Nematodes alter the taxonomic and functional profiles of benthic bacterial communities: A metatranscriptomic approach.

Marine sediments cover 70% of the Earth's surface, and harbour diverse bacterial communities critical for marine biogeochemical processes, which affect climate change, biodiversity and ecosystem functioning. Nematodes, the most abundant and species-rich metazoan organisms in marine sediments, in turn, affect benthic bacterial communities and bacterial-mediated ecological processes, but the underlying mechanisms by which they affect biogeochemical cycles remain poorly understood. Here, we demonstrate using a metatranscriptomic approach that nematodes alter the taxonomic and functional profiles of benthic bacterial communities. We found particularly strong stimulation of nitrogen-fixing and methane-oxidizing bacteria in the presence of nematodes, as well as increased functional activity associated with methane metabolism and degradation of various carbon compounds. This study provides empirical evidence that the presence of nematodes results in taxonomic and functional shifts in active bacterial communities, indicating that nematodes may play an important role in benthic ecosystem processes.

Correction: Haegeman et al. Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests. Plants 2023, 12, 2139.

In the original publication [...].

Detection of Fusarium oxysporum f.sp. lactucae race 1 and 4 via race-specific real-time PCR and target enrichment.

Fusarium oxysporum f.sp. lactucae (Fol) causes a vascular disease in lettuce that results in significant yield losses. Race-specific and sensitive real-time PCR assays were developed for Fol races 1 and 4, which are prevalent in Europe. Using genotyping-by-sequencing, unique DNA loci specific to each race were identified and subsequently used for the design of primers and hydrolysis probes. Two assays per race were developed to ensure specificity. The two assays of each race could be run in duplex format, while still giving a sensitivity of 100 fg genomic DNA for all assays. Sample preparation methods were developed for plant tissue, soil, and surfaces, with an extra enrichment step when additional sensitivity was required. By controlling the incubation conditions during the enrichment step, the real-time PCR signal could be matched to the number of spore equivalents in the original sample. When enriching naturally infested soil, down to six conidiospore equivalents L-1 soil could be detected. As enrichment ensures sensitive detection and focuses on living Fol propagules, it facilitates the evaluation of control measures. The developed detection methods for soil and surfaces were applied to samples from commercial lettuce farms and confirmed the prevalence of Fol race 4 in Belgium. Monitoring of soil disinfestation events revealed that despite a dramatic decrease in quantity, the pathogen could still be detected either immediately after sheet steaming or after harvesting the first new crop. The detection method for plant tissue was successfully used to quantify Fol in lettuce inoculated with race 1, race 4 or a combination of both. Under the temperature conditions used, race 4 was more aggressive than race 1, as reflected in larger amounts of DNA of race 4 detected in the roots. These newly developed assays are a promising tool for epidemiological research as well as for the evaluation of control measures.

Detection of single nucleotide polymorphisms in virus genomes assembled from high-throughput sequencing data: large-scale performance testing of sequence analysis strategies.

Recent developments in high-throughput sequencing (HTS) technologies and bioinformatics have drastically changed research in virology, especially for virus discovery. Indeed, proper monitoring of the viral population requires information on the different isolates circulating in the studied area. For this purpose, HTS has greatly facilitated the sequencing of new genomes of detected viruses and their comparison. However, bioinformatics analyses allowing reconstruction of genome sequences and detection of single nucleotide polymorphisms (SNPs) can potentially create bias and has not been widely addressed so far. Therefore, more knowledge is required on the limitations of predicting SNPs based on HTS-generated sequence samples. To address this issue, we compared the ability of 14 plant virology laboratories, each employing a different bioinformatics pipeline, to detect 21 variants of pepino mosaic virus (PepMV) in three samples through large-scale performance testing (PT) using three artificially designed datasets. To evaluate the impact of bioinformatics analyses, they were divided into three key steps: reads pre-processing, virus-isolate identification, and variant calling. Each step was evaluated independently through an original, PT design including discussion and validation between participants at each step. Overall, this work underlines key parameters influencing SNPs detection and proposes recommendations for reliable variant calling for plant viruses. The identification of the closest reference, mapping parameters and manual validation of the detection were recognized as the most impactful analysis steps for the success of the SNPs detections. Strategies to improve the prediction of SNPs are also discussed.

Identification and characterization of CYP71 subclade cytochrome P450 enzymes involved in the biosynthesis of bitterness compounds in Cichorium intybus.

Industrial chicory (Cichorium intybus var. sativum) and witloof (C. intybus var. foliosum) are crops with an important economic value, mainly cultivated for inulin production and as a leafy vegetable, respectively. Both crops are rich in nutritionally relevant specialized metabolites with beneficial effects for human health. However, their bitter taste, caused by the sesquiterpene lactones (SLs) produced in leaves and taproot, limits wider applications in the food industry. Changing the bitterness would thus create new opportunities with a great economic impact. Known genes encoding enzymes involved in the SL biosynthetic pathway are GERMACRENE A SYNTHASE (GAS), GERMACRENE A OXIDASE (GAO), COSTUNOLIDE SYNTHASE (COS) and KAUNIOLIDE SYNTHASE (KLS). In this study, we integrated genome and transcriptome mining to further unravel SL biosynthesis. We found that C. intybus SL biosynthesis is controlled by the phytohormone methyl jasmonate (MeJA). Gene family annotation and MeJA inducibility enabled the pinpointing of candidate genes related with the SL biosynthetic pathway. We specifically focused on members of subclade CYP71 of the cytochrome P450 family. We verified the biochemical activity of 14 C. intybus CYP71 enzymes transiently produced in Nicotiana benthamiana and identified several functional paralogs for each of the GAO, COS and KLS genes, pointing to redundancy in and robustness of the SL biosynthetic pathway. Gene functionality was further analyzed using CRISPR/Cas9 genome editing in C. intybus. Metabolite profiling of mutant C. intybus lines demonstrated a successful reduction in SL metabolite production. Together, this study increases our insights into the C. intybus SL biosynthetic pathway and paves the way for the engineering of C. intybus bitterness.

Industrial chicory genome gives insights into the molecular timetable of anther development and male sterility.

Industrial chicory (Cichorium intybus var. sativum) is a biannual crop mostly cultivated for extraction of inulin, a fructose polymer used as a dietary fiber. F1 hybrid breeding is a promising breeding strategy in chicory but relies on stable male sterile lines to prevent self-pollination. Here, we report the assembly and annotation of a new industrial chicory reference genome. Additionally, we performed RNA-Seq on subsequent stages of flower bud development of a fertile line and two cytoplasmic male sterile (CMS) clones. Comparison of fertile and CMS flower bud transcriptomes combined with morphological microscopic analysis of anthers, provided a molecular understanding of anther development and identified key genes in a range of underlying processes, including tapetum development, sink establishment, pollen wall development and anther dehiscence. We also described the role of phytohormones in the regulation of these processes under normal fertile flower bud development. In parallel, we evaluated which processes are disturbed in CMS clones and could contribute to the male sterile phenotype. Taken together, this study provides a state-of-the-art industrial chicory reference genome, an annotated and curated candidate gene set related to anther development and male sterility as well as a detailed molecular timetable of flower bud development in fertile and CMS lines.

Looking beyond Virus Detection in RNA Sequencing Data: Lessons Learned from a Community-Based Effort to Detect Cellular Plant Pathogens and Pests.

High-throughput sequencing (HTS), more specifically RNA sequencing of plant tissues, has become an indispensable tool for plant virologists to detect and identify plant viruses. During the data analysis step, plant virologists typically compare the obtained sequences to reference virus databases. In this way, they are neglecting sequences without homologies to viruses, which usually represent the majority of sequencing reads. We hypothesized that traces of other pathogens might be detected in this unused sequence data. In the present study, our goal was to investigate whether total RNA-seq data, as generated for plant virus detection, is also suitable for the detection of other plant pathogens and pests. As proof of concept, we first analyzed RNA-seq datasets of plant materials with confirmed infections by cellular pathogens in order to check whether these non-viral pathogens could be easily detected in the data. Next, we set up a community effort to re-analyze existing Illumina RNA-seq datasets used for virus detection to check for the potential presence of non-viral pathogens or pests. In total, 101 datasets from 15 participants derived from 51 different plant species were re-analyzed, of which 37 were selected for subsequent in-depth analyses. In 29 of the 37 selected samples (78%), we found convincing traces of non-viral plant pathogens or pests. The organisms most frequently detected in this way were fungi (15/37 datasets), followed by insects (13/37) and mites (9/37). The presence of some of the detected pathogens was confirmed by independent (q)PCRs analyses. After communicating the results, 6 out of the 15 participants indicated that they were unaware of the possible presence of these pathogens in their sample(s). All participants indicated that they would broaden the scope of their bioinformatic analyses in future studies and thus check for the presence of non-viral pathogens. In conclusion, we show that it is possible to detect non-viral pathogens or pests from total RNA-seq datasets, in this case primarily fungi, insects, and mites. With this study, we hope to raise awareness among plant virologists that their data might be useful for fellow plant pathologists in other disciplines (mycology, entomology, bacteriology) as well.

Using environmental DNA metabarcoding to monitor fish communities in small rivers and large brooks: Insights on the spatial scale of information.

Monitoring fish communities is central to the evaluation of ecological health of rivers. Both presence/absence of fish species and their relative quantity in local fish assemblages are crucial parameters to measure. Fish communities in lotic systems are traditionally monitored via electrofishing, characterized by a known limited efficiency and high survey costs. Analysis of environmental DNA could serve as a non-destructive alternative for detection and quantification of lotic fish communities, but this approach still requires further insights in practical sampling schemes incorporating transport and dilution of the eDNA particles; optimization of predictive power and quality assurance of the molecular detection method. Via a controlled cage experiment, we aim to extend the knowledge on streamreach of eDNA in small rivers and large brooks, as laid out in the European Water Framework Directive's water typology. Using a high and low source biomass in two river transects of a species-poor river characterized by contrasting river discharge rates, we found strong and significant correlations between the eDNA relative species abundances and the relative biomass per species in the cage community. Despite a decreasing correlation over distance, the underlying community composition remained stable from 25 to 300 m, or up to 1 km downstream of the eDNA source, depending on the river discharge rate. Such decrease in similarity between relative source biomass and the corresponding eDNA-based community profile with increasing distance downstream from the source, might be attributed to variation in species-specific eDNA persistence. Our findings offer crucial insights on eDNA behaviour and characterization of riverine fish communities. We conclude that water sampled from a relatively small river offers an adequate eDNA snapshot of the total fish community in the 300-1000 m upstream transect. The potential application for other river systems is further discussed.

Phylogeography and population structure of the global, wide host-range hybrid pathogen Phytophthora × cambivora.

Invasive, exotic plant pathogens pose a major threat to native and agricultural ecosystems. Phytophthora × cambivora is an invasive, destructive pathogen of forest and fruit trees causing severe damage worldwide to chestnuts (Castanea), apricots, peaches, plums, almonds and cherries (Prunus), apples (Malus), oaks (Quercus), and beech (Fagus). It was one of the first damaging invasive Phytophthora species to be introduced to Europe and North America, although its origin is unknown. We determined its population genetic history in Europe, North and South America, Australia and East Asia (mainly Japan) using genotyping-by-sequencing. Populations in Europe and Australia appear clonal, those in North America are highly clonal yet show some degree of sexual reproduction, and those in East Asia are partially sexual. Two clonal lineages, each of opposite mating type, and a hybrid lineage derived from these two lineages, dominated the populations in Europe and were predominantly found on fagaceous forest hosts (Castanea, Quercus, Fagus). Isolates from fruit trees (Prunus and Malus) belonged to a separate lineage found in Australia, North America, Europe and East Asia, indicating the disease on fruit trees could be caused by a distinct lineage of P. × cambivora, which may potentially be a separate sister species and has likely been moved with live plants. The highest genetic diversity was found in Japan, suggesting that East Asia is the centre of origin of the pathogen. Further surveys in unsampled, temperate regions of East Asia are needed to more precisely identify the location and range of the centre of diversity.

Flexible spandrels of the global plant virome: Proteomic-wide evolutionary patterns of structural intrinsic protein disorder elucidate modulation at the functional virus-host interplay.

Intrinsically disordered proteins and regions (IDPs/IDRs) make up a large part of viral proteomes, but their real prevalence across the global plant virome is still murky, partly because of their massive diversity. Here, we propose an evolutionary quantitative proteomic approach to foray into genomic signatures that are preserved in the amino acid sequences of orthologous IDRs. Markedly, we found that relatively abundant IDP varies substantially in viral species among and within plant virus families, including according to genome size, partition or replication strategies. We also demonstrate that most encoded proteomic modules of the plant virome contain multiple disordered features that are phylogenomically preserved, and can be correlated to genomic, bio-physical and evolutionary strategies. Furthermore, our focused interactome-wide analysis highlights lines of evidence indicating that various IDPs with similar evolutionary signatures modulate viral multifunctionality. Moreover, estimated fractions of IDR in the vicinity of pivotal evolutionary structural domains embedded in interaction modules are strongly enriched with affinity binding functional annotations and relate to vector-borne virus transmission modes. Importantly, molecular recognition features (MoRFs) are abundantly widespread in IDRs of viral hallmark modules and their binding partners. Finally, we propose a coarse-grained conceptual framework in which evolutionary proteome-wide IDP/IDRs patterns can be, rather, reliably exploited to elucidate their foundational fine-tuning role in plant virus transmission mechanisms. While opening unexplored avenues for consistently predicting virus-host functions for many new or uncharacterized viruses based on their proteomic repertoire, other considerations advocating further structural IDP research in Plant Virology are thoroughly discussed in light of viral modular evolution.

Unravelling hybridization in Phytophthora using phylogenomics and genome size estimation.

The genus Phytophthora comprises many economically and ecologically important plant pathogens. Hybrid species have previously been identified in at least six of the 12 phylogenetic clades. These hybrids can potentially infect a wider host range and display enhanced vigour compared to their progenitors. Phytophthora hybrids therefore pose a serious threat to agriculture as well as to natural ecosystems. Early and correct identification of hybrids is therefore essential for adequate plant protection but this is hampered by the limitations of morphological and traditional molecular methods. Identification of hybrids is also important in evolutionary studies as the positioning of hybrids in a phylogenetic tree can lead to suboptimal topologies. To improve the identification of hybrids we have combined genotyping-by-sequencing (GBS) and genome size estimation on a genus-wide collection of 614 Phytophthora isolates. Analyses based on locus- and allele counts and especially on the combination of species-specific loci and genome size estimations allowed us to confirm and characterize 27 previously described hybrid species and discover 16 new hybrid species. Our method was also valuable for species identification at an unprecedented resolution and further allowed correct naming of misidentified isolates. We used both a concatenation- and a coalescent-based phylogenomic method to construct a reliable phylogeny using the GBS data of 140 non-hybrid Phytophthora isolates. Hybrid species were subsequently connected to their progenitors in this phylogenetic tree. In this study we demonstrate the application of two validated techniques (GBS and flow cytometry) for relatively low cost but high resolution identification of hybrids and their phylogenetic relations.

Reassessment of the Columnea latent viroid (CLVd) Taxonomic Classification.

Columnea latent viroid (CLVd) is a member of the Pospiviroid family and its naked circular RNA genome typically forms native "rod-like" secondary structures. In this work, the CLVd taxonomy was reevaluated based on sequence similarity and phylogenetic analysis, as well as the evaluation of the symptom development and disease severity of four selected CLVd isolates in a range of host species. The phylogenetic analysis showed that all CLVd isolates were clustered into five distinct clades: (I) severe isolates originally found in tomato crops in Thailand, (II) ornamental isolates, (III) mild isolates originally found in tomato crops in Thailand, and two clades (IV and V) containing mild isolates originating mainly from tomato crops in European countries, with different virulence levels on several hosts. Our analysis demonstrated that some CLVd isolates have a sequence similarity of less than 90% within the species taxon, as well as distinct biological characteristics (symptom development and virulence), both of which are important ICTV criteria for viroid classification. For these reasons, we propose that CLVd should be re-classified into at least three main taxonomic lineages: a "CLVd-tomato Asian lineage" (I), a "CLVd-tomato European lineage" (IV) and a "CLVd-ornamental European lineage" (II), plus two minor lineages (III and V), fitting the ICTV criteria.

A Primer on the Analysis of High-Throughput Sequencing Data for Detection of Plant Viruses.

High-throughput sequencing (HTS) technologies have become indispensable tools assisting plant virus diagnostics and research thanks to their ability to detect any plant virus in a sample without prior knowledge. As HTS technologies are heavily relying on bioinformatics analysis of the huge amount of generated sequences, it is of utmost importance that researchers can rely on efficient and reliable bioinformatic tools and can understand the principles, advantages, and disadvantages of the tools used. Here, we present a critical overview of the steps involved in HTS as employed for plant virus detection and virome characterization. We start from sample preparation and nucleic acid extraction as appropriate to the chosen HTS strategy, which is followed by basic data analysis requirements, an extensive overview of the in-depth data processing options, and taxonomic classification of viral sequences detected. By presenting the bioinformatic tools and a detailed overview of the consecutive steps that can be used to implement a well-structured HTS data analysis in an easy and accessible way, this paper is targeted at both beginners and expert scientists engaging in HTS plant virome projects.

Study of the transfer of Listeria monocytogenes during the slaughter of cattle using molecular typing.

The introduction, transmission, and persistence of Listeria monocytogenes in Belgian beef slaughterhouses was investigated using genetic characterization. During slaughter, samples were taken of the hide, carcass, and environment to detect the pathogen. Remarkably, L. monocytogenes was massively present on the hide of incoming animals (93%; 112/120), regardless of their visual cleanliness, which implies high contamination pressure levels entering the slaughterhouses. Pathogen transfer via cross-contamination was conclusively confirmed in this study, with the same pulsotypes isolated from the hide, carcass, and environmental samples. Despite the important bacterial presence on the hide of incoming animals, most slaughterhouses succeeded in limiting the transfer as cause of carcass contamination. Persistence along the slaughter line seemed to be a more significant problem, as it was clearly linked to most of the L. monocytogenes positive carcasses. In one slaughterhouse, whole genome sequencing (WGS) revealed that the carcass splitter had been contaminating carcasses with the same strain belonging to CC9 for more than one year.

Contamination Sources and Transmission Routes for Campylobacter on (Mixed) Broiler Farms in Belgium, and Comparison of the Gut Microbiota of Flocks Colonized and Uncolonized with Campylobacter.

Biosecurity seems to be the most promising tool for Campylobacter control on poultry farms. A longitudinal molecular epidemiological study was performed during two production cycles, in which the broilers, the poultry house, and the environment of 10 (mixed) broiler farms were monitored weekly. Cecal droppings from the second production cycle were also used for 16S metabarcoding to study the differences in the microbiota of colonized and uncolonized flocks. Results showed that 3 out of 10 farms were positive for Campylobacter in the first production cycle, and 4 out of 10 were positive in the second. Broilers became colonized at the earliest when they were four weeks old. The majority of the flocks (57%) became colonized after partial depopulation. Before colonization of the flocks, Campylobacter was rarely detected in the environment, but it was frequently isolated from cattle and swine. Although these animals appeared to be consistent carriers of Campylobacter, molecular typing revealed that they were not the source of flock colonization. In accordance with previous reports, this study suggests that partial depopulation appears to be an important risk factor for Campylobacter introduction into the broiler house. Metabarcoding indicated that two Campylobacter-free flocks carried high relative abundances of Megamonas in their ceca, suggesting potential competition with Campylobacter.

Monitoring of spatiotemporal occupancy patterns of fish and amphibian species in a lentic aquatic system using environmental DNA.

To effectively monitor, manage and protect aquatic species and understand their interactions, knowledge of their spatiotemporal distribution is needed. In this study, we used a fine-scale spatiotemporal water sampling design, followed by environmental DNA (eDNA) 12S metabarcoding, to investigate occupancy patterns of a natural community of fish and amphibian species in a lentic system. In the same system, we experimentally estimated the spatial and temporal dispersion of eDNA by placing a community of different fish and amphibian species in cages at one side of the pond, creating a controlled point of eDNA emission. Analyses of this cage community revealed a sharp spatial decline in detection rates and relative eDNA quantities at a distance of 5-10 m from the source, depending on the species and its abundance. In addition, none of the caged species could be detected 1 week after removal from the system. This indicates high eDNA decay rates and limited spatial eDNA dispersal, facilitating high local resolution for monitoring spatial occupancy patterns of aquatic species. Remarkably, for seven of the nine cage species, the presence of a single individual could be detected by pooling water of subsamples taken across the whole water body, illustrating the high sensitivity of the eDNA sampling and detection method applied. Finally, our work demonstrated that a fine-scale sampling design in combination with eDNA metabarcoding can cover total biodiversity very precisely and allows the construction of consistent spatiotemporal patterns of relative abundance and local distribution of free-living fish and amphibian species in a lentic ecosystem.

Daring to be differential: metabarcoding analysis of soil and plant-related microbial communities using amplicon sequence variants and operational taxonomical units.

BACKGROUND: Microorganisms are not only indispensable to ecosystem functioning, they are also keystones for emerging technologies. In the last 15 years, the number of studies on environmental microbial communities has increased exponentially due to advances in sequencing technologies, but the large amount of data generated remains difficult to analyze and interpret. Recently, metabarcoding analysis has shifted from clustering reads using Operational Taxonomical Units (OTUs) to Amplicon Sequence Variants (ASVs). Differences between these methods can seriously affect the biological interpretation of metabarcoding data, especially in ecosystems with high microbial diversity, as the methods are benchmarked based on low diversity datasets. RESULTS: In this work we have thoroughly examined the differences in community diversity, structure, and complexity between the OTU and ASV methods. We have examined culture-based mock and simulated datasets as well as soil- and plant-associated bacterial and fungal environmental communities. Four key findings were revealed. First, analysis of microbial datasets at family level guaranteed both consistency and adequate coverage when using either method. Second, the performance of both methods used are related to community diversity and sample sequencing depth. Third, differences in the method used affected sample diversity and number of detected differentially abundant families upon treatment; this may lead researchers to draw different biological conclusions. Fourth, the observed differences can mostly be attributed to low abundant (relative abundance < 0.1%) families, thus extra care is recommended when studying rare species using metabarcoding. The ASV method used outperformed the adopted OTU method concerning community diversity, especially for fungus-related sequences, but only when the sequencing depth was sufficient to capture the community complexity. CONCLUSIONS: Investigation of metabarcoding data should be done with care. Correct biological interpretation depends on several factors, including in-depth sequencing of the samples, choice of the most appropriate filtering strategy for the specific research goal, and use of family level for data clustering.

Whole-Genome Deep Sequencing Reveals Host-Driven in-planta Evolution of Columnea Latent Viroid (CLVd) Quasi-Species Populations.

Columnea latent viroid (CLVd) is one of the most serious tomato diseases. In general, viroids have high mutation rates. This generates a population of variants (so-called quasi-species) that co-exist in their host and exhibit a huge level of genetic diversity. To study the population of CLVd in individual host plants, we used amplicon sequencing using specific CLVd primers linked with a sample-specific index sequence to amplify libraries. An infectious clone of a CLVd isolate Chaipayon-1 was inoculated on different solanaceous host plants. Six replicates of the amplicon sequencing results showed very high reproducibility. On average, we obtained 133,449 CLVd reads per PCR-replicate and 79 to 561 viroid sequence variants, depending on the plant species. We identified 19 major variants (>1.0% mean relative abundance) in which a total of 16 single-nucleotide polymorphisms (SNPs) and two single nucleotide insertions were observed. All major variants contained a combination of 4 to 6 SNPs. Secondary structure prediction clustered all major variants into a tomato/bolo maka group with four loops (I, II, IV and V), and a chili pepper group with four loops (I, III, IV and V) at the terminal right domain, compared to the CLVd Chaipayon-1 which consists of five loops (I, II, III, IV and V).

Tapping into the maize root microbiome to identify bacteria that promote growth under chilling conditions.

BACKGROUND: When maize (Zea mays L.) is grown in the Northern hemisphere, its development is heavily arrested by chilling temperatures, especially at the juvenile phase. As some endophytes are beneficial for plants under stress conditions, we analyzed the impact of chilling temperatures on the root microbiome and examined whether microbiome-based analysis might help to identify bacterial strains that could promote growth under these temperatures. RESULTS: We investigated how the maize root microbiome composition changed by means of 16S rRNA gene amplicon sequencing when maize was grown at chilling temperatures in comparison to ambient temperatures by repeatedly cultivating maize in field soil. We identified 12 abundant and enriched bacterial families that colonize maize roots, consisting of bacteria recruited from the soil, whereas seed-derived endophytes were lowly represented. Chilling temperatures modified the root microbiome composition only slightly, but significantly. An enrichment of several chilling-responsive families was detected, of which the Comamonadaceae and the Pseudomonadaceae were the most abundant in the root endosphere of maize grown under chilling conditions, whereas only three were strongly depleted, among which the Streptomycetaceae. Additionally, a collection of bacterial strains isolated from maize roots was established and a selection was screened for growth-promoting effects on juvenile maize grown under chilling temperatures. Two promising strains that promoted maize growth under chilling conditions were identified that belonged to the root endophytic bacterial families, from which the relative abundance remained unchanged by variations in the growth temperature. CONCLUSIONS: Our analyses indicate that chilling temperatures affect the bacterial community composition within the maize root endosphere. We further identified two bacterial strains that boost maize growth under chilling conditions. Their identity revealed that analyzing the chilling-responsive families did not help for their identification. As both strains belong to root endosphere enriched families, visualizing and comparing the bacterial diversity in these communities might still help to identify new PGPR strains. Additionally, a strain does not necessarely need to belong to a high abundant family in the root endosphere to provoke a growth-promoting effect in chilling conditions. Video abstract.

Effects of synthetic fertilizer and farm compost on soil nematode community in long-term crop rotation plots: A morphological and metabarcoding approach.

Soil biodiversity plays a key regulation role in the ecosystem services that underpin regenerative sustainable agriculture. It can be impacted by agricultural management techniques, both positively (through measures such as compost application) and negatively (through, for example, application of synthetic nitrogen). As one of the most numerous members of the soil biota, nematodes are well established as indicators for the soil food web. However, compost application also includes the addition of nematodes present in compost and their subsequent survival in soil is unknown. Nematode communities within the compost applied to soil, and nematode communities in the soil of a multi-year rotational cropping field trial in Melle (Belgium) were studied using morphological and metabarcoding techniques. Compost (C) and nitrogen fertilizer (NF) treated plots were compared. Three replicate plots were investigated for each of the following treatments: C application only; C and NF application; NF only; no C and no NF (control). Plots were sampled six times between 2015-2017, before and after C or NF were added each spring and after crop harvest (except for 2017). NF treatment resulted in a significant decrease of fungal feeding and predatory nematodes, while herbivorous nematodes were positively affected. Remarkably, we did not find compost addition to exert any noticeable effects on the soil nematode community. The morphological and metabarcoding data resulted in different results of the nematode community composition. However, trends and patterns in the two data sets were congruent when observed with NMDS plots and using the nematode maturity index. Metabarcoding of individual compost nematode taxa demonstrated that nematodes originating from compost did not persist in soil.