Comparative genomics of Bradyrhizobium japonicum CPAC 15 and Bradyrhizobium diazoefficiens CPAC 7: elite model strains for understanding symbiotic performance with soybean.

The soybean-Bradyrhizobium symbiosis can be highly efficient in fixing nitrogen, but few genomic sequences of elite inoculant strains are available. Here we contribute with information on the genomes of two commercial strains that are broadly applied to soybean crops in the tropics. B. japonicum CPAC 15 (=SEMIA 5079) is outstanding in its saprophytic capacity and competitiveness, whereas B. diazoefficiens CPAC 7 (=SEMIA 5080) is known for its high efficiency in fixing nitrogen. Both are well adapted to tropical soils. The genomes of CPAC 15 and CPAC 7 were compared to each other and also to those of B. japonicum USDA 6T and B. diazoefficiens USDA 110T. Differences in genome size were found between species, with B. japonicum having larger genomes than B. diazoefficiens. Although most of the four genomes were syntenic, genome rearrangements within and between species were observed, including events in the symbiosis island. In addition to the symbiotic region, several genomic islands were identified. Altogether, these features must confer high genomic plasticity that might explain adaptation and differences in symbiotic performance. It was not possible to attribute known functions to half of the predicted genes. About 10% of the genomes was composed of exclusive genes of each strain, but up to 98% of them were of unknown function or coded for mobile genetic elements. In CPAC 15, more genes were associated with secondary metabolites, nutrient transport, iron-acquisition and IAA metabolism, potentially correlated with higher saprophytic capacity and competitiveness than seen with CPAC 7. In CPAC 7, more genes were related to the metabolism of amino acids and hydrogen uptake, potentially correlated with higher efficiency of nitrogen fixation than seen with CPAC 15. Several differences and similarities detected between the two elite soybean-inoculant strains and between the two species of Bradyrhizobium provide new insights into adaptation to tropical soils, efficiency of N2 fixation, nodulation and competitiveness

Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence

Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs.h(-1); p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring

Genome-wide identification of the Phaseolus vulgaris sRNAome using small RNA and degradome sequencing

Background: MiRNAs and phasiRNAs are negative regulators of gene expression. These small RNAs have been extensively studied in plant model species but only 10 mature microRNAs are present in miRBase version 21, the most used miRNA database, and no phasiRNAs have been identified for the model legume Phaseolus vulgaris. Thanks to the recent availability of the first version of the common bean genome, degradome data and small RNA libraries, we are able to present here a catalog of the microRNAs and phasiRNAs for this organism and, particularly, we suggest new protagonists in the symbiotic nodulation events.Results: We identified a set of 185 mature miRNAs, including 121 previously unpublished sequences, encoded by 307 precursors and distributed in 98 families. Degradome data allowed us to identify a total of 181 targets for these miRNAs. We reveal two regulatory networks involving conserved miRNAs: those known to play crucial roles in the establishment of nodules, and novel miRNAs present only in common bean, suggesting a specific role for these sequences. In addition, we identified 125 loci that potentially produce phased small RNAs, with 47 of them having all the characteristics of being triggered by a total of 31 miRNAs, including 14 new miRNAs identified in this study.Conclusions: We provide here a set of new small RNAs that contribute to the broader knowledge of the sRNAome of Phaseolus vulgaris. Thanks to the identification of the miRNA targets from degradome analysis and the construction of regulatory networks between the mature microRNAs, we present here the probable functional regulation associated with the sRNAome and, particularly, in N2-fixing symbiotic nodules.Peer reviewedBiochemistry and Molecular Biolog

Comparative genomics of Bradyrhizobium japonicum CPAC 15 and Bradyrhizobium diazoefficiens CPAC 7: elite model strains for understanding symbiotic performance with soybean.

The soybean-Bradyrhizobium symbiosis can be highly efficient in fixing nitrogen, but few genomic sequences of elite inoculant strains are available. Here we contribute with information on the genomes of two commercial strains that are broadly applied to soybean crops in the tropics. B. japonicum CPAC 15 (=SEMIA 5079) is outstanding in its saprophytic capacity and competitiveness, whereas B. diazoefficiens CPAC 7 (=SEMIA 5080) is known for its high efficiency in fixing nitrogen. Both are well adapted to tropical soils. The genomes of CPAC 15 and CPAC 7 were compared to each other and also to those of B. japonicum USDA 6T and B. diazoefficiens USDA 110T. Differences in genome size were found between species, with B. japonicum having larger genomes than B. diazoefficiens. Although most of the four genomes were syntenic, genome rearrangements within and between species were observed, including events in the symbiosis island. In addition to the symbiotic region, several genomic islands were identified. Altogether, these features must confer high genomic plasticity that might explain adaptation and differences in symbiotic performance. It was not possible to attribute known functions to half of the predicted genes. About 10% of the genomes was composed of exclusive genes of each strain, but up to 98% of them were of unknown function or coded for mobile genetic elements. In CPAC 15, more genes were associated with secondary metabolites, nutrient transport, iron-acquisition and IAA metabolism, potentially correlated with higher saprophytic capacity and competitiveness than seen with CPAC 7. In CPAC 7, more genes were related to the metabolism of amino acids and hydrogen uptake, potentially correlated with higher efficiency of nitrogen fixation than seen with CPAC 15. Several differences and similarities detected between the two elite soybean-inoculant strains and between the two species of Bradyrhizobium provide new insights into adaptation to tropical soils, efficiency of N2 fixation, nodulation and competitiveness.201

Rhizobial extrachromosomal replicon variability, stability and expression in natural niches

AbstractIn bacteria, niche adaptation may be determined by mobile extrachromosomal elements. A remarkable characteristic of Rhizobium and Ensifer (Sinorhizobium) but also of Agrobacterium species is that almost half of the genome is contained in several large extrachromosomal replicons (ERs). They encode a plethora of functions, some of them required for bacterial survival, niche adaptation, plasmid transfer or stability. In spite of this, plasmid loss is common in rhizobia upon subculturing. Rhizobial gene-expression studies in plant rhizospheres with novel results from transcriptomic analysis of Rhizobium phaseoli in maize and Phaseolus vulgaris roots highlight the role of ERs in natural niches and allowed the identification of common extrachromosomal genes expressed in association with plant rootlets and the replicons involved

Genome of Rhizobium leucaenae strains CFN 299T and CPAO 29.8: searching for genes related to a successful symbiotic performance under stressful conditions.

Background: Common bean (Phaseolus vulgaris L.) is the most important legume cropped worldwide for food production and its agronomic performance can be greatly improved if the benefits from symbiotic nitrogen fixation are maximized. The legume is known for its high promiscuity in nodulating with several Rhizobium species, but those belonging to the Rhizobium tropici “group” are the most successful and efficient in fixing nitrogen in tropical acid soils. Rhizobium leucaenae belongs to this group, which is abundant in the Brazilian “Cerrados” soils and frequently submitted to several environmental stresses. Here we present the first high-quality genome drafts of R. leucaenae, including the type strain CFN 299T and the very efficient strain CPAO 29.8. Our main objective was to identify features that explain the successful capacity of R. leucaenae in nodulating common bean under stressful environmental conditions. Results: The genomes of R. leucaenae strains CFN 299T and CPAO 29.8 were estimated at 6.7–6.8 Mbp; 7015 and 6899 coding sequences (CDS) were predicted, respectively, 6264 of which are common to both strains. The genomes of both strains present a large number of CDS that may confer tolerance of high temperatures, acid soils, salinity and water deficiency. Types I, II, IV-pili, IV and V secretion systems were present in both strains and might help soil and host colonization as well as the symbiotic performance under stressful conditions. The symbiotic plasmid of CPAO 29.8 is highly similar to already described tropici pSyms, including five copies of nodD and three of nodA genes. R. leucaenae CFN 299T is capable of synthesizing Nod factors in the absence of flavonoids when submitted to osmotic stress, indicating that under abiotic stress the regulation of nod genes might be different. Conclusion: A detailed study of the genes putatively related to stress tolerance in R. leucaenae highlighted an intricate pattern comprising a variety of mechanisms that are probably orchestrated to tolerate the stressful conditions to which the strains are submitted on a daily basis. The capacity to synthesize Nod factors under abiotic stress might follow the same regulatory pathways as in CIAT 899T and may help both to improve bacterial survival and to expand host range to guarantee the perpetuation of the symbiosis.CNPq (National Council for Scientific and Technological Development)Science without Borders (400205/2012-5)Ministerio de Economía y Competitividad (FPU14_00160

Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence

Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs.h(-1); p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring