary validation of the public's emergency preparedness questionnaire for major emerging infectious diseases

BACKGROUND

Major emerging infectious diseases (MEIDs) have been considered as a pressing challenge to global public health. The world will face ongoing and increasing challenges posed by these diseases in the future. However, efficient emergency preparedness among the public could greatly reduce the risk of the spread of MEIDs. There is a scarcity of studies that evaluate the emergency preparedness of the public during MEIDs, which makes it difficult to clarify the emergency preparedness of the public during MEIDs. This study aims to validate the public's emergency preparedness questionnaire for MEIDs to assess the emergency preparedness of public during the outbreak of MEIDs.

METHODS

The questionnaire was constructed through a literature review, the Delphi method, and the analytic hierarchy process. From March to July 2023, experts were invited to conduct the content validity of the questionnaire, and then a cross-sectional survey online and in person was conducted to evaluate the validity and reliability of the questionnaire. Internal consistency, split-half reliability and test-retest reliability were used to test the reliability. Exploratory factor analysis was used to measure the construct validity.

RESULTS

The final questionnaire is composed of 48 items and five factors (cooperating with prevention and control work, preparing knowledge and coping strategies, securing supplies and equipment, preparing economic resources, and maintaining physical and mental health), and adopted the 5-point scoring method. The cumulative contribution of variance was 50.864%. The internal consistency, split-half reliability and test-retest reliability of the questionnaire were 0.953, 0.834 and 0.900, respectively.

CONCLUSIONS

The developed questionnaire exhibits strong reliability and validity for assessing public emergency preparedness during major emerging infectious diseases (MEIDs). Based on these findings, we recommend enhancing public education, implementing supportive policies, fostering community engagement, improving resource accessibility, and providing health support to better prepare the public for future outbreaks, thereby strengthening global public health security.

SIRE 2.0: a novel method for estimating polygenic host effects underlying infectious disease transmission, and analytical expressions for prediction accuracies

BACKGROUND

Genetic selection of individuals that are less susceptible to infection, less infectious once infected, and recover faster, offers an effective and long-lasting solution to reduce the incidence and impact of infectious diseases in farmed animals. However, computational methods for simultaneously estimating genetic parameters for host susceptibility, infectivity and recoverability from real-word data have been lacking. Our previously developed methodology and software tool SIRE 1.0 (Susceptibility, Infectivity and Recoverability Estimator) allows estimation of host genetic effects of a single nucleotide polymorphism (SNP), or other fixed effects (e.g. breed, vaccination status), for these three host traits using individual disease data typically available from field studies and challenge experiments. SIRE 1.0, however, lacks the capability to estimate genetic parameters for these traits in the likely case of underlying polygenic control.

RESULTS

This paper introduces novel Bayesian methodology and a new software tool SIRE 2.0 for estimating polygenic contributions (i.e. variance components and additive genetic effects) for host susceptibility, infectivity and recoverability from temporal epidemic data, assuming that pedigree or genomic relationships are known. Analytical expressions for prediction accuracies (PAs) for these traits are derived for simplified scenarios, revealing their dependence on genetic and phenotypic variances, and the distribution of related individuals within and between contact groups. PAs for infectivity are found to be critically dependent on the size of contact groups. Validation of the methodology with data from simulated epidemics demonstrates good agreement between numerically generated PAs and analytical predictions. Genetic correlations between infectivity and other traits substantially increase trait PAs. Incomplete data (e.g. time censored or infrequent sampling) generally yield only small reductions in PAs, except for when infection times are completely unknown, which results in a substantial reduction.

CONCLUSIONS

The method presented can estimate genetic parameters for host susceptibility, infectivity and recoverability from individual disease records. The freely available SIRE 2.0 software provides a valuable extension to SIRE 1.0 for estimating host polygenic effects underlying infectious disease transmission. This tool will open up new possibilities for analysis and quantification of genetic determinates of disease dynamics.

Inferring Tripartite Associations of Vector-Borne Plant Pathogens Using a Next-Generation Sequencing Approach

Phytoplasmas are a group of plant-pathogenic, cell-wall-less bacteria vectored primarily by leafhoppers (Hemiptera Cicadellidae), one of the most diverse families of insects. Despite the importance of documenting associations between phytoplasmas, their insect vectors, and plant hosts to prevent disease outbreaks, such knowledge is currently highly incomplete and largely neglects the diversity of the system in natural areas. Here, we used anchored hybrid enrichment (AHE) to recover the DNA of five plant genes (rbcL, matK, ITS1, ITS2, and trnH-psbA) in 58 phloem-feeding leafhoppers from around the world that had previously tested positive for phytoplasma infection. Using BLASTn and a strict filtering approach, we assigned taxonomic classifications to the plant sequences and tested for cophylogenetic signals between potential Deltocephalinae leafhopper vectors and their associated plants. We observed incongruence between plant and insect phylogenies. Many leafhopper species, including presumed grass specialists, fed on distantly related plant lineages; 66% of sampled leafhoppers fed on plants from at least two different orders. By disentangling phytoplasma-leafhopper-plant interactions, we identify locations at risk of phytoplasma disease outbreaks. Furthermore, the observed wide diet breadth raises questions about how phytoplasma infection may manipulate the feeding preference of their insect host and helps fill the gaps in understanding the ecology and diversification of the tripartite association.

HOST TRAITS EXPLAIN MORE VARIATION IN OCCUPANCY OF GENERALISTS THAN SPECIALISTS DUE TO STRONG HOST PREFERENCES AMONG GENERALISTS

The range of hosts a parasite can successfully occupy is partially determined by the niche breadth, that is, the set of environmental conditions necessary to maintain a stable population. Niche breadth is often quantified using host specificity, which encompasses the number of host species a parasite can exploit and the parasite's distribution among its hosts. Parasites with a wider niche breadth can potentially occupy more host species and are often more evenly distributed among hosts than parasites with a narrower niche breadth. However, parasites interact with potential hosts within the context of a geographic locality and the set of environmental characteristics associated with it. The extent to which environmental filters associated with host individuals and the geographic context explain variation in occupancy of parasites, and the extent to which variation in occupancy is associated with host range and specificity, is poorly understood. Using data from small mammals and ectoparasites in Vermont, I used a multiscale, multispecies occupancy model (MSOM) to (1) estimate ectoparasite occupancy at 10 geographic sites and on individual hosts within each site, (2) quantify the variation in occupancy explained by the site and host levels of the model using Bayesian R2, and (3) evaluate associations between explained variation and host range of ectoparasites. For ectoparasites collected from at least 4 different host species, I calculated structural specificity to determine the distribution of these parasites across the hosts, and β-specificity to evaluate changes in host use across habitats. Host range was significantly associated with host-level Bayesian R2: generalist parasites had more variation in occupancy explained by host-level covariates than specialist parasites. This result may be explained by differences in structural specificity: many generalists disproportionally occurred on a single-host species, suggesting that host characteristics act as habitat filters for these parasites. There were no significant associations between site-level Bayesian R2 and host specificity. However, some generalists demonstrated high β-specificity, suggesting these parasites may "switch" hosts, depending on host availability. These results highlight that the terms specialist and generalist are context dependent and may not accurately describe the niche breadth of parasite taxa. Understanding variation in host specificity as it pertains to potential habitat filters may be important for predicting which parasites can bypass host filters and "jump" to a novel host, which has implications for the surveillance and management of vector-borne diseases.

Direct Discrimination and Growth Estimation of Foodborne Bacteria in Raw Meat Using Electronic Nose

Evaluation concerning the presence of bacteria in meat products is mandatory for commercializing these goods. Although food bacteria detection is based on microbiological methods, these assays are usually laborious and time-consuming. In this paper, an electronic nose is used to differentiate Salmonella spp. (SA), Escherichia coli (EC), and Pseudomonas fluorescens (PF) inoculated in raw meat (beef, chicken, and pork) and incubated at 22 °C for 3 days. The obtained data were evaluated by principal component analysis (PCA) and different machine learning algorithms. From the graphical analysis of the PCA, on day 1, the clusters were close to each other for beef, chicken, and pork, while on days 2 and 3, more separated bacteria clusters were obtained regardless of the meat type, allowing for the discrimination of the samples for the latter days. To estimate the growth rates of the microorganisms, the distance between clusters was calculated and provided a pattern for the three bacteria, with the slowest-, moderate-, and fastest-growing being EC, SA, and PF, respectively. Concerning the machine learning algorithms, the accuracy varied from 93.8 to 100% for beef and chicken, while for pork, it varied from 75% to 100%. Thus, these results suggest that the proposed methodology based on electronic nose has the potential for the direct discrimination of bacteria in raw meat, with reduced analysis time, costs, and manipulating steps.

Investigation of Antimicrobial Compounds Produced by Endolichenic Fungi in Different Culture Media

Continuous use of synthetic fungicides has led to explosive emergence of fungicide-resistant microbes. Therefore, there are urgent needs for environmentally friendly antimicrobial agents with novel modes of action. This study investigated endolichenic fungi (ELF) as a source of antimicrobial compounds against various plant pathogens. We utilized an One Strain MAny Compounds (OSMAC) approach to enhance the chemical diversity of fourteen ELF. This involved cultivation of ELF in four growth media and subsequently assessing antimicrobial activities of culture extracts. Nearly half of the culture extracts exhibited antimicrobial activity against a Gram-positive bacterium, but showed minimal activity against Gram-negative bacteria tested. Notably, culture extracts from two ELF, Chaetomium globosum and Nodulisporium sp., demonstrated significant inhibitory effects against plant pathogenic fungi. LC-MS/MS-based metabolome profiling confirmed the presence of known bioactive compounds like cyclic dipeptides and chaetoglobosins. These findings highlight the effectiveness of combining OSMAC and metabolomics for identifying antimicrobial agents for agricultural use.

One Health Ethics and the Ethics of Zoonoses: A Silent Call for Global Action

This paper presents a critical review of key issues related to the emergence of new networks for the spread of zoonotic diseases amid the mass extinction of species. Zoonotic and infectious diseases account for approximately 70% of new and existing diseases affecting humans and animals. The initial section argues that the term "zoonoses" should not be confined to single-cause events within veterinary medicine. Instead, zoonoses should be viewed as complex, systemic phenomena shaped by interrelated factors, including environmental, sociocultural, and economic elements, influenced by anthropogenic climate change. The second section presents bioethical principles and potential strategies for those engaged in zoonotic disease prevention. The third section uses the slaughter of animals in disaster settings as a case study to illustrate the need for further clarification of normative and interspecies justice conflicts in One Health ethics. This section concludes with an outlook on "zoonoethics". Section four develops the analysis of the interlinked elements that trigger zoonoses and examines antimicrobial resistance (AMR) from an ethical and political standpoint, concluding with policy recommendations for addressing AMR. Section five offers a critical reflection, integrating contributions from zoonoethics, human ecology, and the ecotheological turn. Finally, section six concludes with a call to action and policy recommendations for an inclusive, intercultural, and gender-sensitive One Health approach.

Multiplex Detection of Foodborne Pathogens using 3D Nanostructure Swab and Deep Learning-Based Classification of Raman Spectra

Proactive management of foodborne illness requires routine surveillance of foodborne pathogens, which requires developing simple, rapid, and sensitive detection methods. Here, a strategy is presented that enables the detection of multiple foodborne bacteria using a 3D nanostructure swab and deep learning-based Raman signal classification. The nanostructure swab efficiently captures foodborne pathogens, and the portable Raman instrument directly collects the Raman signals of captured bacteria. a deep learning algorithm has been demonstrated, 1D convolutional neural network with binary labeling, achieves superior performance in classifying individual bacterial species. This methodology has been extended to mixed bacterial populations, maintaining accuracy close to 100%. In addition, the gradient-weighted class activation mapping method is used to provide an investigation of the Raman bands for foodborne pathogens. For practical application, blind tests are conducted on contaminated kitchen utensils and foods. The proposed technique is validated by the successful detection of bacterial species from the contaminated surfaces. The use of a 3D nanostructure swab, portable Raman device, and deep learning-based classification provides a powerful tool for rapid identification (≈5 min) of foodborne bacterial species. The detection strategy shows significant potential for reliable food safety monitoring, making a meaningful contribution to public health and the food industry.

Mapping African Swine Fever and Highly Pathogenic Avian Influenza Outbreaks along the Demilitarized Zone in the Korean Peninsula

The Korean Demilitarized Zone (DMZ) is one of the world's most preserved habitats for wild animals and migratory birds. The area also plays a major role in the spread of infectious animal diseases, in particular, African swine fever (ASF) and highly pathogenic avian influenza (HPAI). These outbreaks threaten the livelihood of local livestock farms, not infrequently. In this paper, we explore these relatively under-researched diseases by modeling and mapping ASF and HPAI risks in tandem using MaxEnt, a machine-learning algorithm. The results show robust predictive power with high area under the curve values, of 0.92 and 0.99, respectively. We found that precipitation from spring to early summer and solar radiation in winter were essential in explaining the potential distribution of ASF, but land use contributed little. Thus, understanding only wild boars' habitat preferences may not be sufficient in preventing ASF epidemics. HPAI risks were shaped by precipitation and mean temperature from winter to spring and land use. Areas with high ASF and HPAI risks were primarily found in forest and agricultural lands, respectively. The DMZ included many high-risk areas, indicating that the DMZ could lead to a broader regional spread of ASF and HPAI in the peninsula. Thus, our results highlight the essential role of cross-border collaboration and the combination of environmental and epidemiological insights in strategies to control ASF and HPAI risks within and surrounding the DMZ.

Earth at risk: An urgent call to end the age of destruction and forge a just and sustainable future

Human development has ushered in an era of converging crises: climate change, ecological destruction, disease, pollution, and socioeconomic inequality. This review synthesizes the breadth of these interwoven emergencies and underscores the urgent need for comprehensive, integrated action. Propelled by imperialism, extractive capitalism, and a surging population, we are speeding past Earth's material limits, destroying critical ecosystems, and triggering irreversible changes in biophysical systems that underpin the Holocene climatic stability which fostered human civilization. The consequences of these actions are disproportionately borne by vulnerable populations, further entrenching global inequities. Marine and terrestrial biomes face critical tipping points, while escalating challenges to food and water access foreshadow a bleak outlook for global security. Against this backdrop of Earth at risk, we call for a global response centered on urgent decarbonization, fostering reciprocity with nature, and implementing regenerative practices in natural resource management. We call for the elimination of detrimental subsidies, promotion of equitable human development, and transformative financial support for lower income nations. A critical paradigm shift must occur that replaces exploitative, wealth-oriented capitalism with an economic model that prioritizes sustainability, resilience, and justice. We advocate a global cultural shift that elevates kinship with nature and communal well-being, underpinned by the recognition of Earth's finite resources and the interconnectedness of its inhabitants. The imperative is clear: to navigate away from this precipice, we must collectively harness political will, economic resources, and societal values to steer toward a future where human progress does not come at the cost of ecological integrity and social equity.

The communication of artificial intelligence and deep learning in computer tomography image recognition of epidemic pulmonary infectious diseases

The objectives are to improve the diagnostic efficiency and accuracy of epidemic pulmonary infectious diseases and to study the application of artificial intelligence (AI) in pulmonary infectious disease diagnosis and public health management. The computer tomography (CT) images of 200 patients with pulmonary infectious disease are collected and input into the AI-assisted diagnosis software based on the deep learning (DL) model, "UAI, pulmonary infectious disease intelligent auxiliary analysis system", for lesion detection. By analyzing the principles of convolutional neural networks (CNN) in deep learning (DL), the study selects the AlexNet model for the recognition and classification of pulmonary infection CT images. The software automatically detects the pneumonia lesions, marks them in batches, and calculates the lesion volume. The result shows that the CT manifestations of the patients are mainly involved in multiple lobes and density, the most common shadow is the ground-glass opacity. The detection rate of the manual method is 95.30%, the misdetection rate is 0.20% and missed diagnosis rate is 4.50%; the detection rate of the DL-based AI-assisted lesion method is 99.76%, the misdetection rate is 0.08%, and the missed diagnosis rate is 0.08%. Therefore, the proposed model can effectively identify pulmonary infectious disease lesions and provide relevant data information to objectively diagnose pulmonary infectious disease and manage public health.

Bioinspired silver nanoparticle-based nanocomposites for effective control of plant pathogens: A review

Plant pathogens, including bacteria, fungi, and viruses, pose significant challenges to the farming community due to their extensive diversity, the rapidly evolving phenomenon of multi-drug resistance (MDR), and the limited availability of effective control measures. Amid mounting global pressure, particularly from the World Health Organization, to limit the use of antibiotics in agriculture and livestock management, there is increasing consideration of engineered nanomaterials (ENMs) as promising alternatives for antimicrobial applications. Studies focusing on the application of ENMs in the fight against MDR pathogens are receiving increasing attention, driven by significant losses in agriculture and critical knowledge gaps in this crucial field. In this review, we explore the potential contributions of silver nanoparticles (AgNPs) and their nanocomposites in combating plant diseases, within the emerging interdisciplinary arena of nano-phytopathology. AgNPs and their nanocomposites are increasingly acknowledged as promising countermeasures against plant pathogens, owing to their unique physicochemical characteristics and inherent antimicrobial properties. This review explores recent advancements in engineered nanocomposites, highlights their diverse mechanisms for pathogen control, and draws attention to their potential in antibacterial, antifungal, and antiviral applications. In the discussion, we briefly address three crucial dimensions of combating plant pathogens: green synthesis approaches, toxicity-environmental concerns, and factors influencing antimicrobial efficacy. Finally, we outline recent advancements, existing challenges, and prospects in scholarly research to facilitate the integration of nanotechnology across interdisciplinary fields for more effective treatment and prevention of plant diseases.

Antimicrobial Efficacy of Allium cepa and Zingiber officinale Against the Milk-Borne Pathogen Listeria monocytogenes

Listeria monocytogenes is an important food-borne pathogen that causes listeriosis and has a high case fatality rate despite its low incidence. Medicinal plants and their secondary metabolites have been identified as potential antibacterial substances, serving as replacements for synthetic chemical compounds. The present studies emphasize two significant medicinal plants, Allium cepa and Zingiber officinale, and their efficacy against L. monocytogenes. Firstly, a bacterial isolate was obtained from milk and identified through morphology and biochemical reactions. The species of the isolate were further confirmed through 16S rRNA analysis. Furthermore, polar solvents such as methanol and ethanol were used for the extraction of secondary metabolites from A. cepa and Z. officinale. Crude phytochemical components were identified using phytochemical tests, FTIR, and GC-MS. Moreover, the antibacterial activity of the crude extract and its various concentrations were tested against L. monocytogenes. Among all, A. cepa in methanolic extracts showed significant inhibitory activity. Since, the A. cepa for methanolic crude extract was used to perform autography to assess its bactericidal activity. Subsequently, molecular docking was performed to determine the specific compound inhibition. The docking results revealed that four compounds displayed strong binding affinity with the virulence factor Listeriolysin-O of L. monocytogenes. Based on the above results, it can be concluded that the medicinal plant A. cepa has potential antibacterial effects against L. monocytogenes, particularly targeting its virulence.

Cassava Witches' Broom Disease in Southeast Asia: A Review of Its Distribution and Associated Symptoms

Cassava witches' broom disease (CWBD) is one of the main diseases of cassava in Southeast Asia (SEA). Affected cassava plants show reduced internodal length and proliferation of leaves (phyllody) in the middle and top part of the plant, which results in reduced root yields of 50% or more. It is thought to be caused by phytoplasma; however, despite its widespread distribution in SEA still little is known about CWBD pathology. The overarching goal of this study was to review and corroborate published information on CWBD biology and epidemiology considering recent field observations. We report the following: (1) CWBD symptoms are conserved and persistent in SEA and are distinct from what has been reported as witches' broom in Argentina and Brazil. (2) In comparison with cassava mosaic disease, another major disease of cassava in SEA, symptoms of CWBD develop later. (3) Phytoplasma detected in CWBD-affected plants belong to different ribosomal groups and there is no association study available indicating phytoplasma as the causing agent of CWBD. These findings are essential clues for designing surveillance and management strategies and for future studies to better understand the biology, tissue localization and spatial spread of CWBD in SEA and other potential risk areas.

From sequences to species: Charting the phytoplasma classification and taxonomy in the era of taxogenomics

Phytoplasma taxonomy has been a topic of discussion for the last two and half decades. Since the Japanese scientists discovered the phytoplasma bodies in 1967, the phytoplasma taxonomy was limited to disease symptomology for a long time. The advances in DNA-based markers and sequencing improved phytoplasma classification. In 2004, the International Research Programme on Comparative Mycoplasmology (IRPCM)- Phytoplasma/Spiroplasma Working Team – Phytoplasma taxonomy group provided the description of the provisional genus ‘Candidatus Phytoplasma’ with guidelines to describe the new provisional phytoplasma species. The unintentional consequences of these guidelines led to the description of many phytoplasma species where species characterization was restricted to a partial sequence of the 16S rRNA gene alone. Additionally, the lack of a complete set of housekeeping gene sequences or genome sequences, as well as the heterogeneity among closely related phytoplasmas limited the development of a comprehensive Multi-Locus Sequence Typing (MLST) system. To address these issues, researchers tried deducing the definition of phytoplasma species using phytoplasmas genome sequences and the average nucleotide identity (ANI). In another attempts, a new phytoplasma species were described based on the Overall Genome relatedness Values (OGRI) values fetched from the genome sequences. These studies align with the attempts to standardize the classification and nomenclature of ‘Candidatus’ bacteria. With a brief historical account of phytoplasma taxonomy and recent developments, this review highlights the current issues and provides recommendations for a comprehensive system for phytoplasma taxonomy until phytoplasma retains ‘Candidatus’ status.

Assigning cause for emerging diseases of aquatic organisms

Resolving the cause of disease (= aetiology) in aquatic organisms is a challenging but essential goal, heightened by increasing disease prevalence in a changing climate and an interconnected world of anthropogenic pathogen spread. Emerging diseases play important roles in evolutionary ecology, wildlife conservation, the seafood industry, recreation, cultural practices, and human health. As we emerge from a global pandemic of zoonotic origin, we must focus on timely diagnosis to confirm aetiology and enable response to diseases in aquatic ecosystems. Those systems' resilience, and our own sustainable use of seafood, depend on it. Synchronising traditional and recent advances in microbiology that span ecological, veterinary, and medical fields will enable definitive assignment of risk factors and causal agents for better biosecurity management and healthier aquatic ecosystems.

Major Phytochemical Compounds, In Vitro Antioxidant, Antibacterial, and Antifungal Activities of Six Aqueous and Organic Extracts of Crocus sativus L. Flower Waste

PURPOSE

After being considered as a neglected product, agricultural waste is nowadays considered of paramount importance. It has become a source of many chemical compounds with industrial, pharmaceutical, and food applications. This study aims to evaluate the primary phytochemical content, the antioxidant properties, and the antimicrobial activities of different extracts of saffron flower waste (SFE) against bacterial and fungal strains involved in diverse pathologies in southern Morocco.

METHODS

Total phenolic and flavonoid contents were determined. The antioxidant potentials were assessed by DPPH, FRAP, and β-carotene assays. The antimicrobial activity against four bacteria and four fungi was also evaluated. The findings in terms of the relationships between phytochemical content and all activities were depicted by PCA analyses.

RESULTS

SFEs contained large amounts of phenolic and flavonoid compounds that contribute to the significant antioxidant activities. Diethyl ether (DE), n-Butanol (n-B), and Ethyl acetate (EA) fractions respectively exhibited more DPPH scavenging capacity, FRAP reducing power, and β-carotene bleaching inhibition. DE and EA have a remarkable effect mainly against Staphylococcus aureus strain, compared to Listeria monocytogenes, Escherichia coli and Klebsiella pneumoniae. Both SFEs showed antifungal antagonism towards key fungi species involved in post-harvest mold and crop yield losses. Botrytis cinerea was more susceptible than Fusarium solani, Penicillium expansum, and Penicillium digitatum.

CONCLUSION

These results reveal new data about extracts obtained from SFE that could be a potential source of natural antioxidant and antimicrobial agents opening new possibilities for their applications in the food system as a natural preservative and a sustainable alternative to conventional ingredients.

Molecular Detection of Southern Tomato Amalgavirus Prevalent in Tomatoes and Its Genomic Characterization with Global Evolutionary Dynamics

Southern tomato amalgavirus (STV) is a cryptic pathogen that is abundant in tomato production fields and intensifies the resurgence of tomato yellow stunt disease (ToYSD), together with other phytoviruses. Here, we mapped the geographical and genomic diversity, phylogenetics, and evolutionary dynamics of STV. We found that STV prevailed across China and Pakistan, with a maximum average rate of infection of 43.19% in Beijing, China, and 40.08% in Punjab, Pakistan. Subsequently, we amplified, cloned, and annotated the complete genome sequences of STV isolates from Solanum lycopersicum L. in China (OP548653 and OP548652) and Pakistan (MT066231) using Sanger and next-generation sequencing (NGS). These STV isolates displayed close evolutionary relationships with others from Asia, America, and Europe. Whole-genome-based molecular diversity analysis showed that STV populations had 33 haplotypes with a gene diversity (Hd) of 0.977 and a nucleotide diversity (π) of 0.00404. The genetic variability of RNA-dependent RNA-polymerase (RdRp) was higher than that of the putative coat protein (CP) p42. Further analysis revealed that STV isolates were likely to be recombinant but with a lower-to-moderate level of confidence. With a variable distribution pattern of positively and negatively selected sites, negative selection pressure predominantly acted on p42 and RdRp. These findings elaborated on the molecular variability and evolutionary trends among STV populations across major tomato-producing regions of the world.

The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond

The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them-the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.

Ecological super-spreaders drive host-range oscillations: Omicron and risk space for emerging infectious disease

The unusual genetic diversity of the Omicron strain has led to speculation about its origin. The mathematical modelling platform developed for the Stockholm Paradigm (SP) indicates strongly that it has retro-colonized humans from an unidentified nonhuman mammal, likely originally infected by humans. The relationship between Omicron and all other SARS-CoV-2 variants indicates oscillations among hosts, a core part of the SP. Such oscillations result from the emergence of novel variants following colonization of new hosts, replenishing and expanding the risk space for disease emergence. The SP predicts that pathogens colonize new hosts using pre-existing capacities. Those events are thus predictable to a certain extent. Novel variants emerge after a colonization and are not predictable. This makes it imperative to take proactive measures for anticipating emerging infectious diseases (EID) and mitigating their impact. The SP suggests a policy protocol, DAMA, to accomplish this goal. DAMA comprises: DOCUMENT to detect pathogens before they emerge in new places or colonize new hosts; ASSESS to determine risk; MONITOR to detect changes in pathogen populations that increase the risk of outbreaks and ACT to prevent outbreaks when possible and minimize their impact when they occur.

Current Scenario of Pathogen Detection Techniques in Agro-Food Sector

Over the past-decade, agricultural products (such as vegetables and fruits) have been reported as the major vehicles for foodborne diseases, which are limiting food resources. The spread of infectious diseases due to foodborne pathogens poses a global threat to human health and the economy. The accurate and timely detection of infectious disease and of causative pathogens is crucial in the prevention and treatment of disease. Negligence in the detection of pathogenic substances can be catastrophic and lead to a pandemic. Despite the revolution in health diagnostics, much attention has been paid to the agro-food sector regarding the detection of food contaminants (such as pathogens). The conventional analytical techniques for pathogen detection are reliable and still in operation. However, laborious procedures and time-consuming detection via these approaches emphasize the need for simple, easy-to-use, and affordable detection techniques. The rapid detection of pathogens from food is essential to avoid the morbidity and mortality originating from the suboptimal nature of empiric pathogen treatment. This review critically discusses both the conventional and emerging bio-molecular approaches for pathogen detection in agro-food.

Explosive networking: The role of adaptive host radiations and ecological opportunity in a species-rich host-parasite assembly

Many species-rich ecological communities emerge from adaptive radiation events. Yet the effects of adaptive radiation on community assembly remain poorly understood. Here, we explore the well-documented radiations of African cichlid fishes and their interactions with the flatworm gill parasites Cichlidogyrus spp., including 10,529 reported infections and 477 different host-parasite combinations collected through a survey of peer-reviewed literature. We assess how evolutionary, ecological, and morphological parameters determine host-parasite meta-communities affected by adaptive radiation events through network metrics, host repertoire measures, and network link prediction. The hosts' evolutionary history mostly determined host repertoires of the parasites. Ecological and evolutionary parameters predicted host-parasite interactions. Generally, ecological opportunity and fitting have shaped cichlid-Cichlidogyrus meta-communities suggesting an invasive potential for hosts used in aquaculture. Meta-communities affected by adaptive radiations are increasingly specialised with higher environmental stability. These trends should be verified across other systems to infer generalities in the evolution of species-rich host-parasite networks.

Food security and emerging infectious disease: risk assessment and risk management

Climate change, emerging infectious diseases (EIDs) and food security create a dangerous nexus. Habitat interfaces, assumed to be efficient buffers, are being disrupted by human activities which in turn accelerate the movement of pathogens. EIDs threaten directly and indirectly availability and access to nutritious food, affecting global security and human health. In the next 70 years, food-secure and food-insecure countries will face EIDs driving increasingly unsustainable costs of production, predicted to exceed national and global gross domestic products. Our modern challenge is to transform this business as usual and embrace an alternative vision of the biosphere formalized in the Stockholm paradigm (SP). First, a pathogen-centric focus shifts our vision of risk space, determining how pathogens circulate in realized and potential fitness space. Risk space and pathogen exchange are always heightened at habitat interfaces. Second, apply the document-assess-monitor-act (DAMA) protocol developing strategic data for EID risk, to be translated, synthesized and broadcast as actionable information. Risk management is realized through targeted interventions focused around information exchanged among a community of scientists, policy practitioners of food and public health security and local populations. Ultimately, SP and DAMA protect human rights, supporting food security, access to nutritious food, health interventions and environmental integrity.

Evidence of bovine leukemia virus circulating in sheep and buffaloes in Colombia: insights into multispecies infection

Bovine leukemia virus (BLV) is the causative agent of leukemia/lymphoma in cattle. However, previous evidence has shown its presence in other species of livestock as well as in humans, suggesting that other species can be accidental hosts of the virus. In viral infections, receptors that are common to different animal species are proposed to be involved in cross-species infections. For BLV, AP3D1 has been proposed to be its receptor, and this protein is conserved in most mammalian species. In Colombia, BLV has been reported in cattle with high prevalence rates, but there has been no evidence of BLV infections in other animal species. In this study, we tested for the virus in sheep (n = 44) and buffaloes (n = 61) from different regions of Colombia by nested PCR, using peripheral blood samples collected from the animals. BLV was found in 25.7% of the animals tested (12 buffaloes and 15 sheep), and the results were confirmed by Sanger sequencing. In addition, to gain more information about the capacity of the virus to infect these species, the predicted interactions of AP3D1 of sheep and buffaloes with the BLV-gp51 protein were analyzed in silico. Conserved amino acids in the binding domains of the proteins were identified. The detection of BLV in sheep and buffaloes suggests circulation of the virus in multiple species, which could be involved in dissemination of the virus in mixed livestock production settings. Due to the presence of the virus in multiple species and the high prevalence rates observed, integrated prevention and control strategies in the livestock industry should be considered to decrease the spread of BLV.

Soft X-ray Microscopy Techniques for Medical and Biological Imaging at TwinMic—Elettra

Progress in nanotechnology calls for material probing techniques of high sensitivity and resolution. Such techniques are also used for high-impact studies of nanoscale materials in medicine and biology. Soft X-ray microscopy has been successfully used for investigating complex biological processes occurring at micrometric and sub-micrometric length scales and is one of the most powerful tools in medicine and the life sciences. Here, we present the capabilities of the TwinMic soft X-ray microscopy end-station at the Elettra synchrotron in the context of medical and biological imaging, while we also describe novel uses and developments.

Leveraging natural history biorepositories as a global, decentralized, pathogen surveillance network

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic reveals a major gap in global biosecurity infrastructure: a lack of publicly available biological samples representative across space, time, and taxonomic diversity. The shortfall, in this case for vertebrates, prevents accurate and rapid identification and monitoring of emerging pathogens and their reservoir host(s) and precludes extended investigation of ecological, evolutionary, and environmental associations that lead to human infection or spillover. Natural history museum biorepositories form the backbone of a critically needed, decentralized, global network for zoonotic pathogen surveillance, yet this infrastructure remains marginally developed, underutilized, underfunded, and disconnected from public health initiatives. Proactive detection and mitigation for emerging infectious diseases (EIDs) requires expanded biodiversity infrastructure and training (particularly in biodiverse and lower income countries) and new communication pipelines that connect biorepositories and biomedical communities. To this end, we highlight a novel adaptation of Project ECHO’s virtual community of practice model: Museums and Emerging Pathogens in the Americas (MEPA). MEPA is a virtual network aimed at fostering communication, coordination, and collaborative problem-solving among pathogen researchers, public health officials, and biorepositories in the Americas. MEPA now acts as a model of effective international, interdisciplinary collaboration that can and should be replicated in other biodiversity hotspots. We encourage deposition of wildlife specimens and associated data with public biorepositories, regardless of original collection purpose, and urge biorepositories to embrace new specimen sources, types, and uses to maximize strategic growth and utility for EID research. Taxonomically, geographically, and temporally deep biorepository archives serve as the foundation of a proactive and increasingly predictive approach to zoonotic spillover, risk assessment, and threat mitigation.

Screening potential insect vectors in a museum biorepository reveals undiscovered diversity of plant pathogens in natural areas

Phytoplasmas (Mollicutes, Acholeplasmataceae), vector-borne obligate bacterial plant parasites, infect nearly 1,000 plant species and unknown numbers of insects, mainly leafhoppers (Hemiptera, Deltocephalinae), which play a key role in transmission and epidemiology. Although the plant-phytoplasma-insect association has been evolving for >300 million years, nearly all known phytoplasmas have been discovered as a result of the damage inflicted by phytoplasma diseases on crops. Few efforts have been made to study phytoplasmas occurring in noneconomically important plants in natural habitats. In this study, a subsample of leafhopper specimens preserved in a large museum biorepository was analyzed to unveil potential new associations. PCR screening for phytoplasmas performed on 227 phloem-feeding leafhoppers collected worldwide from natural habitats revealed the presence of 6 different previously unknown phytoplasma strains. This indicates that museum collections of herbivorous insects represent a rich and largely untapped resource for discovery of new plant pathogens, that natural areas worldwide harbor a diverse but largely undiscovered diversity of phytoplasmas and potential insect vectors, and that independent epidemiological cycles occur in such habitats, posing a potential threat of disease spillover into agricultural systems. Larger-scale future investigations will contribute to a better understanding of phytoplasma genetic diversity, insect host range, and insect-borne phytoplasma transmission and provide an early warning for the emergence of new phytoplasma diseases across global agroecosystems.