Corrigendum to "A highly specific tool for identification of Xanthomonas vasicola pv. musacearum based on five Xvm-specific coding sequences" [Heliyon 4 (12) (December 2018) Article e01080].

[This corrects the article DOI: 10.1016/j.heliyon.2018.e01080.].

Influence of altitude as a proxy for temperature on key Musa pests and diseases in watershed areas of Burundi and Rwanda.

Pests and diseases are key biotic constraints limiting banana production among smallholder farmers in Eastern and Central Africa. Climate changemay favour pest and disease development and further exacerbate the vulnerability of smallholder farming systems to biotic constraints. Information on effects of climate change on pests and pathogens of banana is required byby policy makers and researchers in designing control strategies and adaptation plans. Since altitude is inversely related to temperature, this study used the occurrence of key banana pests and diseases along an altitude gradient as a proxy for the potential impact of changes in temperature associated with global warming on pests and diseases. We assessed the occurrence of banana pests and diseases in 93 banana fields across three altitude ranges in Burundi and 99 fields distributed in two altitude ranges in Rwanda watersheds. Incidence and prevalence of Banana Bunchy Top Disease (BBTD) and Fusarium wilt (FW) was significantly associated with temperature and altitude in Burundi, revealing that increasing temperatures may lead to upward movement of banana diseases. No significant associations with temperature and altitude were observed for weevils, nematodes and Xanthomonas wilt of banana (BXW). Data collected in this study provides a baseline to verify and guide modelling work to predict future pest and disease distribution according to climate change scenarios. Such information is useful in informing policy makers and designing appropriate management strategies.

Transfer of Xanthomonas campestris pv. arecae and X. campestris pv. musacearum to X. vasicola (Vauterin) as X. vasicola pv. arecae comb. nov. and X. vasicola pv. musacearum comb. nov. and Description of X. vasicola pv. vasculorum pv. nov.

We present an amended description of the bacterial species Xanthomonas vasicola to include the causative agent of banana Xanthomonas wilt, as well as strains that cause disease on Areca palm, Tripsacum grass, sugarcane, and maize. Genome-sequence data reveal that these strains all share more than 98% average nucleotide with each other and with the type strain. Our analyses and proposals should help to resolve the taxonomic confusion that surrounds some of these pathogens and help to prevent future use of invalid names.[Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

A new Multi Locus Variable Number of Tandem Repeat Analysis Scheme for epidemiological surveillance of Xanthomonas vasicola pv. musacearum, the plant pathogen causing bacterial wilt on banana and enset.

Xanthomonas vasicola pv. musacearum (Xvm) which causes Xanthomonas wilt (XW) on banana (Musa accuminata x balbisiana) and enset (Ensete ventricosum), is closely related to the species Xanthomonas vasicola that contains the pathovars vasculorum (Xvv) and holcicola (Xvh), respectively pathogenic to sugarcane and sorghum. Xvm is considered a monomorphic bacterium whose intra-pathovar diversity remains poorly understood. With the sudden emergence of Xvm within east and central Africa coupled with the unknown origin of one of the two sublineages suggested for Xvm, attention has shifted to adapting technologies that focus on identifying the origin and distribution of the genetic diversity within this pathogen. Although microbiological and conventional molecular diagnostics have been useful in pathogen identification. Recent advances have ushered in an era of genomic epidemiology that aids in characterizing monomorphic pathogens. To unravel the origin and pathways of the recent emergence of XW in Eastern and Central Africa, there was a need for a genotyping tool adapted for molecular epidemiology. Multi-Locus Variable Number of Tandem Repeat Analysis (MLVA) is able to resolve the evolutionary patterns and invasion routes of a pathogen. In this study, we identified microsatellite loci from nine published Xvm genome sequences. Of the 36 detected microsatellite loci, 21 were selected for primer design and 19 determined to be highly typeable, specific, reproducible and polymorphic with two- to four- alleles per locus on a sub-collection. The 19 markers were multiplexed and applied to genotype 335 Xvm strains isolated from seven countries over several years. The microsatellite markers grouped the Xvm collection into three clusters; with two similar to the SNP-based sublineages 1 and 2 and a new cluster 3, revealing an unknown diversity in Ethiopia. Five of the 19 markers had alleles present in both Xvm and Xanthomonas vasicola pathovars holcicola and vasculorum, supporting the phylogenetic closeliness of these three pathovars. Thank to the public availability of the haplotypes on the MLVABank database, this highly reliable and polymorphic genotyping tool can be further used in a transnational surveillance network to monitor the spread and evolution of XW throughout Africa.. It will inform and guide management of Xvm both in banana-based and enset-based cropping systems. Due to the suitability of MLVA-19 markers for population genetic analyses, this genotyping tool will also be used in future microevolution studies.

Risks Posed by Intercrops and Weeds as Alternative Hosts to Xanthomonas campestris pv. musacearum in Banana Fields.

Alternative host plants are important in the survival and perpetuation of several crop pathogens and have been suspected to play a role in the survival of Xanthomonas campestris pv. musacearum (Xcm) and perpetuation of Xanthomonas wilt (XW) disease of banana and enset. This study determined the potential risk posed by two weeds (Canna spp. and wild sorghum) and common banana intercrops (maize, millet, sorghum, taro, and sugarcane) as alternative hosts to Xcm. The study employed screenhouse experiments, laboratory procedures and diagnosis of banana fields in XW-affected landscapes. Typical XW symptoms were only observed in artificially inoculated Canna sp., with an incidence of 96%. Leaf lesions characteristic of xanthomonads occurred on millet (50%) and sorghum (35%), though the plants recovered. No symptoms occurred in maize, sugarcane, taro or wild sorghum. However, Xcm was recovered from all these plant species, with higher recoveries in Canna sp. (47%), millet (27%), sugarcane (27%), and wild sorghum (25%). Only isolates recovered from Canna sp., millet, sorghum and wild sorghum caused disease in banana plantlets. The presence and incidence of XW on-farm was positively associated with the presence of susceptible ABB Musa genotypes and negatively with number of banana cultivars on farm and household access to training on XW management. Only 0.02% of field sampled Canna spp. plants had Xcm. Risk posed by Canna spp. on-farm could be limited to tool transmission as it has persistent floral bracts that prevent insect-mediated infections. Given the high susceptibility, perennial nature and propagation through rhizomes of Canna sp., it could pose a moderate-high risk, thus warranting some attention in the management of XW disease. Sugarcane could offer a low-moderate risk due to its perennial nature and propagation through rhizomes while risk from maize, millet, and sorghum was deemed zero-low due to their annual nature, wind-mediated mode of pollination and propagation through seed. Understanding the interactions of a crop pathogen with other plants is thus important when diversifying agroecosystems. The study findings also suggest other factors such as cultivar composition and management of the disease at farm and landscape level to be important in the perpetuation of XW disease.

A highly specific tool for identification of Xanthomonas vasicola pv. musacearum based on five Xvm-specific coding sequences.

Xanthomonas vasicola pv. musacearum (Xvm) is a bacterial pathogen responsible for the economically important Xanthomonas wilt disease on banana and enset crops in Sub-Saharan Africa. Given that the symptoms are similar to those of other diseases, molecular diagnosis is essential to unambiguously identify this pathogen and distinguish it from closely related strains not pathogenic on these hosts. Currently, Xvm identification is based on polymerase chain reaction (PCR) with GspDm primers, targeting the gene encoding general secretory protein D. Experimental results and examination of genomic sequences revealed poor specificity of the GspDm PCR. Here, we present and validate five new Xvm-specific primers amplifying only Xvm strains.