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Microbiome-based biotechnology for reducing food loss post harvest
Microbiomes have an immense potential to enhance plant resilience to various biotic and abiotic stresses. However, intrinsic microbial communities respond to changes in their host's physiology and environment during plant's life cycle. The potential of the inherent plant microbiome has been neglected for a long time, especially for the postharvest period. Currently, close to 50% of all produced fruits and vegetables are lost either during production or storage. Biological control of spoilage and storage diseases is still lacking sufficiency. Today, novel multiomics technologies allow us to study the microbiome and its responses on a community level, which will help to advance current classic approaches and develop more effective and robust microbiome-based solutions for fruit and vegetable storability, quality, and safety.
Complete genome sequence of a new clostridium sp. isolated from anaerobic digestion and biomethanation
Here, we present the genome sequence and annotation of the bacterial strain HV4-5-A1G, a potentially new Clostridium species. Based on its genomic data, this strain may act as a keystone microorganism in the hydrolysis of complex polymers, as well as in the different acidogenesis and acetogenesis steps during anaerobic digestion. © 2020 Hahnke et al.
Functional relationship of particulate matter (PM) emissions, animal species, and moisture content during manure application
Livestock manure is recycled to agricultural land as organic fertilizer. Due to the extensive usage of antibiotics in conventional animal farming, antibiotic-resistant bacteria are highly prevalent in feces and manure. The spread of wind-driven particulate matter (PM) with potentially associated harmful bacteria through manure application may pose a threat to environmental and human health. We studied whether PM was aerosolized during the application of solid and dried livestock manure and the functional relationship between PM release, manure dry matter content (DM), treatment and animal species. In parallel, manure and resulting PM were investigated for the survival of pathogenic and antibiotic-resistant bacterial species. The results showed that from manure with a higher DM smaller particles were generated and more PM was emitted. A positive correlation between manure DM and PM aerosolization rate was observed. There was a species-dependent critical dryness level (poultry: 60% DM, pig: 80% DM) where manure began to release PM into the environment. The maximum PM emission potentials were 1 and 3 kg t−1 of applied poultry and pig manure, respectively. Dried manure and resulting PM contained strongly reduced amounts of investigated pathogenic and antibiotic-resistant microorganisms compared to fresh samples. An optimal manure DM regarding low PM emissions and reduced pathogen viability was defined from our results, which was 55–70% DM for poultry manure and 75–85% DM for pig manure. The novel findings of this study increase our detailed understanding and basic knowledge on manure PM emissions and enable optimization of manure management, aiming a manure DM that reduces PM emissions and pathogenic release into the environment.
Complete genome sequence of a new Bacteroidaceae bacterium isolated from anaerobic biomass digestion
Here, we present the genome sequence and annotation of HV4-6-C5C, a bacterial strain isolated from a mesophilic two-stage laboratory-scale leach bed biogas reactor system. Strain HV4-6-C5C may represent a new genus of the family Bacteroidaceae and may have a key role in acidogenesis and acetogenesis steps during anaerobic biomass digestion. © 2019 Hahnke et al.
Draft Genome Sequence of a New Oscillospiraceae Bacterium Isolated from Anaerobic Digestion of Biomass
Here, we present the genome sequence and annotation of the novel bacterial strain HV4-5-C5C, which may represent a new genus within the family Oscillospiraceae (order Eubacteriales). This strain is a potential keystone species in the hydrolysis of complex polymers during anaerobic digestion of biomass. © 2020 Pascual et al.
Research data management in agricultural sciences in Germany: We are not yet where we want to be
To meet the future challenges and foster integrated and holistic research approaches in agricultural sciences, new and sustainable methods in research data management (RDM) are needed. The involvement of scientific users is a critical success factor for their development. We conducted an online survey in 2020 among different user groups in agricultural sciences about their RDM practices and needs. In total, the questionnaire contained 52 questions on information about produced and (re-)used data, data quality aspects, information about the use of standards, publication practices and legal aspects of agricultural research data, the current situation in RDM in regards to awareness, consulting and curricula as well as needs of the agricultural community in respect to future developments. We received 196 (partially) completed questionnaires from data providers, data users, infrastructure and information service providers. In addition to the diversity in the research data landscape of agricultural sciences in Germany, the study reveals challenges, deficits and uncertainties in handling research data in agricultural sciences standing in the way of access and efficient reuse of valuable research data. However, the study also suggests and discusses potential solutions to enhance data publications, facilitate and secure data re-use, ensure data quality and develop services (i.e. training, support and bundling services). Therefore, our research article provides the basis for the development of common RDM, future infrastructures and services needed to foster the cultural change in handling research data across agricultural sciences in Germany and beyond.
Trade-off for survival: Microbiome response to chemical exposure combines activation of intrinsic resistances and adapted metabolic activity
The environmental microbiota is increasingly exposed to chemical pollution. While the emergence of multi-resistant pathogens is recognized as a global challenge, our understanding of antimicrobial resistance (AMR) development from native microbiomes and the risks associated with chemical exposure is limited. By implementing a lichen as a bioindicator organism and model for a native microbiome, we systematically examined responses towards antimicrobials (colistin, tetracycline, glyphosate, and alkylpyrazine). Despite an unexpectedly high resilience, we identified potential evolutionary consequences of chemical exposure in terms of composition and functioning of native bacterial communities. Major shifts in bacterial composition were observed due to replacement of naturally abundant taxa; e.g. Chthoniobacterales by Pseudomonadales. A general response, which comprised activation of intrinsic resistance and parallel reduction of metabolic activity at RNA and protein levels was deciphered by a multi-omics approach. Targeted analyses of key taxa based on metagenome-assembled genomes reflected these responses but also revealed diversified strategies of their players. Chemical-specific responses were also observed, e.g., glyphosate enriched bacterial r-strategists and activated distinct ARGs. Our work demonstrates that the high resilience of the native microbiota toward antimicrobial exposure is not only explained by the presence of antibiotic resistance genes but also adapted metabolic activity as a trade-off for survival. Moreover, our results highlight the importance of native microbiomes as important but so far neglected AMR reservoirs. We expect that this phenomenon is representative for a wide range of environmental microbiota exposed to chemicals that potentially contribute to the emergence of antibiotic-resistant bacteria from natural environments.
Airborne bacterial emission fluxes from manure-fertilized agricultural soil
This is the first study to quantify the dependence on wind velocity of airborne bacterial emission fluxes from soil. It demonstrates that manure bacteria get aerosolized from fertilized soil more easily than soil bacteria, and it applies bacterial genomic sequencing for the first time to trace environmental faecal contamination back to its source in the chicken barn. We report quantitative, airborne emission fluxes of bacteria during and following the fertilization of agricultural soil with manure from broiler chickens. During the fertilization process, the concentration of airborne bacteria culturable on blood agar medium increased more than 600 000-fold, and 1 m3 of air carried 2.9 × 105 viable enterococci, i.e. indicators of faecal contamination which had been undetectable in background air samples. Trajectory modelling suggested that atmospheric residence times and dispersion pathways were dependent on the time of day at which fertilization was performed. Measurements in a wind tunnel indicated that airborne bacterial emission fluxes from freshly fertilized soil under local climatic conditions on average were 100-fold higher than a previous estimate of average emissions from land. Faecal bacteria collected from soil and dust up to seven weeks after fertilization could be traced to their origins in the poultry barn by genomic sequencing. Comparative analyses of 16S rRNA gene sequences from manure, soil and dust showed that manure bacteria got aerosolized preferably, likely due to their attachment to low-density manure particles. Our data show that fertilization with manure may cause substantial increases of bacterial emissions from agricultural land. After mechanical incorporation of manure into soil, however, the associated risk of airborne infection is low.
Occupational health and safety in agriculture – a brief report on organization, legislation and support in selected European countries
Introduction and objective: Agriculture and forestry are among the most dangerous professions in Europe, with a high level of accidents affecting the sustainability and viability of the sector. International conventions, EU directives and national legislation build the fundamental basis for prevention. The aim of the study is to describe and categorize national mechanisms of occupational safety and health (OSH) for agricultural workers in Europe, to assess the extent of implementing safety regulation, the body in charge, and to give examples of health and safety initiatives. Material and methods: Results of a questionnaire-survey on basic safety regulations on farms sent by e-mail to the representatives of 30 participating European countries in the context of the Sacurima COST action network (CA 16123) are presented. Due to the complexity, only selected countries are described in this study highlighting the regulative bodies, occupational health services or specific training offers, as well as the complexity of the mechanisms. Results: One of the most serious issues and deficits of EU OSH regulation is the exclusion of self-employed farmers who compose nearly 90% of the farming population. This leads to serious under-reporting of accidents, and because one of the most common measures for the performance of health and safety initiatives are the injury and ill health statistics, better registration systems are urgently needed in almost all countries as a basis for preventive efforts. Conclusions: The results of the study provide a basis for raising awareness about the current OSH systems in Europe, and the importance of developing sector specific OSH strategies. The proposed activities should assist in tackling high accident rates and poor occupational health for self-employed farmers.
Towards the automatic detection of social biomarkers in autism spectrum disorder: introducing the simulated interaction task (SIT)
Social interaction deficits are evident in many psychiatric conditions and specifically in autism spectrum disorder (ASD), but hard to assess objectively. We present a digital tool to automatically quantify biomarkers of social interaction deficits: the simulated interaction task (SIT), which entails a standardized 7-min simulated dialog via video and the automated analysis of facial expressions, gaze behavior, and voice characteristics. In a study with 37 adults with ASD without intellectual disability and 43 healthy controls, we show the potential of the tool as a diagnostic instrument and for better description of ASD-associated social phenotypes. Using machine-learning tools, we detected individuals with ASD with an accuracy of 73%, sensitivity of 67%, and specificity of 79%, based on their facial expressions and vocal characteristics alone. Especially reduced social smiling and facial mimicry as well as a higher voice fundamental frequency and harmony-to-noise-ratio were characteristic for individuals with ASD. The time-effective and cost-effective computer-based analysis outperformed a majority vote and performed equal to clinical expert ratings. © 2020, The Author(s).