Organic fertilization reduces nitrous oxide emission by altering nitrogen cycling microbial guilds favouring complete denitrification at soil aggregate scale.

Agricultural management practices can induce changes in soil aggregation structure that alter the microbial nitrous oxide (N2O) production and reduction processes occurring at the microscale, leading to large-scale consequences for N2O emissions. However, the mechanistic understanding of how organic fertilization affects these context-dependent small-scale N2O emissions and associated key nitrogen (N) cycling microbial communities is lacking. Here, denitrification gas (N2O, N2) and potential denitrification capacity N2O/(N2O + N2) were assessed by automated gas chromatography in different soil aggregates (>2 mm, 2-0.25 and <0.25 mm), while associated microbial communities were assessed by sequencing and qPCR of N2O-producing (nirK and nirS) and reducing (nosZ clade I and II) genes. The results indicated that organic fertilization reduced N2O emissions by enhancing the conversion of N2O to N2 in all aggregate sizes. Moreover, potential N2O production and reduction hotspots occurred in smaller soil aggregates, with the degree depending on organic fertilizer type and application rate. Further, significantly higher abundance and diversity of nosZ clades relative to nirK and nirS revealed complete denitrification promoted through selection of denitrifying communities at microscales favouring N2O reduction. Communities associated with high and low emission treatments form modules with specific sequence types which may be diagnostic of emission levels. Taken together, these findings suggest that organic fertilizers reduced N2O emissions through influencing soil factors and patterns of niche partitioning between N2O-producing and reducing communities within soil aggregates, and selection for communities that overall are more likely to consume than emit N2O. These findings are helpful in strengthening the ability to predict N2O emissions from agricultural soils under organic fertilization as well as contributing to the development of net-zero carbon strategies for sustainable agriculture.

Rhizobium nodule diversity and composition are influenced by clover host selection and local growth conditions.

While shaping of plant microbiome composition through 'host filtering' is well documented in legume-rhizobium symbioses, it is less clear to what extent different varieties and genotypes of the same plant species differentially influence symbiont community diversity and composition. Here, we compared how clover host varieties and genotypes affect the structure of Rhizobium populations in root nodules under conventional field and controlled greenhouse conditions. We first grew four Trifolium repens (white clover) F2 crosses and one variety in a conventional field trial and compared differences in root nodule Rhizobium leguminosarum symbiovar trifolii (Rlt) genotype diversity using high-throughput amplicon sequencing of chromosomal housekeeping (rpoB and recA) genes and auxiliary plasmid-borne symbiosis genes (nodA and nodD). We found that Rlt nodule diversities significantly differed between clover crosses, potentially due to host filtering. However, variance in Rlt diversity largely overlapped between crosses and was also explained by the spatial distribution of plants in the field, indicative of the role of local environmental conditions for nodule diversity. To test the effect of host filtering, we conducted a controlled greenhouse trial with a diverse Rlt inoculum and several host genotypes. We found that different clover varieties and genotypes of the same variety selected for significantly different Rlt nodule communities and that the strength of host filtering (deviation from the initial Rhizobium inoculant composition) was positively correlated with the efficiency of symbiosis (rate of plant greenness colouration). Together, our results suggest that selection by host genotype and local growth conditions jointly influence white clover Rlt nodule diversity and community composition.

Major effect loci for plant size before onset of nitrogen fixation allow accurate prediction of yield in white clover.

KEY MESSAGE: Accurate genomic prediction of yield within and across generations was achieved by estimating the genetic merit of individual white clover genotypes based on extensive genetic replication using cloned material. White clover is an agriculturally important forage legume grown throughout temperate regions as a mixed clover-grass crop. It is typically cultivated with low nitrogen input, making yield dependent on nitrogen fixation by rhizobia in root nodules. Here, we investigate the effects of clover and rhizobium genetic variation by monitoring plant growth and quantifying dry matter yield of 704 combinations of 145 clover genotypes and 170 rhizobium inocula. We find no significant effect of rhizobium variation. In contrast, we can predict yield based on a few white clover markers strongly associated with plant size prior to nitrogen fixation, and the prediction accuracy for polycross offspring yield is remarkably high. Several of the markers are located near a homolog of Arabidopsis thaliana GIGANTUS 1, which regulates growth rate and biomass accumulation. Our work provides fundamental insight into the genetics of white clover yield and identifies specific candidate genes as breeding targets.

Introducing a Novel, Broad Host Range Temperate Phage Family Infecting Rhizobium leguminosarum and Beyond.

Temperate phages play important roles in bacterial communities but have been largely overlooked, particularly in non-pathogenic bacteria. In rhizobia the presence of temperate phages has the potential to have significant ecological impacts but few examples have been described. Here we characterize a novel group of 5 Rhizobium leguminosarum prophages, capable of sustaining infections across a broad host range within their host genus. Genome comparisons identified further putative prophages infecting multiple Rhizobium species isolated globally, revealing a wider family of 10 temperate phages including one previously described lytic phage, RHEph01, which appears to have lost the ability to form lysogens. Phylogenetic discordance between prophage and host phylogenies suggests a history of active mobilization between Rhizobium lineages. Genome comparisons revealed conservation of gene content and order, with the notable exception of an approximately 5 kb region of hypervariability, containing almost exclusively hypothetical genes. Additionally, several horizontally acquired genes are present across the group, including a putative antirepressor present only in the RHEph01 genome, which may explain its apparent inability to form lysogens. In summary, both phenotypic and genomic comparisons between members of this group of phages reveals a clade of viruses with a long history of mobilization within and between Rhizobium species.

Defining the Rhizobium leguminosarum Species Complex.

Bacteria currently included in Rhizobium leguminosarum are too diverse to be considered a single species, so we can refer to this as a species complex (the Rlc). We have found 429 publicly available genome sequences that fall within the Rlc and these show that the Rlc is a distinct entity, well separated from other species in the genus. Its sister taxon is R. anhuiense. We constructed a phylogeny based on concatenated sequences of 120 universal (core) genes, and calculated pairwise average nucleotide identity (ANI) between all genomes. From these analyses, we concluded that the Rlc includes 18 distinct genospecies, plus 7 unique strains that are not placed in these genospecies. Each genospecies is separated by a distinct gap in ANI values, usually at approximately 96% ANI, implying that it is a 'natural' unit. Five of the genospecies include the type strains of named species: R. laguerreae, R. sophorae, R. ruizarguesonis, "R. indicum" and R. leguminosarum itself. The 16S ribosomal RNA sequence is remarkably diverse within the Rlc, but does not distinguish the genospecies. Partial sequences of housekeeping genes, which have frequently been used to characterize isolate collections, can mostly be assigned unambiguously to a genospecies, but alleles within a genospecies do not always form a clade, so single genes are not a reliable guide to the true phylogeny of the strains. We conclude that access to a large number of genome sequences is a powerful tool for characterizing the diversity of bacteria, and that taxonomic conclusions should be based on all available genome sequences, not just those of type strains.

MAUI-seq: Metabarcoding using amplicons with unique molecular identifiers to improve error correction.

Sequencing and PCR errors are a major challenge when characterizing genetic diversity using high-throughput amplicon sequencing (HTAS). We have developed a multiplexed HTAS method, MAUI-seq, which uses unique molecular identifiers (UMIs) to improve error correction by exploiting variation among sequences associated with a single UMI. Erroneous sequences are recognized because, across the data set, they are over-represented among the minor sequences associated with UMIs. We show that two main advantages of this approach are efficient elimination of chimeric and other erroneous reads, outperforming dada2 and unoise3, and the ability to confidently recognize genuine alleles that are present at low abundance or resemble chimeras. The method provides sensitive and flexible profiling of diversity and is readily adaptable to most HTAS applications, including microbial 16S rRNA profiling and metabarcoding of environmental DNA.

Greenotyper: Image-Based Plant Phenotyping Using Distributed Computing and Deep Learning.

Image-based phenotype data with high temporal resolution offers advantages over end-point measurements in plant quantitative genetics experiments, because growth dynamics can be assessed and analysed for genotype-phenotype association. Recently, network-based camera systems have been deployed as customizable, low-cost phenotyping solutions. Here, we implemented a large, automated image-capture system based on distributed computing using 180 networked Raspberry Pi units that could simultaneously monitor 1,800 white clover (Trifolium repens) plants. The camera system proved stable with an average uptime of 96% across all 180 cameras. For analysis of the captured images, we developed the Greenotyper image analysis pipeline. It detected the location of the plants with a bounding box accuracy of 97.98%, and the U-net-based plant segmentation had an intersection over union accuracy of 0.84 and a pixel accuracy of 0.95. We used Greenotyper to analyze a total of 355,027 images, which required 24-36 h. Automated phenotyping using a large number of static cameras and plants thus proved a cost-effective alternative to systems relying on conveyor belts or mobile cameras.

Symbiosis genes show a unique pattern of introgression and selection within a Rhizobium leguminosarum species complex.

Rhizobia supply legumes with fixed nitrogen using a set of symbiosis genes. These can cross rhizobium species boundaries, but it is unclear how many other genes show similar mobility. Here, we investigate inter-species introgression using de novo assembly of 196 Rhizobium leguminosarum sv. trifolii genomes. The 196 strains constituted a five-species complex, and we calculated introgression scores based on gene-tree traversal to identify 171 genes that frequently cross species boundaries. Rather than relying on the gene order of a single reference strain, we clustered the introgressing genes into four blocks based on population structure-corrected linkage disequilibrium patterns. The two largest blocks comprised 125 genes and included the symbiosis genes, a smaller block contained 43 mainly chromosomal genes, and the last block consisted of three genes with variable genomic location. All introgression events were likely mediated by conjugation, but only the genes in the symbiosis linkage blocks displayed overrepresentation of distinct, high-frequency haplotypes. The three genes in the last block were core genes essential for symbiosis that had, in some cases, been mobilized on symbiosis plasmids. Inter-species introgression is thus not limited to symbiosis genes and plasmids, but other cases are infrequent and show distinct selection signatures.