African Journal of
Plant Science

  • Abbreviation: Afr. J. Plant Sci.
  • Language: English
  • ISSN: 1996-0824
  • DOI: 10.5897/AJPS
  • Start Year: 2007
  • Published Articles: 792

Full Length Research Paper

Occurrence of maize yellow mosaic virus and evidence of co-infection with maize lethal necrosis viruses in Bomet County, Kenya

Chepkorir Tanui
  • Chepkorir Tanui
  • Institute of Biotechnology Research Jomo Kenyatta University of Agriculture and Technology (JKUAT), P. O. Box 62000-00200, Juja, Kenya.
  • Google Scholar
Sylvester Anami
  • Sylvester Anami
  • Institute of Biotechnology Research Jomo Kenyatta University of Agriculture and Technology (JKUAT), P. O. Box 62000-00200, Juja, Kenya.
  • Google Scholar
Jane Wamaitha
  • Jane Wamaitha
  • Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization (KALRO), P. O. Box 1473-00800, Kenya.
  • Google Scholar
Bramwel Waswa Wanjala
  • Bramwel Waswa Wanjala
  • Biotechnology Research Institute, Kenya Agricultural and Livestock Research Organization (KALRO), P. O. Box 1473-00800, Kenya.
  • Google Scholar


  •  Received: 21 September 2021
  •  Accepted: 11 November 2021
  •  Published: 31 December 2021

 ABSTRACT

Maize Lethal Necrosis (MLN) disease is caused by synergistic interaction between maize chlorotic mottle virus (MCMV) and sugarcane mosaic virus (SCMV). However, some East African countries have detected maize infecting polerovirus named maize yellow mosaic virus (MaYMV) also known as maize yellow dwarf virus (MYDV-RMV) co-infecting maize with MLN viruses. Maize yellow dwarf virus occurrence and distribution in different parts of Kenya are not yet elucidated. This study aimed to establish the occurrence of MaYMV in maize and sorghum in Bomet County, MLN hotspot region in Kenya. Maize (n=90) and sorghum (n=19) samples were collected from East and Central sub-counties of Bomet County in 2019/2020. Reverse transcription-polymerase chain reaction (RT-PCR) protocol was developed and optimized for screening the samples using specific primers. Amplicons of 600, 250 and 169 bp were generated for MaYMV, MCMV and SCMV, respectively. The analysis revealed 56% (62/109) of the samples tested positive for MaYMV co-infecting maize with MLN viruses. Sanger sequencing of representative samples confirmed the presence of MaYMV. BLASTN analysis showed 95-100% sequence identity to MaYMV/MYDV-RMV hence confirmed the occurrence of MaYMV infecting maize and sorghum in Bomet County whose impacts is a potential threat to food security.

 

Key words: Occurrence, co-infection, maize lethal necrosis, maize yellow mosaic virus, maize chlorotic mottle virus, sugarcane mosaic virus.


 INTRODUCTION

Maize (Zea mays L.) and Sorghum (Sorghum bicolor L. Moench) are important cereals crops essential for livelihood and food security in Kenya (De Groote et al., 2016; Njagi et al., 2019). The former can flourish in a wide range of climatic conditions; therefore, it can be cultivated extensively throughout the country (Mwathi et al., 2016). The latter is drought tolerant and mainly grown in arid and semi-arid parts of Kenya, including Western, Eastern, North Rift valley, and some parts of the Central province of Kenya (Kagwiria et al., 2019). They are primarily grown for their grains and are closely related in their utilization (One Acre Fund, 2020). For example, they can be milled to flour to make 'ugali' and porridge, typical Kenyan meals. Further, maize and sorghum grains have other uses. They can be brewed into alcoholic beverages, boiled and consumed like rice, baked like wheat, and popped like popcorn for snack (Esilaba et al., 2019; One Acre Fund, 2020).

 

Maize serves as a leading staple food and source of income and livelihood for most rural farmers in Kenya (Naseem et al., 2018). However, the emergence of Maize Lethal Necrosis (MLN) disease affected maize production making sorghum the second preferred alternative cereal after maize (One Acre Fund, 2020). In East Africa MLN disease is caused by synergistic interaction of MCMV and SCMV (Kiruwa et al., 2016). However, recent MLN studies identified a novel Polerovirus known as MaYMV/MYDV-RMV infecting maize and sorghum in mixed infection with the MLN causing viruses (Massawe et al., 2018; Yahaya et al., 2019).

 

Maize yellow mosaic virus (MaYMV) belongs to the genus Polerovirus (Chen et al., 2016). Together with Luteovirus and Enamovirus genera; they are members of the Luteoviridae family (Garcia-Ruiz et al., 2020). Maize yellow mosaic virus was first reported in China and later in South America and Africa (Chen et al., 2016; Bernreiter et al., 2017; Palanga et al., 2017; Yahaya et al., 2019). Empirical evidence associated MaYMV with yellow mosaic and leaf reddening symptoms with an estimated yield loss of 10-30% in maize (Stewart et al., 2020; Bernreiter et al., 2017). Maize yellow mosaic virus is phloem limited (Garcia-Ruiz et al., 2020). It is efficiently transmitted by corn leaf aphid Rhopalosiphum maidis and partially transmitted by Rhopalosiphum padi (R.padi) (Stewart et al., 2020). Its genome comprises linear, monopartite, positive-sense single-stranded RNAs, which is approximately 5.3-5.7 kb (Chen et al., 2016). Additionally, the genome has six open reading frames (ORF) encoding protein P0-P5 with three untranslated regions (UTRs), including the 51 UTR, the 31 UTR, and the intergenic UTR between ORF2 and ORF3. Typical to other polerovirus, P0 protein of MaYMV is a potent silencing suppressor (Holste, 2020).

 

Poleroviruses are likely to interact among themselves or with other viruses from different families. Some of these associations include synergistic interaction between Beet western yellows virus (BWYV) a Polerovirus with Beet mosaic virus (BtMV) a Potyvirus which leads to fast systemic infection with early and severe symptoms development (Garcia-Ruiz et al., 2020). Similar results were demonstrated by Stewart and Willie (2021) who reported stunting symptoms in MLN triple infection (MCMV+SCMV+MaYMV) which further progressed to MLN disease. Besides, farmers in Kenya plant maize and sorghum in traditional farming system or in the nearby field (Demissie et al., 2020). This practice allows the horizontal spread of common pathogens infecting the two crops such as MCMV, SCMV and MaYMV. Thus, acting as an inoculum for the new non-infected plants especially in Bomet County where farmers practice continuous maize cropping.

 

Despite the detection of MaYMV in mixed infection with MLN viruses, most studies in Kenya continue to focus on understanding MCMV and SCMV interaction in association with MLN without any consideration of MaYMV co-infection, a potential threat to food security. Therefore, this study sought to establish the occurrence of MaYMV co-infection with MLN viruses in Bomet County, an MLN hotspot region in Kenya.


 MATERIALS AND METHODS

Study area

 

Bomet County (Figure 1) was selected for this study because it is the epicentre of MLN infections. Furthermore, it is classified among the MLN hotspot regions in Kenya (Wangai et al., 2012). The County lies between latitudes 0° 29' and 1° 03' south and between longitudes 35° 05' and 35° 35' east (County Government of Bomet, 2018). Maize yellow mosaic virus incidence in Kenya remained to be established. However, previous MLN studies identified MaYMV in mixed infection with MLN causing viruses suggesting potential with high distribution (Massawe et al., 2018; Mwatuni et al., 2020).

 

 

Sample collection and RNA extraction

 

Maize and sorghum samples were collected from East and Central Sub-Counties of Bomet County in 2019/2020 (Figure 1). In total, 90 symptomatic maize (Figure 2a) and 19 asymptomatic sorghum (Figure 2b) samples were collected from the visited farmers' fields.

 

 

A handheld Global Positioning System (GPS) was used to record the coordinates at the samples collection points. A zig-zag pattern was adopted during sampling in the farmers’ fields. A polythene bag was inverted over one hand and used to grip a portion of the leaf to be sampled. The other hand was used to cut the leaf off into the inverted polythene bag while maintaining the leaf sample inside the pack following a procedure described by Mezzalama et al. (2015). The samples were labelled and placed in a cool box containing dry ice and transported to Kenya Agricultural and Livestock Organization (KALRO) Biotechnology laboratory and stored at -80°C.

 

In the laboratory, total RNA was extracted from 0.1 g of the collected maize and sorghum samples using TRIzolTM reagent (Thermo Fisher Scientific, Waltham, MA, USA) following manufacturers' instructions.

 

 

Primer design and validation

 

Maize yellow mosaic virus primers were designed using primer3 software package. A Kenyan isolate with the accession number (MH205607.1) was used as a reference sequence. Eleven overlapping primers were generated spanning the entire reference genome (Table S1). To validate the primers efficiency, Reverse transcription-polymerase chain reaction (RT-PCR) was carried out using MaYMV positive RNA sample previously used for generation of complete sequence of MYDV-RMV (MH205607.1) with the eleven overlapping primers.

 

 

Reverse transcription polymerase chain reaction optimization and detection

 

Two step RT-PCR was optimized using specific primers (MYDV-RMV_1, MCMV_1 and SCMV_1) and representative symptomatic maize samples from Bomet county. Reverse transcription was carried out using Thermo Scientific RevertAid First Strand cDNA Synthesis kit following manufacturers' instructions. Briefly, RNA (2 µl) was used as a template. A 12 µl reaction volume containing 1 µl of Oligo primer, and 9 µl of nuclease-free water was incubated in hot water bath at 65°C for 5 min then chilled immediately on ice. Reverse transcription (RT) was done in 20 µl reaction volume at 45°C for 60 min, followed by reaction termination at 70°C for 5 min.

 

PCR amplification was carried out using Thermo Fisher Scientific DreamTaq PCR Master Mix (2X) which contained DreamTaq DNA Polymerase, 2X DreamTaq buffer, dNTPs, and 4 mM MgCl2 following manufacturers' instructions. Thirty-five cycles of PCR amplification were completed in Veriti™ 96-Well Thermal Cycler (The Applied Biosystems™, Carlsbad, CA, USA). Typically, the PCR program begun with DNA initial denaturation at 95°C for 3 min, followed by denaturation at 95°C for 30 s, primer annealing between 52.8 -60°C (based on the specific primers) for 30 s, extension at 72°C for 1.5 min, and end with a final extension at 72°C for 5 min. The PCR products were analysed by gel electrophoresis in 1.5% agarose gel stained with ethidium bromide. The amplicons were viewed under a UV transilluminator (UVTEC Essentail V6 from UVItec.Ltd Cambridge).

 

 

Sanger sequencing and sequence analysis

 

The PCR products (4 µl) from 19 representative samples were enzymatically cleaned using 10 µl of ExoSAP™ (Thermo Fisher, Waltham, USA) following the manufacturer's instructions. Briefly, enzymatic cleaning was carried out in Veriti thermocycler (Applied Biosystems, Carlsbad, CA, USA) at 37°C for 15 minand 80°C for 15 min. BigDyeTM Terminator Sequencing Kit (Thermo fisher Scientific) was used to perform cycle sequencing using the Sanger Method. Base-calling was performed upon completion of the analysis, AB1 file was generated ready for bioinformatic analysis.

 

The sequenced data was edited for quality using ChromasPro software (Technelysium Pty Ltd, South Brisbane, Australia). Consensus sequences were generated using CAP3 software (Huang and Madan, 1999). BLASTN analysis was used to identify the close relatives of MaYMV. Multiple sequence alignments of the 19 nucleotide sequences from this study and twelve MaYMV nucleotide sequences from NCBI GenBank database were done using CLUSTALW software (Thompson et al., 2002). The downloaded nucleotide sequences included Nigerian isolate (KY684356.1), Ecuador isolate (KY052793.1), Brazil isolate (KY940544.1), China isolates (KU291103.1, KU291100.1, KY378940.1, and KT992824.1), Tanzanian isolate (MG664794.1), Ethiopian isolate (MF684368.1), South Africa isolate (MG570476.1), Kenya isolates (MF974579.2 and MH205607.1) and Cassava brown streak virus (KR911746.1) was used as an outgroup. A phylogenetic tree showing evolutionary relationship was generated using unweighted pair group method with arithmetic mean (UPGMA) method with 1,000 bootstrap replication using Molecular Evolutionary Genetics Analysis (MEGA) version 6 software package (Tamura et al., 2013).


 RESULTS AND DISCUSSION

Primer design and validation

 

Primer design led to generation of eleven overlapping primers for MaYMV (Table S2). Validation of the primers amplified expected 600 bp for all the designed primers as shown in Figure 3a. This revealed the efficiency of all the designed primers for molecular detection of MaYMV. Hence, they can be used for RT-PCR detection and Sanger Sequencing of MaYMV.

 

 

 

Reverse transcription polymerase chain reaction optimization and virus detection

 

The results of RT-PCR optimization amplified 600, 250 and 169 bp for MaYMV, MCMV and SCMV, respectively (Figure 3b). This amplification demonstrates the competency of RT-PCR protocol and the selected specific primers, (MYDV-RMV_1, MCMV_1 and SCMV_1), for detection of MaYMV, MCMV and SCMV, respectively.

 

The RT-PCR detection results (Table 1) revealed double infection of MCMV and SCMV in 19% or (20/109) of the analysed samples. Similar double infection was responsible for maize yield losses of 59% or 300,000 tons in moist transitional zones, mainly in Western Kenya (De Groote et al., 2016).

 

 

Maize lethal necrosis disease is caused by combined infection of Maize chlorotic mottle virus (MCMV) with any member of genus potyvirus such as Sugarcane mosaic virus (SCMV), Maize dwarf mosaic virus (MDMV) or Wheat streak mosaic virus (WSMV) (Isabirye and Rwomushana, 2016). In South Rift region of Kenya, MLN was confirmed to be caused by synergistic interaction of MCMV and SCMV (Leitich et al., 2020). The results showed the continued occurrence of the MLN disease in Bomet County.

 

This study further reveals the occurrence of MaYMV in 56% or (62/109) of the analysed samples (Table 1). It is worth noting that MaYMV was only detected in mixed infection with MLN causing viruses, MCMV and SCMV. These results concurred with those reported by Massawe et al. (2018) who also detected MaYMV in mixed infection with MCMV and SCMV in maize. Besides, the triple infection (MCMV+ SCMV+ MaYMV) was present in all the 18 maize fields where 90 symptomatic maize samples were collected This indicated the occurrence of MaYMV in Bomet County in mixed infection with MCMV and SCMV the MLN causing viruses.

 

The detection rate of triple infection (MCMV+ SCMV+ MaYMV) was higher (62/109) than the detection rate of the double infection (MCMV+SCMV) of MLN causing viruses (20/109) (Table 1). This is indicative of high occurrence of MaYMV in Bomet County as shown in Figure 1, which may be a potential threat to food security. Furthermore the synergistic interaction between MaYMV and the MLN causing viruses (MCMV+SCMV+MaYMV) enhance stunting in maize which further progressed to MLN disease despite suppression of increased MCMV titer induced by SCMV in double infection (Stewart and Willie, 2021). Thus, presenting unknown potential disease impact of MaYMV in single and in mixed infection.

 

SCMV was the most abundant virus in the study site. It was detected in triple and double infection and 8% (9/109) samples were positive for its single infection. Thus, it was confirmed that SCMV was the major potyvirus causing MLN in South Rift region of Kenya as reported by Leitich et al. (2020). All the sorghum samples tested negative for MaYMV by RT-PCR. However, representative Sanger Sequenced sorghum samples were positive. This might be associated with low sensitivity of RT-PCR as compared to Sanger Sequencing which is able to detect low viral concentration. Besides MaYMV are restricted to the phloem (Garcia-Ruiz et al., 2020), hence the viral concentration on the leaf tissue could be low.

 

The low MLN incidence on sorghum observed in this study could be attributed to the tolerance nature of sorghum to MLN viruses which results in low viral titer level. Plant cultivars play a crucial role in disease symptoms expression and viral titer concentration during plant development for example MLN susceptible maize hybrid developed severe MLN symptoms coupled with increased viral titer concentration at an early stage of development as compared to less susceptible hybrid (Leitich et al., 2021). Besides, all the sorghum collected were landraces (local varieties) which the farmers believe they are resilient and can resist diseases.

 

Polerovirus are reported to be the most damaging viruses infecting more than 32 monocot and dicot plants in Luteoviridae family (Garcia-Ruiz et al., 2020). For instance, the Potato leafroll virus, the first identified Polerovirus, is associated with a 50-60% yield loss in potatoes equivalent to 100 million dollars annually in the United States (Holste, 2020). Likewise, MaYMV occurrence may be accountable for the substantial maize losses observed in the farmers’ fields in Bomet County.

 

Synergistic interaction between poleroviruses and other viruses have been reported by Holste (2020). A classical illustration is the interaction between Potato leafroll virus (PLRV) (Polerovirus) co-infection with either Potato virus X (PVX) or Potato virus Y (PVY) (Potyviruses), resulting in increased symptoms severity and yield loss (Garcia-Ruiz et al., 2020). Similarly, the synergistic interaction of MaYMV with MLN viruses MCMV and SCMV may be responsible for the severe symptoms characterized by bright yellow symptoms on the leaf surface and stunted growth with small or no ear formation of maize as observed in the farmers' fields in Bomet County. Furthermore, the triple infection (MCMV+SCMV+MaYMV) is reported to cause maize stunting which advance to MLN disease (Stewart and Willie, 2021).

 

 

Sanger sequencing and sequence analysis

 

Sanger Sequencing further confirmed the presence of MaYMV in both maize and sorghum (Table S2). BLASTN analysis showed 95-100% identity of our samples to MaYMV/MYDV-RMV with 100% coverage. Similar results were reported by Wamaitha et al. (2018) who also detected MaYMV in mixed infection with MCMV and SCMV using Next Generation Sequence (NGS) in maize and sorghum samples collected in Embu and Kirinyaga County which are low MLN hotspot regions in Kenya.

 

Phylogenetic analysis of 19 sequences from this study and 12 from NCBI database were separated into four groups based on geographical location named as Africa Isolate (AI), Asian Isolate (ASI) and South America (SA). The 19 isolates from this study exclusively clustered together with isolates from different parts of Africa as shown in Figure 4. This showed close relationship and insignificant variation among the MaYMV African isolates. The same observation was made by Yahaya et al. (2019) who also described geography specificity of MaYMV independent of their host. Interestingly, the African isolates shared a node with the China Isolates. This indicated a potential common ancestral origin. However, the South America isolates were separated displaying some variation between them. Cassava brown streak virus (CBSV) was used as an outgroup.

 


 CONCLUSION

This study established the occurrence of recently reported maize infecting polerovirus MaYMV/MYDV-RMV in co-infection with MLN causing viruses in Bomet County. The results showed that MaYMV co-infect maize and sorghum with MLN causing viruses MCMV and SCMV and the triple infection of (MCMV+SCMV+MaYMV) is higher 56% compared to the double infection (MCMV+SCMV) which was 19%. Considering the potential losses associated with the MaYMV co-infection, we recommend MaYMV to be integrated in development of MLN control/management strategies and a need to determine the impact associated with MaYMV in single and mixed infection on yield.

 


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interests.

 


 ACKNOWLEDGEMENTS

The authors gratefully appreciate Dr. Catherine Taracha, the Centre Director Biotechnology Research Institute (BioRI) Kabete Centre, for providing workspace at the Molecular and Biotechnology laboratory and screen houses and also express gratitude to Prof Ben E. Lockhart from University of Minnesota USA, Department of Plant Pathology for facilitating the synthesis of the designed MaYMV primers. Mary Lechuta and Michael Njoroge for their assistance in laboratory and bioinformatic analysis, respectively. This work was funded by the World Bank through Kenya Climate Smart Agriculture (KCSAP) (Grant Number 20076) and National Research Fund (NRF).

 



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