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Horizon scanning is intended to identify the opportunities and threats associated with technological, regulatory and social change. In 2017 some of the present authors conducted a horizon scan for bioengineering (Wintle et al., 2017). Here we report the results of a new horizon scan that is based on inputs from a larger and more international group of 38 participants. The final list of 20 issues includes topics spanning from the political (the regulation of genomic data, increased philanthropic funding and malicious uses of neurochemicals) to the environmental (crops for changing climates and agricultural gene drives). The early identification of such issues is relevant to researchers, policy-makers and the wider public.

Additional file 9: Table S7. Distribution of Tp1 gene alleles of T. parva from cattle and buffalo in the sub-Saharan region of Africa.

Additional file 1: Table S1. Cattle blood sample distribution across agro-ecological zones.

Additional file 6: Table S5. Tp1 and Tp2 genes alleles with their corresponding antigen variants.

Additional file 4: Figure S3. Rhipicephalus annulatus dorsal and ventral views.

Additional file 7: Figure S6. Rhipicephalus decoloratus dorsal and ventral views.

Additional file 10: Figure S9. Rhipicephalus microplus dorsal and ventral views.

Additional file 12: Figure S4. Phylogenetic tree showing the relationships among concatenated Tp1 and Tp2 nucleotide sequences of 93 T. parva samples from cattle in DRC and Burundi.

Additional file 3: Table S3. Characteristics of 119 T. parva samples obtained from cattle in different agro-ecological zones (AEZs) of The Democratic Republic of Congo and Burundi.

Additional file 5: Table S4. Estimates of evolutionary divergence between gene alleles for Tp1 and Tp2, using proportion nucleotide distance.

Additional file 3: Figure S2. Hyalomma truncatum and Hyalomma rufipes dorsal and ventral views.

Additional file 2: Table S2. Nucleotide and amino acid sequences of Tp1 and Tp2 antigen epitopes from T. parva Muguga reference sequence.

Additional file 10: Table S8. Distribution of Tp2 gene alleles of T. parva from cattle and buffalo in the sub-Saharan region of Africa.

Theileria parva is a protozoan parasite transmitted by the brown ear tick Rhipicephalus appendiculatus that causes East Coast fever (ECF) in cattle, resulting in substantial economic losses in the regions of southern, eastern and central Africa. The schizont form of the parasite transforms the bovine host lymphocytes into actively proliferating cancer-like cells. However, how T. parva causes bovine host cells to proliferate and maintain a cancerous phenotype following infection is still poorly understood. On the other hand, current efforts to develop improved vaccines have identified only a few candidate antigens. In the present paper, we report the first comparative transcriptomic analysis throughout the course of T. parva infection. We observed that the development of sporoblast into sporozoite and then the establishment in the host cells as schizont is accompanied by a drastic increase of upregulated genes in the schizont stage of the parasite. In contrast, the ten highest gene expression values occurred in the arthropod vector stages. A comparative analysis showed that 2845 genes were upregulated in both sporozoite and schizont stages compared to the sporoblast. In addition, 647 were upregulated only in the sporozoite whereas 310 were only upregulated in the schizont. We detected low p67 expression in the schizont stage, an unexpected finding considering that p67 has been reported as a sporozoite stage-specific gene. In contrast, we found that transcription of p67 was 20 times higher in the sporoblast than in the sporozoite. Using the expression profiles of recently identified candidate vaccine antigens as a benchmark for selection for novel potential vaccine candidates, we identified three genes with expression similar to p67 and several other genes similar to Tp1 - Tp10 schizont vaccine antigens. We propose that the antigenicity or chemotherapeutic potential of this panel of new candidate antigens be further investigated. Structural comparisons of the transcripts generated here with the existing gene models for the respective loci revealed indels. Our findings can be used to improve the structural annotation of the T. parva genome, and the identification of alternatively spliced transcripts.

Table S2. cox1 and 12S rRNA BLAST results for species identification and confirmation. (DOCX 16 kb)

Table S6. Rhipicephalus appendiculatus 12S rRNA haplotypes and their distribution among agro-ecological zones of the Great lakes region and other sub-Saharan African countries. (DOCX 15 kb)

Figure S2. Neighbor-joining tree of 12S haplotype sequences for R. appendiculatus across African countries. (DOCX 18 kb)

Table S4. Population genetic structure inferred by analysis of molecular variance (AMOVA) based on cox1 sequences of R. appendiculatus from different agro-ecological zones. (DOCX 13 kb)

Figure S2. Size and frequency of de novo-assembled representative contigs with high similarity to known viruses. In total 68 samples were sequenced and analyzed. Contig size is represented in 0.5 Kb increments in the X axis. The Y axis represents the number of contigs per size class. For each virus, the number of samples categorized as infected is indicated. a MCMV. b SCMV. c MSV. d MYDV-RMV. (PDF 278Â kb)

Figure S1. cox1 mismatch distribution pattern for R. appendiculatus haplogroup A in different agro-ecological zones. (DOCX 193 kb)

Table S3. Polymorphism in the 22 haplotypes of the cox1 gene fragment of R. appendiculatus. (DOCX 21 kb)

Table S1. Rhipicephalus appendiculatus cox1 and 12S rRNA haplotype sequences retrieved from GenBank. (DOCX 16 kb)

Table S5. Evolutionary neutrality, demographic and spatial history of mitochondrial cox1 gene. (DOCX 15 kb)

Figure S3. Partial nucleotide sequence alignment of Kenya samples in group 1, 2 and 3 relative to the Ohio isolate of SCMV (JX188385.1). The coat protein detected in the original description of maize lethal necrosis in Kenya was used for comparison (JX286708.1) [6]. Alignment was generate using MAFFT. NIb and coat protein coding sequences are color coded blue and red, respectively. Coordinates are based on the Ohio isolate (JX188385.1). In group 1 no nucleotide insertions or deletions were observed. Nucleotide substitutions resulted in amino acid substitutions. Group two, had a 39Â nt deletion (8487 to 8525) that resulted in an in-frame deletion of 13 amino acids. Group 3, had low similarity and a 45Â nt deletion between nt 8487 to 8676 that resulted in a 15-amino acid deletion. (PDF 256Â kb)

RT-PCR confirmation of Rhopalosiphum padi virus in maize samples collected from Kitui County. (PDF 84 kb)

Confirmation of the presence of Aphid lethal paralysis virus (ALPV) and a Big Sioux River-like virus. (PDF 1.5 MB)

International audience; The HIV-PDI resource was designed and implemented to address the problems of drug resistance with a central focus on the 3D structure of the target-drug interaction. Clinical and biological data, structural and physico-chemical information and 3D interaction data concerning the targets (HIV protease) and the drugs (ARVs) were meticulously integrated and combined with tools dedicated to study HIV mutations and their consequences on the efficacy of drugs. Here, the capabilities of the HIV-PDI resource are demonstrated for several different scenarios ranging from retrieving information associated with patients to analyzing structural data relating cognate proteins and ligands. HIV-PDI allows such diverse data to be correlated, especially data linking antiretroviral drug (ARV) resistance to a given treatment with changes in three-dimensional interactions between a drug molecule and the mutated protease. Our work is based on the assumption that ARV resistance results from a loss of affinity between the mutated HIV protease and a drug molecule due to subtle changes in the nature of the protein-ligand interaction. Therefore, a set of patients whose resistance to first line treatment was corrected by a second line treatment was selected from the HIV-PDI database for detailed study, and several queries regarding these patients are processed via its graphical user interface. Considering the protease mutations found in the selected set of patients, our retrospective analysis was able to establish in most cases that the first line treatment was not suitable, and it predicted a second line treatment which agreed perfectly with the clincian's prescription. The present study demonstrates the capabilities of HIV-PDI. We anticipate that this decision support tool will help clinicians and researchers find suitable HIV treatments for individual patients. The HIVPDI database is thereby useful as a system of data collection allowing interpretation on the basis of all available information, thus helping in possible decision-makings.

Two closely related potyviruses, bean common mosaic virus (BCMV) and bean common mosaic necrosis virus (BCMNV), are regarded as major constraints on production of common bean (Phaseolus vulgaris L.) in Eastern and Central Africa, where this crop provides a high proportion of dietary protein as well as other nutritional, agronomic, and economic benefits. Previous studies using antibody-based assays and indicator plants indicated that BCMV and BCMNV are both prevalent in bean fields in the region but these approaches cannot distinguish between these potyviruses or detect other viruses that may threaten the crop. In this study, we utilized next generation shotgun sequencing for a metagenomic examination of viruses present in bean plants growing at two locations in Kenya: the University of Nairobi Research Farm in Nairobi's Kabete district and at sites in Kirinyaga County. RNA was extracted from leaves of bean plants exhibiting apparent viral symptoms and sequenced on the Illumina MiSeq platform. We detected BCMNV, cucumber mosaic virus (CMV), and Phaseolus vulgaris alphaendornaviruses 1 and 2 (PvEV1 and 2), with CMV present in the Kirinyaga samples. The CMV strain detected in this study was most closely related to Asian strains, which suggests that it may be a recent introduction to the region. Surprisingly, and in contrast to previous surveys, BCMV was not detected in plants at either location. Some plants were infected with PvEV1 and 2. The detection of PvEV1 and 2 suggests these seed transmitted viruses may be more prevalent in Eastern African bean germplasm than previously thought.

Horizon scanning is intended to identify the opportunities and threats associated with technological, regulatory and social change. In 2017 some of the present authors conducted a horizon scan for bioengineering (Wintle et al., 2017). Here we report the results of a new horizon scan that is based on inputs from a larger and more international group of 38 participants. The final list of 20 issues includes topics spanning from the political (the regulation of genomic data, increased philanthropic funding and malicious uses of neurochemicals) to the environmental (crops for changing climates and agricultural gene drives). The early identification of such issues is relevant to researchers, policy-makers and the wider public.