Open access peer-reviewed chapter

The Microbiome of Cassava (Manihot esculanta)

Written By

Andri Frediansyah

Submitted: 30 March 2021 Reviewed: 21 April 2021 Published: 08 May 2021

DOI: 10.5772/intechopen.97818

From the Edited Volume

Cassava - Biology, Production, and Use

Edited by Andri Frediansyah

Chapter metrics overview

642 Chapter Downloads

View Full Metrics

Abstract

The plant microbiome, like the plant, influences the processes that lead to plant development, health, and crop productivity. Cassava is a perennial herbaceous plant native to South America that has been cultivated for centuries as a staple food throughout the world. Not only is cassava a good source of carbohydrates, but it also has a high tolerance for a variety of phenotypic conditions, and the majority of cassava plants are susceptible to a variety of diseases. Thus, using cassava as a model, this chapter discusses the plant microbiome. We discuss the structure and function of the microbiome, as well as the technique for studying microbiomes. Additionally, we conducted a systematic review of references pertaining to the microbiome of the cassava plant using cultivation-dependent or cultivation-independent methods. Numerous significant genera of bacteria and fungi are found in cassava’s phyllosphere and rhizosphere, including groups of gram-negative bacteria, gram-positive Actinobacteria, and gram-positive non Actinobacteria. Additionally, we identified critical organisms in the phyllosphere and rhizosphere. Cassava endophytes also produce antifungal secondary metabolites such as pumilacidins and surfactin. The investigation of their phenotypes and interactions with the cassava plant will aid in increasing productivity.

Keywords

  • cassava microbiome
  • metagenomic
  • plant microbiome
  • staple crop
  • phyllosphere
  • rhizosphere

1. Introduction

The microbiome was defined for the first time as the ecological niche within the human body where symbionts, pathogens, and commensal or neutral microorganisms coexist [1]. It is then widely used in a variety of habitats infested with microorganisms, including plants and their microbes. As with the plant itself, the plant microbiome influences the various processes that contribute to plant development, health, and crop productivity [2]. These connections have an effect on both nutrient absorption and susceptibility to biotic and abiotic stress [3]. Furthermore, factors such as regional landscape, plant species and cultivars, genotypes, soil, soil-borne microorganisms, climate and other environmental factors, farming management practices, and crop safety all influence the microbiome’s dynamic and distribution [4, 5, 6]. Moreover, microbes associated with plants colonized both the plant’s surface and internal tissue. They are frequently referred to as the plant’s second genome due to their presence in the inner plant bodies as well [7]. Additionally, the complexity of nearly all plant microbiomes including its rhizosphere is still unknown [8]. Additionally, there is still a knowledge gap regarding plant-colonizing microbes, their interactions, and the microbiome’s structure.

Cassava (Manihot esculenta Crantz) is an herbaceous perennial plant native to South America that is a member of the Euphorbiaceae family [9]. It is widely grown in tropical and subtropical regions [10]. Cassava was grown on a global scale of up to 201 million hectares in 2017, with Africa accounting for more than 60% of the total [11]. Furthermore, Nigeria was the largest producer of cassava, followed by Thailand and Indonesia [9, 11]. Cassava’s tuberous roots contain an unexpected amount of starch, making it an extremely valuable food source, particularly in developing countries. As a result, cassava has developed into a staple food for roughly 800 million people worldwide [11]. Crop management and fertilization [12], food process development and fermentation [9, 13, 14, 15, 16, 17], component functional status [18], cassava disease [19, 20], and raw material and product quality control [21, 22], are just a few of the cassava-related studies published worldwide.

Cassava plants, like other plants, support a diverse range of microorganisms and plant-microbial interactions that enable the crop to perform a variety of task [23]. As illustrated in Figure 1, the cassava microbiome is distributed throughout the plant’s body, including the portion of the upper and lower leaf surface (phyllosphere) that contains stems (caulosphere) and leaves (phylloplane), as well as the portion of the bellow grounds that contains roots and a trace of associated soil (rhizosphere). Within compartments, fungal and bacterial (and, to a lesser extent, archaeal) communities can be classified as epiphytes, which colonize the exterior surface of plant tissues, and endophytes, which penetrate the outermost plant cell layer (epidermis) and colonize the internal intercellular and intracellular sections of plant tissues.

Figure 1.

The distribution of microbiome in cassava plant.

Cassava is not only a good source of carbohydrates, but it also has a high tolerance for a variety of phenotypic conditions, including heat, nutrient deficiency, and drought [24, 25]. Additionally, the majority of cassava plants are susceptible to a variety of diseases, including cassava brown streak disease, cassava mosaic disease, and cassava bacterial blight [26, 27, 28]. As a result, our understanding of these correlations with the vastness of the microbiome is still limited at the moment. Thus, in this chapter, we will use cassava as a model plant to investigate its microbiome. Each cassava plant compartment is thoroughly examined. Additionally, we discuss the microbiome’s structure and function, as well as the data collection methods used. Finally, we investigate the possibility of manipulating the microbiome to increase cassava crop productivity.

Advertisement

2. The technique to study cassava microbiome

There are two approaches to studying the cassava microbiome: cultivation-dependent and cultivation-independent approaches. Historically, the cultivation-dependent method was used to evaluate microbial communities. This strategy is based on the technique of microbial isolation. However, this is debatable given that only 1% of microbes can be cultured in the laboratory [29]. This is because a variety of factors affect microbes’ cultivability, including nutrients, oxygen levels, temperature, salinity, pH, and growth factor [30, 31]. This technique has numerous advantages, including the ability to cultivate culturable microbes, the ability to quantify the cell, and the ability to identify viable cells in samples. Therefore, as consequence, using this approach results in a low level of taxonomic diversity, contamination, the requirement of time and resources, and the reliance on phenotypical biochemical characterization.

Without cultivating the bacteria, a molecular technique utilizing unprecedented amounts of 16S RNA or ITS data, such as denaturing and temperature gradient gel electrophoresis [32] and single-strand conformation polymorphism [33]. Additionally, polymorphisms in the terminal restriction fragment length [34], restriction analysis of amplified ribosomal DNA [35], random amplified polymorphic DNA [36], and sequencing of SSU ribosomal DNA [37], can be used to determine the microbial composition of the sample.

Moreover, recent advances in high-throughput sequencing, combined with a variety of omics techniques [38, 39, 40, 41], have enabled researchers to gain a new level of understanding of the microbiome’s structure and dynamics, as well as host-microbiome interactions. It also can provide a wealth of information about the microbial partners of a plant, including their identity and relative abundance [42, 43]. Therefore, employing this cultivation-independent approach, using sequencing technology, may result in an avalanche of data, which must be mitigated by using an experimental design and technique that are appropriate for the scientific question at hand [44, 45, 46]. It is critical to have a thorough understanding of the various types of biases and errors that can occur when selecting the system.

In plant microbiome research, including cassava, high-throughput sequencing of marker gene amplicons is increasingly being used to elucidate the structure, organization, and spatial distribution of microbial communities [5, 47, 48, 49]. Amplicon sequencing has the distinct advantage of being able to target specific microbe classes or even functional genes. Although the high specificity of amplicon sequencing enables it to positively classify unusual organisms, it is susceptible to contamination due to its sensitive nature [50]. Thus, any experiment involving a significant amount of amplicon sequencing should include both positive and negative controls [51].

When it comes to confirming the existence of rare organisms, shotgun metagenomics is less robust than amplicon sequencing [52, 53, 54]. The abundances measured, on the other hand, are less skewed, and the data can be binned into draft genome sequences [54, 55, 56]. These enable us to connect taxonomic identity to essential plant functions like nitrogen fixation, or to determine whether symbionts can communicate with plants via secretion systems or effectors. Metagenomic approaches also can supplement other high-throughput molecular methods such as transcriptomics, proteomics, and metabolomics [57, 58, 59].

In general, these techniques provide access to a microbial genetic pool that cultivation-dependent techniques do not provide, which means that microbial isolates do not need to be cultured because sequences are generated directly from environmental samples. High specificity and the ability to freeze samples for later use are also advantages. However, we were unable to obtain colonies for further research. Furthermore, there is a high risk of contamination with this technique, and the researchers are unable to distinguish between living and dead cells. Last but not least, the method is dependent on a well-designed primer plate, precise sequence identification, and a high-quality cell lysis process.

Advertisement

3. The phyllosphere and its microbiome

The phyllosphere is the first compartment in the microbiome of the cassava plant. This compartment is the visible portion of the leaf surface on both the upper and lower leaf surfaces [60]. Cover only the area above the ground, however. Microbial cells can colonize arial plant surfaces such as leaves (phylloplane) and stems in this environment (caulosphere) [61]. Leaves may be one of the largest microbial habitats on the planet, with an estimated global terrestrial leaf surface area of 108 km2 [62]. Along with bacteria, filamentous fungi, archaea, viruses, yeast, bryophytes, lichens, protozoa, and nematodes thrive in this environment. Bacteria, on the other hand, have been found to be the most abundant cell type in the phyllosphere, with up to 107 cells cm−2 of leaf tissues present [63]. Another type of microorganism, filamentous fungi, appears to be more prevalent [63]. For all of these leaves’ living things, water and food are scarce resources.

Special consideration will be given to endophytes when it comes to the cassava microbial community. Endophytic microorganisms are microorganisms that live inside the tissues of plants without harming the host [64]. The majority of endophytes spread systemically via the xylem to various plant compartments such as the stem, leaves, and fruits. They maintain the plant’s viability throughout or part of its life cycle by colonizing the internal leaf tissues (endophyllosphere) and internal plant reproductive tissue [65]. Due to the fact that they live within the tissue, their nutritional requirements are also reduced [66]. As consequences, they multiply and grow rapidly within the plant tissue. They defend themselves by producing toxins and enzymes that aid them in colonizing the plant and competing with other microorganisms. Additionally, several of them produce beneficial secondary metabolites such as antibiotics, antifungals, anti-inflammatory agents, and biological control agents as part of the host’s development and physiological process [67].

Melo, Fiore [68] successfully cultured several endophytes bacteria from the cassava phyllosphere using a cultivation-dependent approach. They were able to grow bacteria from cassava stems (23 strains) and leaves (17 strains). The 16S rRNA coupled with fatty acid methyl ester (FAME) assay could only be used to examine a small number of bacteria. Bacillus was found to be the most prevalent bacteria in this study [68]. Bacillus anthracis, Bacillus pumilus, Brachybacterium paraconglomeratum, and Brevibacillus brevi were discovered in the cassava stem, as well as gram-negative bacteria Enterobacter aerogenes, E. cancerogenus, Salmonella enteritidis, S. bongori, S. choleraesus, Escherichia coli, and Serratia rubidae [68]. Furthermore, Bacillus cereus, Clavibacter michiganensis, Curtobacterium luteum, Microbacterium aerborescens, Microbacterium imperial, and Ochrobactrum antropi were the predominant bacteria in cassava leaves, followed by gram-negative bacteria such as Pseudomonas rhodesiae and Enterobacter cloacae [68], as shown in Table 1. They also demonstrated that environmental factors largely determined the phyllosphere’s microbial composition.

GeneraStemsLeaves
BulleraVV
FusariumVV
AlternariaVV
CryptococcusVV
SaitoellaVV
PseudpzymaV
RamichloridiumV
AeurobasidiumV
ColletotrichumV
HannaellaV
PhaeosphaeriopsisV
PseudocercosporaV
NigrosporaV
AureobasidiumV
PyrenochaetopsisV
SphaerulinaV

Table 1.

Bacterial genera in cassava stems and leaves [69].

Interestingly, Bacillus pumilus isolated from stem cassava was considered as a biocontrol agent with anti-fungal activity in a detailed study conducted by Melo, Fiore [68]. This rod bacteria produces pumilacidins A–E, as shown in Figure 2. The molecular formulas of pumilacidin A, B, and C are C54H95N7O13, C53H93N7O13, and C56H99N7O13, respectively. Moreover, pumilacidin D and E share a molecular formula of C55H97N7O13. However, the amino acid valine was substituted for ileusin in pumilacidin D, resulting in pumilacidin E.

Figure 2.

Natural products produce by endophytic bacteria in cassava.

Another study from Canova, Petta [70] discovered that Paenibacillus sp. IIRAC-30 from cassava could produce a major surfactin C (Figure 2) compound with the molecular formula C53H93N7O13 and a [M + H]+ on peak at m/z 1037.0. This strain also produces surfactin A (C51H89N7O13, the [M + H]+ on peak is at m/z 1036.9) and surfactin B (C52H91N7O13, the [M + H] + on peak is at m/z 1022.9) as shown in Figure 2. These three secondary metabolites showed antifungal activity.

In addition, using a similar approach, Leite, Pereira [71] discovered 24 bacterial endophytes in cassava stems. According to Leite, Pereira [71] the most common genera discovered in this study were Achromobacter, Bacillus, Burkholderia, Enterobacter, Pantoea, and Pseudomonas. The majority of them demonstrated a variety of biological activities related to cassava plant growth and productivity [71]. In studies conducted by Teixeira and Vieira [72] and Teixeira, Melo [73], several endophytic bacteria from cassava were identified, including Bacillus, Burkholderia, Enterobacter, Escherichia, Salmonella, Serratia, and Stenotropomonas.

Using a cultivation-dependent approach, Hartanti, Susanti [74] successfully cultured 14 endophyte fungi from cassava plants. All of them were examined using the ITS rDNA primers ITS 5 (forward: 5’–TCCTCCGCTTATTGATATGC–3′) and ITS 4 (reverse: 5’–TCCGTAGGTGAACCTGCGC–3). Aspergillus sp., Aspergillus fumigatus, Fusarium falciforme, Fusarium lichenicola, Fusarium oxysporum, Fusarium solani, Lasiodiplodia sp., Nectria pseudotrichia, Penicillium citrinum, and Schizophyllum commune were discovered in this study [74]. Using similar approach, Suciatmih and Supriyati [75] successfully discovered Guignardia endophyllicola, an endophytic fungus, in cassava stems.

Zhang, Zhang [76] used a cultivation-independent approach of shotgun metagenome sequencing to determine the microbiome composition of cassava stems and leaves. The cassava phyllosphere’s key bacterial genera have been identified as a result of this research. Gram-negative bacteria Lelliottia and Stenotrophomonas were isolated from cassava stems, gram-positive bacteria Exiguobacterium were isolated from leaves, and gram-negative bacteria [76], as shown in Table 1, the most prevalent genera were Methylobacterium from leaves. Therefore, the major fungi genera appear to be more complex than previously believed. Zhang, Zhang [69] discovered Pseudpzyma, Ramichloridium, Aeurobasidium, Colletotrichum, and Hannaella were among the key fungal genera identified from cassava stems as shown in Table 2. Six fungal genera were discovered in the casava leaves, including Phaeosphaeriopsis, Pseudocercospora, Nigrospora, Aureobasidium, Pyrenochaetopsis, and Sphaerulina (Table 2). In-depth analysis showed that Bullera, Alternaria, Fusarium, Cryptococcus, and Saitolla were identified in both phyllosphere samples [69].

GeneraStemsLeaves
EnterobacterVV
PantoeaVV
PseudomonasVV
EscherichiaVV
StenotrophomonasV
AeromonasVV
ChloroplastVV
KlebsiellaVV
PaenibacillusV
ShigellaVV
LelliottiaV
AcinetobacterVV
ExiguobacteriumV
ErwiniaVV
MethylobacteriumV

Table 2.

Fungal genera in cassava stems and leaves [69].

In general, bacteria, fungi, and other microbes migrate into the plant phyllosphere via rain water, air, seeds, pollution, and animal sources [77]. Additionally, research indicates that some of these microbes are passed down from generation to generation [78]. The distribution of microbiomes in the phyllosphere may vary due to nutritional heterogeneity, such as carbon source uptake [79].

Advertisement

4. The rhizosphere and its microbiome

The soil ecosystem is one of the most complex and diverse on the planet. The soil contains a complex microcosm that interacts with the roots of plants [80]. This category includes archaea, bacteria, filamentous fungi, yeast, bryophytes, lichens, and protozoa. This soil organism significantly aids in the growth of various plants. Complex biochemical processes, such as the release of essential substances from organic matter, enable plants to access nutrients such as nitrogen, sulfur, and phosphorus, as well as essential growth hormones and toxic degradation products [81]. Furthermore, by providing pathogen protection, non-pathogenic microbes can alter plant immune responses [82].

In general, when plants live in a composite environment, they interact with specific soil microorganisms that live in the rhizosphere, the region around their roots [83]. This compartment is the narrow area of soil immediately surrounding the root system where the plant and microbes interact. It is defined by biological, chemical, and physical gradients that vary radially and longitudinally along the roots. The plant microbiome beneath the ground may be constructed in two stages: first, the rhizosphere may be colonized by a subset of bulk microbial communities, and then the rhizoplane (root surface) and root endosphere may be colonized by a subset of the rhizosphere communities [84].

Thousands of distinct microbial communities, including pathogens, mutualists, and commensals, coexist in the rhizosphere of cassava roots, just as they do in other plants. Their connection to the rhizosphere is complex and dynamic. However, it may be facilitated by the root exudate produced by the plant. Exudates play a critical role in plant–soil feedback by regulating plant survival in the face of antibiotic and biotic stress [85]. To the detriment of neighboring plants, plants regulate the rhizosphere via root-secreted metabolites [86]. Additionally, it is a critical mechanism of communication between plants and soil microbes [87]. The majority of root exudation takes place at the root’s tip [88]. The root tip is the first part of the plant to investigate a new soil environment, and it plays a critical role in root responses to environmental stimuli [88]. Roots secrete a diverse array of primary metabolites, including amino acids, growth factors, vitamins, fatty acids, hormones, and antimicrobial compounds, which are believed to be lost passively from the root and utilized by rhizosphere-dwelling microbes [89].

Additionally, via a complex mechanism, exudates play a critical role in shaping microbial diversity [90]. However, no specific research on the microbial shaping of cassava plants in response to exudate has been conducted. However, research on other plants may explain this discrepancy.

Bacillus, a genus bacteria, in tomatoes produce systemic exudates of acylsugar metabolites, as demonstrated in a study of Korenblum, Dong [91]. Additionally, the metabolomes and transcriptomes of tomato leaves and systemic roots change in response to the rhizosphere’s microbial community structure [91]. In-depth analyses of the systemic root metabolome suggest that glycosylated azelaic acid may function as a signaling molecule that is induced by the microbiome and then excreted as free azelaic acid [91]. The results indicate that the rhizosphere microbiome assembly plays a molecular and chemical role in systemically induced root metabolite exudation and soil conditioning.

Another study by Strehmel, Böttcher [92] reported that when Arabidopsis thaliana was grown hydroponically, it produced over a hundred distinct metabolites belonging to a variety of chemical classes. This metabolic diversity suggests that plants have developed a sophisticated chemical language for mediating an infinite number of rhizosphere interactions [93]. In conclusion, these studies indicated that structural changes in microbial communities have the potential to significantly alter host phenotypes. Additionally, root exudates have the potential to act as messengers between roots and soil organisms, triggering biological and physical interactions.

Melo, Fiore [68] used a cultivation-dependent approach to successfully cultivate 27 endophyte bacteria from cassava root. According to this study, Bacilluspredominates in cassava root [68]. Gram-negative bacteria (Kluyvera cryocrescens, Stenotrophomonas maltophilia, Enterobacter aerogenes, Klebsiella pneumoniae, and Acidovorax avenae), gram-positive non-Actinobacteria (Bacillus cereus, Bukrhoklderia cepacia, Bradyrhizobium japonicum, and Microbacterium homonis) and gram-positive Actinobacteria (Streptomyces olivaceus) were found in cassava root [68]. Another study by Leite, Pereira [71] used a similar approach to discover 28 bacterial endophytes in the root. The most prevalent bacteria found in cassava root were Bacillus, Burkholderia, Enterobacter, and Pantoea. The majority of them possessed biological properties, including the ability to solubilize inorganic phosphate and the capacity to synthesize Indole acetic acid [71].

Zhang, Zhang [76] successfully identified a variety of bacterial genera in the cassava root. Gram-negative Enterobacter, Pantoea, Pseudomonas, Escherichia, Aeromonas, Chloroplast, Shigella, and Klebsiella were discovered in cassava roots, as were gram-positive Lactococcus and Paenibacillus [69]. Therefore, the only major bacterial genera found in root cassava were gram-positive cocci Lactococcus. Additionally, using a cultivation-dependent technique, Ilyas [94] isolated endophytic fungi Fusarium sp. and Penicilium sp. from cassava roots.

A recent study took a non-cultivation-dependent approach. Zhang, Zhang [76] discovered 11 fungal genera in the cassava root, including Bullera, Fusarium, and Alternaria, as well as eight key fungal genera that were not found in the cassava stems and leaves, including Humicola, Penicillium, Nigrospora, Beauveria, Thozetella, Codinaeopsis, Paraphaeosphaeria, and Dinemasporium [76]. Additionally, Ascomycota have been described as domination endophyte assemblages. According to a study conducted by Li, Yan [95], Stephanonectaria, Cutaneotrichosporon, Pleurotus, Wallemia, Aspergillus, Gibberella, Lachancea, Yamadazyma, Neurospora, Cladosporium, Wickerhamomyces, Penicillium, Diaporthe, Fusarium, and Lasiodioplodia were successfully detected in cassava root. Therefore, Lasiodioplodia was genus-level dominant [95].

Advertisement

5. The effect of plant genotypes and genetic background on plant microbiome

Plants live harmoniously with a diverse array of microorganisms. These microbes, which include bacteria, archaea, filamentous fungi, and nematodes, can live as endophytes or epiphytes, as well as in any plant organ or tissue, including cassava. A rapidly growing body of literature has documented the influence of the microbiome on critical plant traits such as disease resistance [96], nutrient acquisition and growth [97], and abiotic stress tolerance [98]. Thus, the microbiome can be viewed as an extended phenotype of the plant genome that can assist plants in dealing with environmental stressors.

Li, Yan [95] investigated the microbiome of various cassava cultivars in a study. They examined four cassava cultivars, two of which were resistant to rot (SC124 and SC205) and two of which were susceptible to rot (SC124 and SC205) (SC10 and SC5). Surprisingly, both groups were dominated by gram-positive Weissella (family Leuconostaceae) close behind with gram-negative Serratia (family Enterobacteriaceae). At the phylum level, the most prevalent phyla were Proteobacteria and Firmicutes [95]. Thus, Lasidiplodia (family Botryosphaeraceae) was the most prevalent fungus in the susceptible and tolerant groups, followed by Fusarium from family Nectriaceae and Diaporthe from family Diaporthaceae [95]. Thus, susceptible cultivars have been found to harbor bacteria such as Paenalcaligenes, Parapusillomonas, Corticicoccus, and Lachinoclostridium that have not been detected in tolerant cultivars [95]. On the other hand, Phascolarctobacterium, Olivibacter, and Citrobacter were key genera found exclusively in the tolerant group [95]. Culvularia was the most frequently encountered fungus among vulnerable groups. Hortaea and Agaricostilbomyctes were significantly more abundant in the tolerant cultivar, indicating the importance of relative abundance [95].

Zhang, Zhang [69] is also investigating the microbiome of cassava plants that is associated with disease resistance. Interestingly, several microorganisms involved in disease resistance include Lactococcus sp., Pantoea dispersa, and Saccharomyces cerevisiae [69]. Additionally, the presence of nisin-related genes in Lactococcus was positively associated with disease resistance in cassava plants [69].

Advertisement

6. Manipulation of cassava microbiome to improve the yield

Like in other plant, manipulation of the plant microbiome may aid in increasing cassava productivity [99]. By increasing soil bioavailability and plant tolerance to biotic and abiotic stresses, good soil management practices such as the use of beneficial microbes in the Rhizosphere can be achieved, thereby reducing reliance on agricultural chemicals. Crop rotation is also an option for increasing the diversity of soil microbes, which contributes to plant pathogen resistance [100]. A stimulating biofertilizer as shown in Figure 3, which includes co-inoculation of several beneficial strains, including endophytes, will enhance microbial root colonization capability and establish a useful niche for plant pathogens to compete. Bacillus pumilus and Paenibacillus spp. inoculation will improve fungal pathogen suppression on cassava plants as a biofertilizer agent capable of producing pumilacidines and surfactins. Additionally, inoculants containing microorganisms and microbial phosphorus solubilizers capable of producing active indole acetic acid promote the growth of manicured plants (as shown in Figure 3).

Figure 3.

Consortium’s inoculant strategy for improving the cassava microbiome and production.

References

  1. 1. Berg G, Rybakova D, Fischer D, Cernava T, Vergès M-CC, Charles T, et al. Microbiome definition re-visited: old concepts and new challenges. 2020;8(1):1-22
  2. 2. Compant S, Samad A, Faist H, Sessitsch AJJoar. A review on the plant microbiome: ecology, functions, and emerging trends in microbial application. 2019;19:29-37
  3. 3. Trivedi P, Leach JE, Tringe SG, Sa T, Singh BKJNRM. Plant–microbiome interactions: From community assembly to plant health. 2020;18(11):607-621
  4. 4. Mercado-Blanco J, Abrantes I, Barra Caracciolo A, Bevivino A, Ciancio A, Grenni P, et al. Belowground microbiota and the health of tree crops. 2018;9:1006
  5. 5. Turner TR, James EK, Poole PSJGb. The plant microbiome. 2013;14(6):1-10
  6. 6. Schlaeppi K, Bulgarelli DJMP-MI. The plant microbiome at work. 2015;28(3):212-217
  7. 7. Berg G, Grube M, Schloter M, Smalla KJFim. Unraveling the plant microbiome: looking back and future perspectives. 2014;5:148
  8. 8. Fierer NJNRM. Embracing the unknown: disentangling the complexities of the soil microbiome. 2017;15(10):579-90
  9. 9. Frediansyah AJC. Microbial Fermentation as Means of Improving Cassava Production in Indonesia. 2018:123
  10. 10. Frediansyah A, Kurniadi M, Nurhikmat A, Susanto A, editors. Improving quality of mocaf (modified cassava flour) by bioprocess using Lactobacillus plantarum and its utility for foodstuff. International Seminar on Enhanching Grasroot Innovation Competitiveness for Poverty Alleviation (EGICPA); 2012
  11. 11. Cassava [Internet]. IITA Headquarters. 2021 [cited 30 March 2021]. Available from: https://www.iita.org/cropsnew/cassava/
  12. 12. Howeler RHJCB, production, utilization. Cassava mineral nutrition and fertilization. 2002:115-47
  13. 13. Damayanti E, Kurniadi M, Helmi R, Frediansyah A, editors. Single starter Lactobacillus plantarum for modified cassava flour (mocaf) fermentation. IOP Conference Series: Earth and Environmental Science; 2020: IOP Publishing
  14. 14. Frediansyah A, Kurniadi M, Putri NNN, Prasedya ES, editors. The kinetics of enzymes that involved in cassava fermentation produce by co-culture starter of two lactic acid bacteria. AIP Conference Proceedings; 2019: AIP Publishing LLC
  15. 15. Frediansyah A, Kurniadi MJNB. Comparative influence of salinity and temperature on cassava flour product by Lactobacillus plantarum and Lactobacillus acidophilus during single culture fermentation. 2016;8(2):207-214
  16. 16. Frediansyah A, Kurniadi M, editors. Michaelis kinetic analysis of extracellular cellulase and amylase excreted by Lactobacillus plantarum during cassava fermentation. AIP Conference Proceedings; 2017: AIP Publishing LLC
  17. 17. Awoyale W, Alamu EO, Chijioke U, Tran T, Takam Tchuente HN, Ndjouenkeu R, et al. A review of cassava semolina (gari and eba) end-user preferences and implications for varietal trait evaluation. 2021;56(3):1206-22
  18. 18. Li S, Cui Y, Zhou Y, Luo Z, Liu J, Zhao MJJotSoF, et al. The industrial applications of cassava: current status, opportunities and prospects. 2017;97(8):2282-2290
  19. 19. Hillocks R, Jennings DJIJoPM. Cassava brown streak disease: a review of present knowledge and research needs. 2003;49(3):225-234
  20. 20. Olasanmi B, Kyallo M, Yao NJSR. Marker-assisted selection complements phenotypic screening at seedling stage to identify cassava mosaic disease-resistant genotypes in African cassava populations. 2021;11(1):1-8
  21. 21. Ikediobi C, Onyia G, Eluwah CJA, Chemistry B. A rapid and inexpensive enzymatic assay for total cyanide in cassava (Manihot esculenta Crantz) and cassava products. 1980;44(12):2803-9
  22. 22. Arise AK, Malomo SA, Owolabi O, Arise ROJAFS, Technology. Proximate, Antioxidant, and Sensory Properties of Tidbit Snacks from Cassava Enriched with Processed Benniseeds. 2021;1(2):268-274
  23. 23. Guttman DS, McHardy AC, Schulze-Lefert PJNRG. Microbial genome-enabled insights into plant–microorganism interactions. 2014;15(12):797-813
  24. 24. dos Santos Silva PP, e Sousa MB, de Oliveira EJ, Morgante CV, de Oliveira CRS, Vieira SL, et al. Genome-wide association study of drought tolerance in cassava. 2021;217(4):1-26
  25. 25. Moreno-Cadena P, Hoogenboom G, Cock JH, Ramirez-Villegas J, Pypers P, Kreye C, et al. Modeling growth, development and yield of cassava: A review. 2021;267:108140
  26. 26. Dimkpa S, Lawson T, Ukoima HJEJoA, Research F. Growth Performance of Eleven Improved Cassava Varieties and their susceptibility to Some Insect Pests and Diseases in Humid Tropics, Rivers State. 2021;9(2):1-13
  27. 27. Jaemthaworn T, Kalapanulak S, Saithong TJSR. Topological clustering of regulatory genes confers pathogenic tolerance to cassava brown streak virus (CBSV) in cassava. 2021;11(1):1-14
  28. 28. Bizabani C, Rogans SJ, Rey MECJVR. Differential miRNA profiles in South African cassava mosaic virus-infected cassava landraces reveal clues to susceptibility and tolerance to cassava mosaic disease. 2021:198400
  29. 29. Cardenas E, Tiedje JMJCoib. New tools for discovering and characterizing microbial diversity. 2008;19(6):544-549
  30. 30. Pham VH, Kim JJTib. Cultivation of unculturable soil bacteria. 2012;30(9):475-484
  31. 31. Bodor A, Bounedjoum N, Vincze GE, Kis ÁE, Laczi K, Bende G, et al. Challenges of unculturable bacteria: environmental perspectives. 2020;19(1):1-22
  32. 32. Smalla K, Wieland G, Buchner A, Zock A, Parzy J, Kaiser S, et al. Bulk and rhizosphere soil bacterial communities studied by denaturing gradient gel electrophoresis: plant-dependent enrichment and seasonal shifts revealed. 2001;67(10):4742-4751
  33. 33. Srinivasa C, Sharanaiah U, Shivamallu CJABBS. Molecular detection of plant pathogenic bacteria using polymerase chain reaction single-strand conformation polymorphism. 2012;44(3):217-223
  34. 34. Sakai M, Matsuka A, Komura T, Kanazawa SJJomm. Application of a new PCR primer for terminal restriction fragment length polymorphism analysis of the bacterial communities in plant roots. 2004;59(1):81-89
  35. 35. Edel V, Steinberg C, Gautheron N, Alabouvette CJMR. Evaluation of restriction analysis of polymerase chain reaction (PCR)-amplified ribosomal DNA for the identification of Fusarium species. 1997;101(2):179-87
  36. 36. Kelly JDJH. Use of random amplified polymorphic DNA markers in breeding for major gene resistance to plant pathogens. 1995;30(3):461-5
  37. 37. Tae M-S, Eom A-H, Lee SSJM. Sequence analyses of PCR amplified partial SSU of ribosomal DNA for identifying arbuscular mycorrhizal fungi in plant roots. 2002;30(1):13-17
  38. 38. Nilsson RH, Anslan S, Bahram M, Wurzbacher C, Baldrian P, Tedersoo LJNRM. Mycobiome diversity: high-throughput sequencing and identification of fungi. 2019;17(2):95-109
  39. 39. Xu L, Pierroz G, Wipf HM-L, Gao C, Taylor JW, Lemaux PG, et al. Holo-omics for deciphering plant-microbiome interactions. 2021;9(1):1-11
  40. 40. López-Mondéjar R, Kostovčík M, Lladó S, Carro L, García-Fraile P. Exploring the plant microbiome through multi-omics approaches. Probiotics in Agroecosystem: Springer; 2017. p. 233-268
  41. 41. Großkinsky DK, Syaifullah SJ, Roitsch TJJoEB. Integration of multi-omics techniques and physiological phenotyping within a holistic phenomics approach to study senescence in model and crop plants. 2018;69(4):825-844
  42. 42. Mora D, Filardi R, Arioli S, Boeren S, Aalvink S, de Vos WMJMb. Development of omics-based protocols for the microbiological characterization of multi-strain formulations marketed as probiotics: the case of VSL# 3. 2019;12(6):1371-86
  43. 43. Afshari R, Pillidge CJ, Read E, Rochfort S, Dias DA, Osborn AM, et al. New insights into cheddar cheese microbiota-metabolome relationships revealed by integrative analysis of multi-omics data. 2020;10(1):1-13
  44. 44. Sarumi OA, Leung CK, Adetunmbi AOJPCS. Spark-based data analytics of sequence motifs in large omics data. 2018;126:596-605
  45. 45. Harel A, Dalah I, Pietrokovski S, Safran M, Lancet D. Omics data management and annotation. Bioinformatics for Omics Data: Springer; 2011. p. 71-96
  46. 46. Nogales J, Agudo L. A practical protocol for integration of transcriptomics data into genome-scale metabolic reconstructions. Hydrocarbon and Lipid Microbiology Protocols: Springer; 2015. p. 135-152
  47. 47. Fox S, Filichkin S, Mockler TCJPSB. Applications of ultra-high-throughput sequencing. 2009:79-108
  48. 48. Adams IP, Fox A, Boonham N, Massart S, De Jonghe KJEJoPP. The impact of high throughput sequencing on plant health diagnostics. 2018;152(4):909-919
  49. 49. Wei Y-j, Wu Y, Yan Y-z, Zou W, Xue J, Ma W-r, et al. High-throughput sequencing of microbial community diversity in soil, grapes, leaves, grape juice and wine of grapevine from China. 2018;13(3):e0193097
  50. 50. Criscuolo A, Brisse SJG. AlienTrimmer: a tool to quickly and accurately trim off multiple short contaminant sequences from high-throughput sequencing reads. 2013;102(5-6):500-506
  51. 51. Sinha R, Abu-Ali G, Vogtmann E, Fodor AA, Ren B, Amir A, et al. Assessment of variation in microbial community amplicon sequencing by the Microbiome Quality Control (MBQC) project consortium. 2017;35(11):1077
  52. 52. Tessler M, Neumann JS, Afshinnekoo E, Pineda M, Hersch R, Velho LFM, et al. Large-scale differences in microbial biodiversity discovery between 16S amplicon and shotgun sequencing. 2017;7(1):1-14
  53. 53. Knief CJFips. Analysis of plant microbe interactions in the era of next generation sequencing technologies. 2014;5:216
  54. 54. Sedlar K, Kupkova K, Provaznik IJC, Journal SB. Bioinformatics strategies for taxonomy independent binning and visualization of sequences in shotgun metagenomics. 2017;15:48-55
  55. 55. Donovan PD, Gonzalez G, Higgins DG, Butler G, Ito KJPO. Identification of fungi in shotgun metagenomics datasets. 2018;13(2):e0192898
  56. 56. Malmstrom RR, Eloe-Fadrosh EAJM. Advancing genome-resolved metagenomics beyond the shotgun. 2019;4(3)
  57. 57. Beale DJ, Karpe AV, Ahmed WJMm. Beyond metabolomics: a review of multi-omics-based approaches. 2016:289-312
  58. 58. Warnecke F, Hugenholtz PJGb. Building on basic metagenomics with complementary technologies. 2007;8(12):1-5
  59. 59. Lucaciu R, Pelikan C, Gerner SM, Zioutis C, Köstlbacher S, Marx H, et al. A bioinformatics guide to plant microbiome analysis. 2019;10:1313
  60. 60. Gong T, Xin XFJJoIPB. Phyllosphere microbiota: Community dynamics and its interaction with plant hosts. 2021;63(2):297-304
  61. 61. Dhankhar R, Mohanty A, Gulati PJPI, Agriculture S. Microbial Diversity of Phyllosphere: Exploring the Unexplored. 2021:66-90
  62. 62. Sleda MA, Grady K, O'Brien K, Bennett A, Shade AJTFJ. Isolation of Bio Energy Crop Phyllosphere Bacteria from Switchgrass. 2017;31:623.7-.7
  63. 63. Schreiber L, Krimm U, Knoll D, Sayed M, Auling G, Kroppenstedt RMJNP. Plant–microbe interactions: identification of epiphytic bacteria and their ability to alter leaf surface permeability. 2005;166(2):589-594
  64. 64. Reinhold-Hurek B, Hurek TJCoipb. Living inside plants: bacterial endophytes. 2011;14(4):435-443
  65. 65. Osono TJCJoM. Role of phyllosphere fungi of forest trees in the development of decomposer fungal communities and decomposition processes of leaf litter. 2006;52(8):701-16
  66. 66. Hadley G, Ong SJNP. Nutritional requirements of orchid endophytes. 1978;81(3):561-569
  67. 67. Firáková S, Šturdíková M, Múčková MJB. Bioactive secondary metabolites produced by microorganisms associated with plants. 2007;62(3):251-257
  68. 68. Melo FMPd, Fiore MF, Moraes LABd, Silva-Stenico ME, Scramin S, Teixeira MdA, et al. Antifungal compound produced by the cassava endophyte Bacillus pumilus MAIIIM4A. 2009;66(5):583-92
  69. 69. Zhang L, Zhang J, Wei Y, Hu W, Liu G, Zeng H, et al. Microbiome-wide association studies reveal correlations between the structure and metabolism of the rhizosphere microbiome and disease resistance in cassava. 2020
  70. 70. Canova SP, Petta T, Reyes LF, Zucchi TD, Moraes LA, Melo ISJWJoM, et al. Characterization of lipopeptides from Paenibacillus sp.(IIRAC30) suppressing Rhizoctonia solani. 2010;26(12):2241-7
  71. 71. Leite M, Pereira A, Souza A, Andreote F, Freire F, Sobral J. Bioprospection and genetic diversity of endophytic bacteria associated with cassava plant. Revista Caatinga. 2018;31(2):315-325
  72. 72. Teixeira M, Vieira R. Ocorrência de bactérias diazotróficas endofíticas na mandioca (Manihot esculenta Crantz). Embrapa Meio Ambiente Boletim de Pesquisa e Desenvolvimento. 2005
  73. 73. Teixeira MA, Melo ISd, Vieira RF, Costa FEC, Harakava R. Microrganismos endofíticos de mandioca de áreas comerciais e etnovariedades em três estados brasileiros. J Pesquisa agropecuária brasileira. 2007;42(1):42-49
  74. 74. Hartanti AT, Susanti FN, PRASASTY VD, Radiastuti NJBJoBD. Culturable endophytic fungal diversity in cassava tubers of Indonesia. 2021;22(3)
  75. 75. Suciatmih S, Supriyati DJJTL. Isolasi, Identifikasi, dan Skrining Jamur Endofit Penghasil Agen Biokontrol dari Tanaman di Lahan Pertanian dan Hutan Penunjang Gunung Salak. 2016;12(2):171-186
  76. 76. Zhang L, Zhang J, Wei Y, Hu W, Liu G, Zeng H, et al. Microbiome-wide association studies reveal correlations between the structure and metabolism of the rhizosphere microbiome and disease resistance in cassava. J Plant Biotechnology Journal. 2020
  77. 77. Vacher C, Hampe A, Porté AJ, Sauer U, Compant S, Morris CEJAroe, evolution,, et al. The phyllosphere: microbial jungle at the plant–climate interface. 2016;47:1-24
  78. 78. Bordenstein SR, Theis KRJPB. Host biology in light of the microbiome: ten principles of holobionts and hologenomes. 2015;13(8):e1002226
  79. 79. Vorholt JAJNRM. Microbial life in the phyllosphere. 2012;10(12):828-40
  80. 80. Young IM, Crawford JWJS. Interactions and self-organization in the soil-microbe complex. 2004;304(5677):1634-1637
  81. 81. Kuzyakov Y, Xu XJNP. Competition between roots and microorganisms for nitrogen: mechanisms and ecological relevance. 2013;198(3):656-669
  82. 82. Teixeira PJP, Colaianni NR, Fitzpatrick CR, Dangl JLJCoim. Beyond pathogens: microbiota interactions with the plant immune system. 2019;49:7-17
  83. 83. Lynch JM, Brimecombe MJ, De Leij FAJeL. Rhizosphere. 2001
  84. 84. Fernández-González AJ, Villadas PJ, Cabanás CG-L, Valverde-Corredor A, Belaj A, Mercado-Blanco J, et al. Defining the root endosphere and rhizosphere microbiomes from the World Olive Germplasm Collection. 2019;9(1):1-13
  85. 85. Vives-Peris V, de Ollas C, Gómez-Cadenas A, Pérez-Clemente RMJPcr. Root exudates: from plant to rhizosphere and beyond. 2020;39(1):3-17
  86. 86. Bais HP, Weir TL, Perry LG, Gilroy S, Vivanco JMJARPB. The role of root exudates in rhizosphere interactions with plants and other organisms. 2006;57:233-266
  87. 87. Narula N, Kothe E, Behl RKJJoAB, Quality F. Role of root exudates in plant-microbe interactions. 2012;82(2):122-130
  88. 88. Badri DV, Vivanco JMJP, cell, environment. Regulation and function of root exudates. 2009;32(6):666-681
  89. 89. Volkov V, Schwenke HJP. A Quest for Mechanisms of Plant Root Exudation Brings New Results and Models, 300 Years after Hales. 2021;10(1):38
  90. 90. Sasse J, Martinoia E, Northen TJTips. Feed your friends: do plant exudates shape the root microbiome? 2018;23(1):25-41
  91. 91. Korenblum E, Dong Y, Szymanski J, Panda S, Jozwiak A, Massalha H, et al. Rhizosphere microbiome mediates systemic root metabolite exudation by root-to-root signaling. 2020;117(7):3874-3883
  92. 92. Strehmel N, Böttcher C, Schmidt S, Scheel DJP. Profiling of secondary metabolites in root exudates of Arabidopsis thaliana. 2014;108:35-46
  93. 93. Venturi V, Keel CJTips. Signaling in the rhizosphere. 2016;21(3):187-198
  94. 94. Ilyas M. Isolation and Identification of mould inhabiting plant rizosphere in Gunung Mutis Natural Reserve, East Nusa Tenggara. Biodiversitas Journal of Biological Diversity. 2006;7(3)
  95. 95. Li H, Yan C, Tang Y, Ma X, Chen Y, Chen S, et al. Endophytic bacterial and fungal microbiota in different cultivars of cassava (Manihot esculenta Crantz). 2020;58:614-23
  96. 96. Zahn G, Amend ASJP. Foliar microbiome transplants confer disease resistance in a critically-endangered plant. 2017;5:e4020
  97. 97. Bahram M, Netherway T, Hildebrand F, Pritsch K, Drenkhan R, Loit K, et al. Plant nutrient-acquisition strategies drive topsoil microbiome structure and function. 2020;227(4):1189-1199
  98. 98. Hussain SS, Mehnaz S, Siddique KH. Harnessing the plant microbiome for improved abiotic stress tolerance. Plant Microbiome: Stress Response: Springer; 2018. p. 21-43
  99. 99. Bhardwaj D, Ansari MW, Sahoo RK, Tuteja NJMcf. Biofertilizers function as key player in sustainable agriculture by improving soil fertility, plant tolerance and crop productivity. 2014;13(1):1-10
  100. 100. Krupinsky JM, Bailey KL, McMullen MP, Gossen BD, Turkington TKJAj. Managing plant disease risk in diversified cropping systems. 2002;94(2):198-209

Written By

Andri Frediansyah

Submitted: 30 March 2021 Reviewed: 21 April 2021 Published: 08 May 2021