Maize is the most important cereal crop and a staple food in sub-Saharan Africa. With over 5 million hectares of its land planted with this crop and a per capita consumption of 128 kg, Tanzania is one of the largest producers and consumers of maize in eastern and southern Africa [1
]. Maize is intensively cultivated in the southern highland, lake, and northern zones of Tanzania [2
]. Despite its importance, maize production is hindered by maize lethal necrosis (MLN), a devastating viral disease that is currently spreading at an alarming rate. The disease was first reported in the Southern Rift Valley region of Kenya in 2011 [3
] and Mwanza and Arusha regions in Tanzania in 2012 [4
]. MLN has since spread to several other maize-producing African countries, including Rwanda, the Democratic Republic of the Congo, and Ethiopia [5
]. The disease is characterized by elongated yellow streaks parallel to leaf veins, chlorotic mottling, and necrosis [9
]. The necrotic symptoms occur at different stages of maize development and can lead to 100% crop loss.
The reported causative agents of MLN in eastern and central Africa are Maize chlorotic mottle virus
(MCMV) and Sugarcane mosaic virus
]. MCMV is a positive-sense single-stranded RNA virus belonging to the family Tombusviridae
and has a genome size of 4.4 kb [11
]. SCMV is a positive-sense single-stranded RNA virus belonging to the family Potyviridae
and has a genome size of 9.6 kb [12
]. MCMV alone infects maize causing leaf mosaic and moderate stunting symptoms, while co-infection of maize by MCMV and SCMV results in more severe symptoms of stunting, necrosis, and eventually plant death [9
]. Other viruses in the Potyviridae
family such as Wheat streak mosaic virus
(WSMV) and Maize dwarf mosaic virus
(MDMV) have also been reported to synergize with MCMV causing MLN [13
]. However, these other viruses have not been reported to associate with MLN in eastern and central Africa. Given the complexity of this disease and the economic importance of maize in sub-Saharan Africa, there is a need for a targeted investigation of the possible presence of other MLN-associated viruses apart from MCMV and SCMV in Tanzania.
Sustainable control of plant diseases requires a good understanding of the epidemiological aspects such as the biology of the causal pathogen(s) and the favorable environmental conditions for compatible pathogen-host interactions [14
]. The combination of several viral strains makes the disease even more complex because of varying favorable conditions for virulence and transmission of the viruses. The transmission of MLN has been characterized as mainly vector-borne, but also soil-borne and seed-borne [7
]. MCMV, which has mainly been associated with MLN symptoms, is transmitted by thrips [15
], rootworms [13
], and beetles [17
]. Most cereal potyviruses
are transmitted by aphids [16
Initial reports of maize lethal necrosis problems in East Africa were based on experiences by farmers and agricultural extension agents, complemented with diagnostics of the disease by international research organizations [3
]. An accurate identification of MLN symptoms by the farmers can play a key role in preventing the spread of the disease, as they can mechanically remove the infected plants and/or apply pesticides to control the vectors. Furthermore, farmers can provide useful information about the occurrence and extent of the spread of this and other diseases [18
]. To safeguard maize production and food security in sub-Saharan Africa, there is a need to conduct comprehensive research (etiological, epidemiological, and genetic studies) to facilitate the development of effective and sustainable MLN control measures. Recent advances in diagnostic technologies including next generation sequencing (NGS) tools have been useful for the identification of new viruses and their variants in infected plants [10
]. The objectives of the current study are to contribute to the existing knowledge on the status of MLN in northern Tanzania by characterizing the causative viruses using NGS, to assess farmers’ awareness and experiences on the spread and damage of MLN, to investigate the prevalence of MLN across villages within different agro-ecological zones, and to identify possible other viruses that co-infect maize.
The current study began as a response to an alert by farmers about a disease that been spreading fast within the maize growing regions of northern Tanzania. The study confirms that the disease was maize lethal necrosis (MLN). This disease is not new in Tanzania, as its occurrence and the causal organisms have been previously reportedin Arusha and Mwanza [7
]. In this paper, we provide information on the occurrence of MLN in a wider geographical area, confirming the presence of the causal viruses for MLN (SCMV and MCMV) and other viruses, which can potentially threaten maize production in Tanzania. The study entailed interviewing farmers’ about their experiences, direct observation of MLN symptoms in the fields and a confirmation of the causal viruses by RT-PCR and next-generation sequencing (Illumina Miseq) analysis of symptomatic maize from Arusha, Manyara and Kilimanjaro regions of Tanzania.
In addition to MCMV and SCMV complete sequences, NGS analysis revealed the occurrence of MSVand signatures of MYDV, MDMV, BYDV, and SrMV that have been previously reported to cause serious infections in maize [27
]. Given that MSV is widely distributed [7
] and a recent study reported the presence of MYDV in a mixed infection with MLN viruses [30
], we extrapolate the possibility of evolved interactions. The interactions could besynergistic, helper-dependence, cross-protection, replacement or mutual suppression that can lead to either an increase or decrease in replication and/or transmission of any of the viruses [32
]. Mixed infections in many viruses have been reported to cause severe symptoms as well as provide opportunities for recombination events leading to the emergence of new viral species [36
]. It is not known whether the other viruses detected in this study (except SCMV and MCMV) can affect MLN symptoms. The present study observed a higher incidence of MCMV (97%) with a higher co-infection (62%) (MCMV and SCMV) in symptomatic maize compared to previous reports (62% of MCMV incidence and a co-infection of 51%) [7
]. This difference in co-infection could be caused by changes in conditions that favor the pathosystem. There is a need to analyze the cause of these observations and the associated drivers in further laboratory and field tests.
Based on phylogenetic analysis, MCMV isolates identified in this study are highly similar to those from other east African countries (Figure 1
). The observed similarity of MCMV isolates from the current study and those from the neighboring countries showsthat combined regional efforts should be applied to control MLN. Currently, initiatives have been taken by the International Maize and Wheat Improvement Center (CIMMYT) and other agricultural research institutes across east Africa to breed for MLN resistant maize varieties. Putative genes and quantitative trait loci (QTL) for MLN resistance have been identified in tropical maize germplasm and will be useful in the breeding efforts [38
]. Interestingly, we observed significant genetic dissimilarities between the SCMV recovered in the current study compared to those from other east African countries retrieved from the NCBI. The observed differences in SCMV could likely indicate that the virus is more sensitive to variations in climate across geographical locations, as pointed out by other authors [7
]. Furthermore, SCMV is an RNA virus, and its variations could be caused by inherent replication errors due to the lack of proofreading activity of RNA-dependent RNA polymerases [41
]. Previous reports show that quarantine measures to control the movement of MCMV in uninfected areas could be more effective than similar measures for controlling SCMV [5
]. It is not known whether the observed diversity in SCMV affects MLN and whether this could complicate the management of the disease.
We emphasize the importance for regional scientists to utilize farmers’ degree of awareness in identifying MLN hot spots and facilitate their capacity to collect data from a wider geographical area to enhance better understanding of the disease complex and epidemiology. The findings in the current study revealed that the majority of the farmers across the three regions had observed MLN in four consecutive years since the first report in 2012. The highest MLN prevalence (complete yield loss in 88% of the surveyed farms) was observed in 2014. A similar magnitude of maize yield loss was previously reported in Western Kenya, with the incidence of MCMV increasing between the years 2013 and 2014 [8
]. The devastating disease mainly damages small-scale farmers’ field crops, who cannot afford to buy pesticides to control the vectors, and yet their livelihood depends mostly on agriculture. Small-scale farmers contribute to over 80% of Tanzania’s total maize production [2
]. Thus, the reported maize yield losses due to MLN indicate a major threat to the per capita income and food security at large in Tanzania, an African country that is struggling to feed its burgeoning population. Given that small-scale farmers cannot afford to buy pesticides and their current methods used to control MLN (e.g., roguing diseased plants) are not very effective, there is a need to look for more sustainable and targeted methods such as breeding for resistant maize varieties.
Farmers reported a high incidence of MLN in irrigated farms, where continuous maize cropping is practiced throughout the year. As continuous cropping can lead to a build-up and retention of the viral inoculum, there is a need to train farmers on crop rotation methods. Maize could be replaced by other crops (e.g., legumes), as these would not only break the pathogen cycle but also increase dietary diversity. Besides crop rotation, farmers should be encouraged to practice intercropping of maize with crops that are not affected by either MCMV or SCMV. Intercropping creates a vegetation diversity that can divert or repel the vectors of MLN [44
]. In the current study, both farmers and the research assistants observed the two main vectors of MLN (thrips and aphids) in farmers’ fields. The presence of vectors enhances a fast spread of most vector-bone plant viruses. Although seed transmission could play a role in the transmission of MLN [7
], farmers should be trained on integrated pest management strategies to sustainably control the vectors and the spread of MLN. Pull and push technology has been developed and validated as an effective tool for controlling insect-pests within east Africa [47
]. As the region works towards developing MLN resistant maize, it is paramount to train farmers on how to apply the push and pull, together with other feasible strategies to effectively combat the disease and hence enhance food security in Tanzania.
4. Materials and Methods
4.1. Study Site and Design
A two-part survey was conducted in Arusha, Kilimanjaro, and Manyara regions in northern Tanzania in 2015. First, because of farmers’ frequent complains of maize crop loss, our research team aimed to establish whether the reported disease was MLN and whether there were other possible viruses that co-infect maize, based on symptoms and molecular diagnostics. Second, the team conducted a survey to assess farmers’ awareness and experiences on MLN including control strategies.
4.2. Assessment of Prevalence and Collection of Samples
Based on information on the reported MLN-like symptoms, including leaf mosaic, stunting, yellowing in leaf margins, and necrosis from agricultural extension agents, farms (n
= 41) were selected for direct visual observation and sampling of infected maize plants. The farms were within villages stratified across the maize producing AEZs in Northern Tanzania (Figure 4
). Within each farm, plants with MLN-like symptoms were scouted in quadrants of one-hundred maize plants (three random quadrants of each quarter-acre of the farm). The mean of the counts of the symptomatic plants (%) was considered as the magnitude of the disease in the sampled farm. MLN prevalence across the villages within AEZs and the regions were compared based on the percentages of symptomatic plants in the sampled farms (Table 1
). Consequently, maize leaf samples (n
= 223) of randomly selected plants containing viral-like symptoms were collected across the farms and dried in silica gel prior to laboratory analysis.
4.3. Detection of MCMV Using Reverse-Transcription Polymerase Chain Reaction (RT-PCR)
All leaf samples collected were tested for the presence of MCMV using RT-PCR. Total RNA was extracted from the samples (n
= 223) using a ZR Plant RNA MinPrepTM
kit (Zymo Research, Irvine, CA, USA) after homogenization using mortar and pestle in liquid nitrogen. The quality of RNA was checked using formamide-denatured agarose gel electrophoresis on 1x TAE [48
] and quantified using a Qubit™ 2.0 fluorometer (Thermo Fisher Scientific, Waltham, MA). Complementary DNA (cDNA) synthesis was performed using the Maxima First Strand cDNA synthesis Kit for RT-qPCR (Thermo Fisher Scientific, Waltham, MA) as per manufacturer’ s instructions, followed by PCR. Reactions consisted of 10 µL of 2x One Taq master mix with standard buffer [20 mM Tris-HCl, 1.8 mM NH4
Cl, 22 mM KCl, 0.2 mM dNTPs, 5% glycerol, 0.06% IGEPAL CA-630, 0.05% Tween 20 and 25 U/mL One Taq DNA Polymerase] (New England Bio Labs, Ipswich, MA), 0.1 µL (10 µM) of the forward (5′-CGCGGCTGACAAGCAAAT-3′) and reverse primer (5′-ACTGGTTGTTCCGGTCTTG-3′) targeting MCMV, 2 µL cDNA and 7.8 µL of sterile water for a final volume of 20 µL. The thermocycler conditions were as follows: an initial denaturation at 95 °C for 3 min followed by 30 cycles of denaturation at 95 °C for 30 sec, annealing at 49.4 °C for 30 sec, elongation at 72 °C for 1 min and a final extension step at 72 °C for 15 min. The PCR products were visualized under UV light on a stained (gel red) 1.2% agarose gel following electrophoresis.
4.4. Characterization of MLN Viruses by Next Generation Sequencing
Based on the results of the RT-PCR for MCMV, a subset of samples positive for MCMV from Kilimanjaro (n = 15), Arusha (n = 22), and Manyara (n = 11) were selected for NGS characterization of the MLN causal viruses. The samples (n = 48) were used for the construction of sequence libraries using the Illumina TruSeq RNA library prep kit following the manufacturer’s instructions (Illumina, San Diego, CA, USA). Briefly, 0.5µg of RNA/sample was fragmented using the fragmentation mix (Elute, Prime, Fragment High Mix) followed by first strand and second strand cDNA synthesis. The double-stranded cDNA was purified using Agencourt AMPure XP magnetic beads (Beckman Coulter, Indianapolis, IN, USA) followed by end repair and adapters ligation. The ligated ds-cDNA was amplified in a PCR using universal and index primers. Resulting libraries were purified using Agencourt AMPure XP magnetic beads. Libraries’ quality and quantity were assessed with the Agilent Tape Station 2200 system (Agilent Technologies, Santa Clara, CA, USA) and a Qubit™ fluorometer (Thermo Fisher Scientific, Waltham, MA, USA), respectively. The libraries were then normalized to a concentration of 10nM, pooled, and diluted to a final concentration of 6.5 pM. Pooled libraries were sequenced on the Illumina MiSeq system at the BecA-ILRI Hub (Nairobi, Kenya) generating 151 paired-end reads.
4.5. Assessment of Farmers’ Awareness and Experiences on MLN
A random group of farmers (n
= 137) selected with the help of extension staff representing different villages (Lyamungu Kati, Mandaka Mnono, Mlangarini, Ngaramtoni, and Ayasanda) within the three regions of Northern Tanzania were interviewed about specific aspects relating to awareness and experiences of MLN in 2015. Farmers provided information about whether they had observed MLN symptoms (pictures of the symptomatic plants were shown to farmers) in their maize crop within the past four years (2012–2015), the approximate percentage of maize losses due to MLN in comparison with previous yields, seed types and origin used, the predominant insect pests identified by using pictures and maize insect pests identifier from CIMMYT [49
], whether they sprayed pesticides to control the insects, and any other methods adopted to manage MLN in their farms.
4.6. Data Analysis
The quality assessment of the sequence reads generated was performed using Fastqc v0.11.2 [50
]. The FASTX_toolkit [51
] and SolexaQA [52
] were used for the removal of adapters and poor quality sequences. De novo assembly of the reads was performed using Trinity v2.2.1 [53
]. Assembled sequences were then blasted against a locally installed plant virus database using BLASTN 2.2.30+, TBLASTX 2.2.30+ [54
]. Identities of the viruses present in each sample were visualized using Krona [21
]. Reference mapping was performed for individual samples against the most similar reference genome downloaded from NCBI, using CLC Genomics Workbench 5.5.1 software (Qiagen, Germany).
Multiple sequence alignment of the viruses was performed using CLC Genomics Workbench 5.5.1 software. Nucleotide sequences of MCMV and SCMV coat proteins were used for phylogenetic analysis in Mega 6.0 [55
], where a maximum likelihood method based on the Kimura 2-parameter model [56
] was used with 1000 bootstrap replicates. Sequences of MCMV, SCMV, and MSV were submitted to the GenBank using the BankIt sequence submission tool [57
Farmers’ interviews and field observation data were analyzed using JMP Pro v.12 (SAS Institute Inc. 2013). Means of symptomatic plants across villages within the regions and AEZs were computed and compared in a nested linear regression model.
This study contributes to a better understanding of MLN in Northern Tanzania, by providing information on disease prevalence across different AEZs in Kilimanjaro, Arusha and Manyara regions in 2015, detection of the associated viruses and indicates possible measures to manage the disease. Furthermore, the study detected other potential viruses that could present a threat to maize production in Northern Tanzania. The complete sequences of the virus isolates reported in this study provide additional resources for the development of diagnostic tools and for enhancing understanding of genetic relatedness of isolates of MCMV, SCMV, and MSV across Africa and their management. Given that the observational and sampling component of the current study were limited in scope, we propose further studies to expand these aspects in order to assess the seasonal variations of the epidemics, the role of the interaction among multiple viruses on severity of MLN, how the genetic variability of SCMV affects MLN, and the role of vectors in respect to changes in the climatic factors.