*2.2.5 High sensitivity C-reactive protein*

Hs-CRP is a marker of inflammation and endothelial dysfunction and subsequent atherosclerosis. It is produced by hepatocytes in response to circulating cytokines, particularly IL-6.18. It is also a robust downstream marker of inflammation, although unlikely to have a causative role in CVD. Consequently, the relationship between elevated hs-CRP and ASCVD risk remains a matter of controversy. The merit of hs-CRP use is because it does require neither sophisticated equipment nor particular operator skills, especially in developing countries. The hs-CRP, which is incorporated in the Reynolds score, may provide supplemental predictive capacity compared with the FRS [38]. Moreover, the 2013 ACC/AHA guidelines on the assessment of CV risk recommend hs-PCR in men (>50 y) and in women (>60 y) at intermediate risk, which are qualified for lipid lowering drugs [39]. In this regard, many studies reported a robust association of hs-CRP with numerous traditional risk factors for CHD such as obesity, diabetes, physical inactivity, smoking, and alcohol use [40–42]. Other studies highlighted the modest relationship between hs-CRP and CVD, because of its variability among age, gender (higher magnitude in men), and ethnicity (higher magnitude in African Americans vs. Caucasians) [43, 44]. A study comprised of aircrew from both African and Caucasian origin reported a net reclassified global ASCVD risk based on 2018 ESC/ESH guidelines chiefly in intermediate risk hypertensive individuals [40].

## *2.2.6 Coronary artery calcium*

Coronary artery calcium (CAC) a powerful novel risk indicator for ASCVD risk. It is linked with an enhanced risk to develop harmful cardiovascular events independently of clinical markers and inflammatory biomarkers [45]. Conversely, a calcium artery score of 0 has a strong negative predictive value for the development of coronary artery diseases (CAD).


**2. Nutritional composition of banana fruit**

*Banana Nutrition - Function and Processing Kinetics*

fourth leading agricultural crop [3]. Banana is said to be among human foods which was introduced in the first century. The fruit is cultivated in more than 130 countries throughout tropical and subtropical regions with over a harvested area of approximately 10 million hectares [4]. Furthermore, countries in Latin America such as Ecuador and Columbia have been reported to be major producers of the fruit, while the United States and European Union import the highest amounts of

*The diversity of banana and plantains with various genome compositions [2].*

Plantains when compared with unripe dessert bananas differ in terms of plantains being larger in size, possessing more finger body mass and also having higher starch content [5]. Plantains are economically important and serve as a major staple food [6] in some countries such as India and other countries of Latin America and African origin [3]. Plantains are considered as a very important source of energy and starch [7] and are described as sweet acid starchy bananas majorly consumed upon frying or boiling [3]. Similarly, dessert banana serves as a source of energy for athletes due to its potential benefits for sports application [1]. Hence, in some countries, the fruit is used in the production of a variety of energy drinks as well as dried banana bars for athletes. In addition, the fruit also prevents athletes from muscular contractions as it contains significant amount of vitamins and minerals [8]. The works of Doymaz [9] and Pareek [10] showed that banana and plantain contains low amount of protein and substantial amounts of carbohydrates (hemicellulose, starch and pectin), vitamins A and C, potassium, calcium, sodium and magnesium. Dessert and cooking banana plant parts: roots, leaves, flowers, stem and pseudostems have long being used in traditional and indigenous medicine due to their therapeutic properties in various countries of the world such as Africa, America, Asia and Oceania [11]. These beneficial plant parts have been employed in the treatment of various ailments such as snakebite, inflammation, intestinal colitis, dysentery and diarrhoea [8]. Presently, several authors have investigated the potential of banana in mitigating type I and II diabetes mellitus [9, 12], its role in the inhibition of carbohydrate-digesting enzymes (α-glucosidase and α-amylase), glucose absorption [13] and its antioxidant activity [14]. Compared with plantain, most available reports are on changes in chemical composition of dessert banana cultivars during ripening [5, 15–17]. Plantains are rich in nutrients and their biochemical composition varies with growth stage and maturity [5]. Overall, pulp and peel of both cooking and dessert banana can serve as natural sources of amine

compounds, antioxidants, carotenoids and polyphenols [11].

Production of banana can be limited by biotic and abiotic stress factors. Thus, improving the nutritional quality, ability of the fruit to adapt to different geographical conditions and production of new disease resistant varieties using genetic engineering are very important [18]. The science behind genetic modification of bananas therefore aims at increasing productivity and nutritional value and this could be one of the sustainable strategies to address food insecurity in the near future [19].

**28**

banana [4].

**Figure 1.**

Banana and plantain consist of a high nutritional value (**Table 1**) which contributes to an improved absorption of numerous nutrients with minimal fat absorption [18]. Bananas are effective in maintaining plasma glucose and possibly improving endurance exercise performance [20]. Banana fruit is a rich source of phytochemicals, including unsaturated fatty acids and sterols. In the works of Wall [21], composition of 'Dwarf Brazil' banana was reported to be 12.7 mg/100 g vitamin C, 12.4 mg/100 g retinol activity equivalent (RAE) vitamin A, 17.9% total soluble solids (TSS) and a moisture content of 68.5%. Wall [21] further reported concentrations of 4.5 mg/100 g vitamin C, 8.2 mg RAE/100 g vitamin A, 20.5% TSS and moisture content of 73.8% for 'Williams' banana cultivar with the author also showing that cultivars of banana have different nutrient concentrations. An average-sized banana was found to contain 450–467 mg of potassium (K) [22]. Banana is rich in fibre with a medium-sized banana containing about 6 g of fibre. Dessert and cooking banana have been implicated to contain vitamin B, C, macro and micro essential minerals, α- and β-carotene as well as higher concentrations of lutein than provitamin A pigments [20] and all in varying concentrations. As stated in the works of Pareek [10], it was reported in Hawaii that 'Apple' bananas

#### **Table 1.**

*Musa cultivars by genomic classification.*

recorded a concentration of 12.7 mg/100 g FW for vitamin C that was almost threefold than 'Williams' (4.5 mg/100 g); a β-carotene concentration of 96.9 μg α-carotene/100 g and 104.9 μg α-carotene/100 g, while 'Williams' averaged 55.7 μg β-carotene/100 g and 84.0 μg α-carotene/100 g. 'Apple' bananas were also reported to have more phosphorus (P), calcium (Ca), magnesium (Mg), manganese (Mn) and zinc (Zn) than 'Williams' [10]. Similar data for fully ripe banana fruit (**Table 2**) were reported by the United States Department of Agriculture [23]. Other nutrients implicated to be present in cultivars of *Musa* spp. includes biogenic amines and polyphenols.

#### **2.1 Carbohydrates**

Banana and plantain are known to contain sugars, starch, fibre and cellulose compounds especially in its pulp. The peel portion of banana and plantain are rich in fibre. In banana fruit, inherent starch accumulates during development, with minimal changes in the principal carbohydrate metabolites observed during the preclimacteric phase [24]. Subsequently, the fruit starch is converted to sucrose, glucose and fructose as senescence sets in and progresses. Ripening in banana generally involves a decrease in starch concentration from 15 to 25% to less than 5% in the ripened pulp, together with an additional increase in sugar content [25, 26]. At the onset of senescence, sucrose is the predominant sugar, with glucose and fructose predominating as ageing sets in [27]. The concentration of sugars in banana and plantain is associated with respiratory climacteric stage [1]. Starch conversion to sucrose is catalysed by activity of sucrose phosphate synthase, while acid hydrolysis causes starch conversion to non-reducing sugars from sucrose. It was observed that harvest maturity largely affects the conversion of starch to sugar. Changes like these have been reported in both diploid (*Musa* AA) [28] and triploid (*Musa* AAA) banana fruits [29]. Similarly, during the ripening stage of dessert banana, starch is completely broken down, unlike for plantains where starch is not totally broken down [30]. Due to the presence of pectin in banana, it was reported that consumption of the fruit can mitigate intestinal diseases [1]. Furthermore, green banana produces antidiarrheal activity in children which will help to fight against the incidence of diarrhoea, one of the main causes of high mortality and morbidity in children of third world countries. Research further revealed that low fasting blood glucose and glycogenesis in the liver can be increased due to presence of fibres in banana fruit [1]. Dessert and cooking banana in their ripe state are reported to be rich in resistant starch (RS), while at their unripe state, the fruit contains mostly digestible starch [31].

#### **2.2 Protein and Amino Acids**

In the works of John and Marchal [32], whole nitrogen in 'Cavendish' pulp has been reported to be 210 mg/100 g (FW) and 750 mg/100 g (DW). The protein signified a total nitrogen content of about 60–65%. This is in agreement with what was reported by the USDA [23], wherein the protein content for *M. acuminata* was 1.09 g/100 g (FW). John and Marchal [32] found an increased protein value of 4–7 g/100 g (DW) and 1.3–1.8 g/100 g (FW) upon development of 'Cavendish' banana, and also for 'Dwarf Cavendish' from 4 to 8 g/100 g (FW), with the concentration increasing as ripening progresses. Unripe bananas are rich in proteins, with chitinase enzymes being the most abundant protein [32]. During ripening of bananas, starch phosphorylase, malate dehydrogenase and pectate lyase are accumulated. Dopamine, a water-soluble antioxidant reported in both pulp and peel of 'Cavendish' banana is one of the catecholamines that suppress the oxygen

**31**

*Source: [23].*

**Table 2.**

cardiovascular disease risk.

 Similarly, various bioactive amines including putrescine, spermidine and serotonin are reported to be present in high concentrations in banana. In addition, bananas have been found to contain physiologically relevant amounts of biogenic amines, nitrogenous compounds that include serotonin, dopamine and norepinephrine that vary relative to the ripening cycle, as well as the cultivar-dependent phytosterols cycloeucalenone, cycloeucalenone, cycloeucalenol, cycloartenol, stigmasterol, campesterol and β-sitosterol [33]. Bananas have some potential health benefits for cancer, cholesterol metabolism and related markers of

*Nutritional and biochemical composition of Musa acuminata Colla per 100 g.*

*DOI: http://dx.doi.org/10.5772/intechopen.83369*

Calcium (mg) 5.00 Iron (mg) 0.26 Magnesium (mg) 27.00 Phosphorus (mg) 22.00 Potassium (mg) 358 Sodium (mg) 1.00 Zinc (mg) 0.15 Vitamin C, total ascorbic acid (mg) 8.70 Thiamine (mg) 0.031 Riboflavin (mg) 0.07 Niacin (mg) 0.67 Vitamin B-6 (mg) 0.37 Folate, DFE (μg) 20.00 Vitamin B-12 (μg) 0.00 Vitamin A, RAE (μg) 3.00 Vitamin A (IU) 64.00 Vitamin E (α-tocopherol) (mg) 0.10 Vitamin D (D2 + D3) (μg) 0.00 Vitamin D (IU) 0.00 Vitamin K (phylloquinone) (μg) 0.50 Fatty acids, total saturated (g) 0.11 Fatty acids, total monounsaturated (g) 0.03 Fatty acids, total polyunsaturated (g) 0.07

*Banana Nutrition - Function and Processing Kinetics*

polyphenols.

**2.1 Carbohydrates**

digestible starch [31].

**2.2 Protein and Amino Acids**

recorded a concentration of 12.7 mg/100 g FW for vitamin C that was almost threefold than 'Williams' (4.5 mg/100 g); a β-carotene concentration of 96.9 μg α-carotene/100 g and 104.9 μg α-carotene/100 g, while 'Williams' averaged 55.7 μg β-carotene/100 g and 84.0 μg α-carotene/100 g. 'Apple' bananas were also reported to have more phosphorus (P), calcium (Ca), magnesium (Mg), manganese (Mn) and zinc (Zn) than 'Williams' [10]. Similar data for fully ripe banana fruit (**Table 2**) were reported by the United States Department of Agriculture [23]. Other nutrients implicated to be present in cultivars of *Musa* spp. includes biogenic amines and

Banana and plantain are known to contain sugars, starch, fibre and cellulose compounds especially in its pulp. The peel portion of banana and plantain are rich in fibre. In banana fruit, inherent starch accumulates during development, with minimal changes in the principal carbohydrate metabolites observed during the preclimacteric phase [24]. Subsequently, the fruit starch is converted to sucrose, glucose and fructose as senescence sets in and progresses. Ripening in banana generally involves a decrease in starch concentration from 15 to 25% to less than 5% in the ripened pulp, together with an additional increase in sugar content [25, 26]. At the onset of senescence, sucrose is the predominant sugar, with glucose and fructose predominating as ageing sets in [27]. The concentration of sugars in banana and plantain is associated with respiratory climacteric stage [1]. Starch conversion to sucrose is catalysed by activity of sucrose phosphate synthase, while acid hydrolysis causes starch conversion to non-reducing sugars from sucrose. It was observed that harvest maturity largely affects the conversion of starch to sugar. Changes like these have been reported in both diploid (*Musa* AA) [28] and triploid (*Musa* AAA) banana fruits [29]. Similarly, during the ripening stage of dessert banana, starch is completely broken down, unlike for plantains where starch is not totally broken down [30]. Due to the presence of pectin in banana, it was reported that consumption of the fruit can mitigate intestinal diseases [1]. Furthermore, green banana produces antidiarrheal activity in children which will help to fight against the incidence of diarrhoea, one of the main causes of high mortality and morbidity in children of third world countries. Research further revealed that low fasting blood glucose and glycogenesis in the liver can be increased due to presence of fibres in banana fruit [1]. Dessert and cooking banana in their ripe state are reported to be rich in resistant starch (RS), while at their unripe state, the fruit contains mostly

In the works of John and Marchal [32], whole nitrogen in 'Cavendish' pulp has been reported to be 210 mg/100 g (FW) and 750 mg/100 g (DW). The protein signified a total nitrogen content of about 60–65%. This is in agreement with what was reported by the USDA [23], wherein the protein content for *M. acuminata* was 1.09 g/100 g (FW). John and Marchal [32] found an increased protein value of 4–7 g/100 g (DW) and 1.3–1.8 g/100 g (FW) upon development of 'Cavendish' banana, and also for 'Dwarf Cavendish' from 4 to 8 g/100 g (FW), with the concentration increasing as ripening progresses. Unripe bananas are rich in proteins, with chitinase enzymes being the most abundant protein [32]. During ripening of bananas, starch phosphorylase, malate dehydrogenase and pectate lyase are accumulated. Dopamine, a water-soluble antioxidant reported in both pulp and peel of 'Cavendish' banana is one of the catecholamines that suppress the oxygen

**30**

## **Table 2.**

*Source: [23].*

*Nutritional and biochemical composition of Musa acuminata Colla per 100 g.*

uptake of linoleic acid [33]. Similarly, various bioactive amines including putrescine, spermidine and serotonin are reported to be present in high concentrations in banana. In addition, bananas have been found to contain physiologically relevant amounts of biogenic amines, nitrogenous compounds that include serotonin, dopamine and norepinephrine that vary relative to the ripening cycle, as well as the cultivar-dependent phytosterols cycloeucalenone, cycloeucalenone, cycloeucalenol, cycloartenol, stigmasterol, campesterol and β-sitosterol [33]. Bananas have some potential health benefits for cancer, cholesterol metabolism and related markers of cardiovascular disease risk.

#### **2.3 Vitamins**

Dessert and cooking banana contain different forms of vitamins in varying concentrations among the known cultivars worldwide. According to the reports of USDA [23] and Wills et al. [34], the vitamin C levels for 'Cavendish' banana estimated using high-performance liquid chromatography (HPLC), ranged from 2.1 to 18.7 mg/100 g (DW/FW), which however, varies considerably among different cultivars. The average vitamin C (**Table 2**) content for 'Dwarf Brazilian' (*Musa* AAB 'Santa Catarina Prata') was found to be 12.7 mg/100 g and 4.5 mg/100 g for 'Williams' [13]. These results agree with the report of Wenkam [35], who reported vitamin C values of 5.1 mg/100 g (DW/FW?) for 'Williams' and 14.6 mg/100 g (DW/FW?) for 'Dwarf Brazilian' banana cultivar.

Dessert banana contains substantial levels of provitamin A carotenoids (PVAC), but few cultivars with orange- or yellow-coloured pulp are known to have higher concentration of carotenoids [15]. Vitamin A deficiency has been reported to be a public health concern identified in almost 118 countries in the world, with highest prevalence in Asia and Africa, as their diets are mainly cereals and tubers [1]. Researchers from Australia (Queensland University of Technology) have concocted Cavendish banana with high amounts of β-carotene, a precursor of vitamin A. The carotenoids mostly found in fully developed bananas are lutein, α- and β-carotene. The fruit pulp is also rich in carotenoids, while the peel contains low amounts [36]. It is reported that during ripening the amount of carotenoids increase [20, 34]. Similar observation was reported by Kanazawa and Sakakibara [37], which contradicts the report of Gross and Flugel [38] who found carotenoid content decreasing during initial stage of ripening. As can thus be seen, different cultivars of *Musa* spp. contain different amounts of carotenoids. Banana and plantain fruits with orange flesh are rich in VAC [38, 39]. One variety of banana, 'Karat' of Micronesia, was reported to accumulate β-carotene of about 2230 mg/100 g [39].

### **2.4 Minerals**

Banana and plantain are very rich in K, an essential element for maintaining human blood pressure and for proper functioning of the heart [40]. The fruit is also rich in Mg, Fe, Cu and Mn [20]. In the works of Pareek [10], the average K content for Hawaii's bananas ('Dwarf Brazilian' and 'Williams') were reported to be 330.6 mg/100 g (FW). Similarly, it was reported that fruits cultivated in Tenerife, were observed to contain a K content of 5.09 mg/g (FW), P content of 0.59 mg/g (FW), Ca content of 0.38 mg/g (FW) and Mg content of 0.38 mg/g (FW) [10, 41], though it was reported by the authors that the area of origin had a major effect on the occurrence of the minerals. Varietal differences had no effect on concentration of minerals present except for Fe. In the works of Forster et al. [42], differences were observed in the mineral content of bananas grown in both Ecuador and Tenerife. High Na, K, Mg and Fe contents were found for bananas grown in Tenerife, while high Ca, Cu, Zn and Mn contents were reported for bananas grown in Ecuador. This difference was attributed to agricultural practices, geographical location and soil composition [42]. Mineral composition of banana samples according to degree of ripeness was reported for the fruits obtained from Nigeria: 73.47% ash, 0.68% Zn, 0.146% Mn for unripe samples; 77.19% ash, 0.80% Zn, 0.271% Mn for ripe samples and 79.22% ash, 0.78% Zn for overripe samples [43]. Similarly, the peel of banana cultivars obtained from Cameroon contained relatively high minerals: K (50.0 mg/g DW), P (22.2 mg/g DW), Mg (11 mg/g DW) and Ca (18 mg/g DW) [44]. Generally, bananas contain low amounts of Ca, however, Micronesian cv. 'Krat' is relatively high in Ca [39].

**33**

*Banana Bioactives: Absorption, Utilisation and Health Benefits*

ability to damage macromolecules and nucleic chains.

Phenolic compounds have been implicated to be present in banana fruits. Although, banana peels contain more tannin compared with its pulp, tannins in the fruit confer an unpleasant astringent taste on the fruit. The astringency in ripe fruit is reduced, which is associated with a change in the structure of the tannins, rather than a reduction in their levels, as they form polymers [28]. When banana fruit is cut, oxidative browning occurs due to the presence of polyphenols. Report of different studies has shown that banana peels of different cultivars contain varying concentrations of total phenolic compounds (TPC). In the works of Nguyen et al. [54], it was reported that total phenolics, flavonoids and antioxidant activity of banana pulp and peel flours, Cv. 'Kulai Hom Thong' was shown to contain 3.0 mg of gallic acid equivalent (GAE)/gFW, while 'Kulai Khai' was reported to contain 0.9 mg of (GAE)/ gFW. Similarly, banana cv. 'Pisangmas' from Malaysia was reported to contain TPC ranging from 0.24 to 0.72 mg GAE/g FW, depending on the extraction method [32]. Sulaiman et al. [52], also reported significant differences in the antioxidant activity, total phenolic and mineral contents of eight Malaysian banana cultivars. Flavonoids epicatechin and myricetin 3-O-rhamnosyl-glucoside were identified in flour of organic acid pretreated "Mabonde", "Luvhele" and "M-red" cultivars at different concentrations [55]. Authors Bennett et al. [56] and Borges et al. [57] also reported the presence of catechin and gallic acid in pulp and peel of ripe and unripe banana cultivars. Similarly, plantain a banana cultivar belonging to the AAB, ABB or BBB group [58] have also been reported to contain high concentration of hydroxycinnamic acids (ferulic acid–hexoside with 4.4–85.1 μg/g DW) in its pulp [32]. Plantain peels are rich in flavonol glycosides and rutin ranging from 242.2 to 618.7 μg/g DW.

Phytochemicals have been reported to be an immense source of anticancer medications and chemopreventive agents [45]. These plant chemicals exert some of their actions through interactions with essential enzymes that regulate the activities in genes. Banana contains various bioactive compounds such as phenolics, carotenoids, alkaloids, glycosides, phlobatannins, tannins, terpenoids, saponins, steroids, biogenic amines and phytosterols, which are highly desirable in diet as they exert health beneficial effects [11, 32, 46]. These composites are helpful in protecting the body against oxidative stress due to their antioxidative activities [47], controlling gene expression in cell proliferation and apoptosis and important in controlling blood pressure [48]. The incorporation of banana pulp and peel in various food products could add value since they have health benefits [47]. Thus, banana pulp and peel can be used as natural sources of antioxidants and provitamin A. Banana peel is reported to have higher antioxidant capacity than banana pulp [49–53]. Furthermore, phenolic content of banana peel was higher compared to other fruits such as avocado, pineapple, papaya, passion fruit, water melon and melon [50]. However, it is recommended that to effectively recover and utilise phenolic compounds from banana peels, it is important to evaluate its chemical profile, factors affecting the levels of phenolic compounds in the peels such as antinutrients, and potential use of these compounds as food ingredients or nutraceuticals. It is important to understand how these bioactive compounds found in fruits and vegetables limit or prevent oxidative stresses as a free-radical scavengers or metalchelating agents. In the report of Liu [53], it was emphasised that there has to be a balance between oxidants and antioxidants for normal functioning of the body cell and/or sustaining optimal physical condition in the human body. Too much oxidants in the human body result in damage to the biomolecules such as proteins, lipids carbohydrates and DNA. Hence, to understand the mechanism of action of antioxidant, it is imperative to understand the formation of free radicals and their

*DOI: http://dx.doi.org/10.5772/intechopen.83369*

**3. Banana phytochemicals and bioactives**


Redox in Electrochemistry

*Redox*

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10.1007/BF00718923

**48**

**Chapter 4**

**Abstract**

potential.

**51**

**1. Introduction**

Redox Potentials as Reactivity

*José H. Zagal, Ingrid Ponce and Ruben Oñate*

**Keywords:** redox potential, reactivity descriptors, redox catalysis, chemical catalysis, linear free-energy correlations, volcano correlations

Predicting the rate of chemical processes on the basis of thermodynamic information is of fundamental importance in all areas of chemistry including biochemistry, coordination chemistry and especially electrochemistry [1]. Correlations do exist between the Gibbs free-energy for one series of reactions and logarithm of the reaction rate constant for a related series of reactions. These relations are known as linear free-energy relationships (LFER) [1]. For example, the Brønsted catalysis equation describes the relationship between the ionization constant of a series of catalysts and the reaction rate constant for a reaction on which the catalyst operates. The Hammett equation predicts the equilibrium constant or reaction rate constant of a reaction from a substituent constant and a reaction type constant. The Edwards equation relates the nucleophilic power to polarizability and basicity. The Marcus equation is an example of a quadratic free-energy relationship (QFER) that applies to electron transfer (ET) reactions where the activation energy is given by the inner and outer reorganizational energies. In the case of electrochemical reactions, the

Descriptors in Electrochemistry

A redox catalyst can be present in the solution phase or immobilized on the electrode surface. When the catalyst is present in the solution phase the process can proceed via inner- (with bond formation, chemical catalysis) or outer-sphere mechanisms (without bond formation, redox catalysis). For the latter, log *k* is linearly proportional to the redox potential of the catalysts, *E*°. In contrast, for inner-sphere catalyst, the values of *k* are much higher than those predicted by the redox potential of the catalyst. The behaviour of these catalysts when they are confined on the electrode surface is completely different. They all seem to work as inner-sphere catalysts where a crucial step is the formation of a bond between the active site and the target molecule. Plots of (log *i*)*E* versus *E*° give linear or volcano correlations. What is interesting in these volcano correlations is that the falling region corresponding to strong adsorption of intermediates to the active sites is not necessarily attributed to a gradual surface occupation of active sites by intermediates (Langmuir isotherm) but rather to a gradual decrease in the amount of M(II) active sites which are transformed into M(III)OH inactive sites due to the applied


**6.2. Chronic antibody mediated rejection**

Chronic AMR is now included in the newest update of the Banff 07 classification of renal allograft pathology with the following criteria: [1]morphological changes as glomerular double contours compatible with transplant glomerulopathy (TPG) and severe PTC basement membrane multilayering, interstitial fibrosis and tubular atrophy with or without PTC loss, and fibrous intimal thickening in arteries without internal elastica duplication; [2] diffuse C4d deposition in PTCs; and [3] presence of DSA (Solez et al.,2008). Not all these criteria are always fulfilled in an individual patient at every given time point (Fehr et al., 2009).

PTC basement membrane multilayering correlates highly with TPG, and most of TPG have evidence of either C4d-positive staining or DSA. However, the proposed criteria do not apply to all situations of chronic active antibody-mediated rejection. Chronic AMR is distinct from acute AMR in that no acute inflammation (neutrophils, edema, necrosis, thrombosis) is present. However, cellular activity is often reflected by increased mononu‐ clear cells in glomerular capillaries and PTC (Colvin, 2007). The Banff criteria require PTC C4d positivity for diagnosis of ABMR as well as microcirculation injury. However, C4d is not a sensitive marker of chronic ABMR, and in many patients with transplant glomerulopathy, C4d staining is negative in the presence of anti-HLA DSA. Therefore, the recent update of the Banff classification introduced the diagnostic category of "suspi‐ cious for ABMR." It is defined with the presence of morphologic evidence of antibodymediated tissue injury and positive anti-HLA antibody with negative C4d, or PTC C4d positivity in the absence of alloantibody (Solez et al., 2008).


**Author details**

Lisha O'Sullivan\* and Emer Ring Mary Immaculate College, Limerick, Ireland

\*Address all correspondence to<EMAIL_ADDRESS>
© 2023 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


**6. Lipidomics**

Lipidomic measurement is a sub‐branch of metabolomics where the identification of lipid classes and species is made. Given obesity is a disease whereby lipids accumulate in adipose tissue to make large adipose tissue depots, lipidomics is an extremely relevant platform for the field. Typically, analysis can identify not only the different classes of lipid that are in a given sample, but also the molecular species that make up those different classes. Multiple approaches to performing lipidomics are available. Shotgun lipidomics refers to the process of identifying the lipidome of biological lipid extracts directly without the need for chromatographic purification. Targeted lipidomics involves the combination of liquid chromatography and stable isotope or non‐physiological internal standards to provide quantification to hundreds of lipids. While untargeted lipidomics refers to the combination of liquid chromatography with high mass analysis to detect lipid species [39]. Numerous studies have investigated the lipidomic signature that is associated with increased fat mass in animal and human models.

#### **6.1. Insights into human obesity from plasma lipidomics**

Variants in the fat mass and obesity‐associated gene FTO has been identified as a risk factor for the accumulation of fat mass and the development of obesity [8, 34]. By correlating metabolites after stratification for whether or not an individual is a carrier of the FTO risk allele, genetic FTO‐induced changes in the metabolome can be assessed. Via utilising samples obtained as part of a Korean community‐based cohort (KARE cohort), Kim et al. [35] used serum metabolite quantification by targeted metabolomics to correlate FTO‐genotype with alterations to metabolites. This resulted in the analysis of 134 different metabolites (78 glycerophospholipids, 21 amino acids, 12 sphingolipids, 12 acylcarnitines, 10 biogenic amines and 1 hexose). Of these metabolites, the authors found that seven metabolites were associated with increased risk of obesity due to the presence of the rs9939609 FTO risk allele [35]. Most notably, of these seven metabolites, five were phosphatidylcholines (PCs) (C36:5, C36:6, C38:5, C38:5, C38:6 and C40:6) and these showed the strongest effect, while the monosaccharide (hexose) and amino acid (valine) were also associated. Similar future studies investigating the impact of genetic risk factors on the metabolome can provide insight into how genes

Using mouse models that have had a genetic manipulation (knock‐out, knock‐down overexpression), metabolomics can be used to gain an idea as to the impact a genetic modification has on obesity or metabolic pathways. Neuroblast differentiation‐associated protein AHNAK knock‐out mice (AHNAK(‐/‐)) have been reported as having a phenotype whereby they have a strong resistance to high‐fat diet‐induced obesity. Consequently, Kim et al. [36] applied (1) H NMR‐based metabolomics to compare the altered metabolites in the urine from high‐ fat diet (HFD) fed wild‐type and AHNAK(‐/‐) mice. The profiling identified that the urinary metabolites of HFD‐fed AHNAK(‐/‐) mice gave higher levels of methionine, putrescine, tartrate, urocanate, sucrose, glucose, threonine and 3‐hydroxyisovalerate compared to wild‐type mice suggesting that the resistance to the HFD‐induced obesity may arise from alterations in amino acids [36]. Likewise, human ataxin‐2 (ATXN2) knock‐out mice display obesity, insulin resistance and dyslipidemia [37]. To understand the effects of the loss of ATXN2, Meierhofer and team used unbiased profiling approaches to quantify the global metabolome of ATXN2 knock‐out mice with label‐free mass spectrometry [38]. Significant down‐regulated pathways for branched chain and other amino acid metabolism, fatty acids and citric acid cycle provided evidence for the biological function of ATXN2 and the potential mechanism via which the lean phenotype is maintained [38]. Thus, metabolomics used in combination with genetic models offers a viable way to determine biological significance of genes and improve under-

Lipidomic measurement is a sub‐branch of metabolomics where the identification of lipid classes and species is made. Given obesity is a disease whereby lipids accumulate in adipose tissue to make large adipose tissue depots, lipidomics is an extremely relevant platform for

impact metabolism and contribute to the development of obesity.

**5.2. Metabolomic and obesity in animal models**

34 Adiposity - Omics and Molecular Understanding

standing of cellular pathways.

**6. Lipidomics**

Plasma lipidomic screening has been used to characterise the circulating lipids in obese compared to lean individuals to gain an insight into how obesity alters this parameter. In a study of monozygotic twins who differed in body weight by 10–25 kg, characterisation of lipid species in serum samples identified that obesity, independent of genetic influences, was associated with increases in lysophosphatidylcholine (LPC) lipids and decreases in ether phospholipids [40]. In an alternative study looking for plasma lipidomic associations with waist circumference used as a marker of central obesity, it was noted that dihydroceramides were associated with waist circumference, particularly the species 18:0, 20:0, 22:0 and 24:1, while two sphingomyelin species 31:1 and 41:1 were inversely associated with waist circumference [41]. In a study of 1,176 young individuals (20 years of age) in which 175 different plasma lipid metabolites were analysed, a positive association was found between waist circumference and seven sphingomyelins and five diacylphosphatidylcholines and negative association with two LPCs [42] while another study also demonstrated a reduction in numerous LPC species in the plasma of obese individuals [43]. Differences observed between studies could be due to the type of obesity in the different cohorts sampled. For example, obesity due to a high caloric intake could potentially result in a different lipidomic profile than what is observed in individuals who are obese due to a sedentary lifestyle. Other factors such as diet, sample preparation and age could also have an effect.

One potential use of plasma lipidomics is to use it as a diagnostic tool or monitoring tool in obese patients. By measuring the plasma lipidomic signature and correlating levels of various lipid species to risk factors of further disease such as region‐specific adiposity or liver dysfunction, a panel of lipids may be identified to stratify at‐risk patients [44]. A serum biomarker that predicts ectopic fat levels could be utilised in the clinic to track ectopic fat levels or conversely to track the effectiveness of interventions to decrease it. Currently, it is necessary to use expensive large‐scale imaging technology to investigate ectopic lipid deposition. Even so, this only detects levels of triacylglycerols (TAGs) rather than other lipid metabolites that are found in lower abundance that have been implicated in causing metabolic dysfunction such as ceramides and diacylglycerols (DAGs). Alternatively, invasive biopsy procedures with analytical analysis can be used to identify the relative expression of these lipids. Given the relative ease of blood collection, plasma lipid profiling may provide an alternative avenue to provide a picture of tissue lipid levels if a predictor(s) can be identified.

In one study using shotgun lipidomics that captured 252 individual lipid species over 14 different classes, the authors aimed to link the circulating levels of blood plasma lipids to fat accumulated in various parts of the body including visceral adiposity and epicardial adipose tissue (EAT) (which are both cardiac disease risk factors) [44]. Via modelling analysis, a strong association was identified between visceral adiposity and plasma diacylglycerol (DAG) and EAT and triacylglycerol (TAG) (both DAG and TAG are composed of saturated fatty acids) [44]. In this study, EAT is also correlated with increased levels of phosphatidylglycerol (PG) species including PG 20:3/20:3 and PG 22:5/18:1 and with decreased levels of ether phosphatidylethanolamine (PE‐O) lipid species that are mainly composed of plasmalogens [44]. Additionally, Perreault and colleagues set out to determine the ability of lipidomics performed in the serum to predict ectopic lipid accumulation in skeletal muscle, in particular, the ability to predict TAG, DAG and ceramide. After analysis of 215 serum lipids, they found that in obese individuals, ganglioside C22:0 and lactosylceramide C14:0 levels in the serum predicted muscle TAG levels while serum DAG C36:1 and free fatty acid (FFA) C18:4 could predict muscle TAG levels. Furthermore, serum TAG C58:5, cholesterol ester C24:1, phosphatidylcholine C38:1 and FFA C14:2 were good predictors of the ceramide levels in muscle. Moving forward, confirmation of such findings could allow for a panel of plasma lipids to accurately depict the state of ectopic lipid deposition in peripheral tissues such as skeletal muscle and prove useful in the clinical setting [45].

#### **6.2. Tissue lipidomics in human obesity**

While plasma is an obvious location to identify a prognostic marker, studying the lipidomic profile in adipose tissue itself or in other metabolic organs is of great interest to understand the biology of the condition. In a study of 20 obese, but otherwise healthy women, lipidomics was carried out on subcutaneous adipose tissue samples. Participants were divided into those with high content of liver fat or those with a low content of liver fat to determine if adipose tissue is altered in those discordant for intrahepatic lipid content. Analysis of 154 lipid species revealed increased concentrations of TAGs particularly long chain, and ceramides, specifically Cer (d18:1/24:1) in the group with more liver fat [46]. In another study carried out in obese insulin‐resistant women compared to obese women with normal insulin levels, lipid profiling revealed an increase in GM3 ganglioside and phosphatidylethanolamine (PE) lipid species in omental adipose tissue [47]. These findings corresponded to an increase in ST3GAL5, the synthesis enzyme for GM3 ganglioside, and a decrease in phosphatidylethanolamine methyl transferase (PEMT), the degradation enzyme of PEs [47]. Thus, these changes may contribute to the obesity‐induced insulin‐resistant state.

In a human lipidomics screening of plasma and skeletal muscle samples comparing lean individuals with those who were obese or overweight but insulin sensitive (as defined by glucose infusion rate during a hyperinsulinemic‐euglycemic clamp) and those who were obese and overweight but insulin resistant, demonstrated that there was no defining difference in the skeletal muscle of those who were lean as compared to those that were overweight or obese [48]. The plasma samples did demonstrate a higher quantity of TAG and lower plasmalogen species in those who were overweight or obese compared to lean. However, in individuals who were overweight or had obesity but were discordant for insulin resistance those who were insulin‐resistant had higher levels of C18:0 sphingolipids in skeletal muscle and higher levels of DAG and cholesterol ester (CE) and a decrease in LPC and lysoalklphosphatidycholine in the plasma [48]. This suggested that insulin resistance has a greater impact within the obese setting on the lipidomic profile than what obesity has on the profile in comparison to those that are lean.


**3. Pathogenesis**

As fungal pathogens have an enormous impact on plant production worldwide, the strategies they use to infect plants and to cause disease are a topic of great interest (Van De Wouw & Howlett, 2011). Knowledge of the pathogenicity/virulence factors essential for fungal infections is very important because it represent the targets that researches must attack in the fight against these pathogens (Fernandez-Acero *et al.,* 2011).

We define pathogenicity gene as those necessary for disease development but not essential for pathogen to complete its lifecycle *in vitro.* Pathogenicity genes are of interest not only to increase our overall knowledge of disease process, but also because any such gene could became a target for disease control.

The types of genes essential for pathogenesis depend on the infection process of a particular fungus. Some fungi degrade the cuticle and cell wall to enter the plant; others form specialized structures, such as appressoria, to penetrate the epidermis, while others enter the host through wounds or natural openings (Idnurm & Howlett, 2001). Once the fungus has colonized plant, it may grow obtaining nutrients from its host without killing cells (as a biotroph); some fungi produce specialized infection structures (e.g. haustoria) during biotrophic stage. Other fungi species act killing host cells with the use of toxins (as necrotrophs) or act as hemibiotroph (biotroph and necrotroph at different stages if infection). Toxins often are major components of the arsenal or virulence determinants by necrotrophic fungi. They can be host specific or non host specific, and they kill or disable functions of host cells (Van De Wouw & Howlett, 2011).

A number of fungal mechanisms and molecules have been shown to contribute to fungal pathogenicity or virulence, understood as the capacity to cause damage in a host, in absolute or relative terms. Among them, cell wall degrading proteins, inhibitory proteins, and

biology to inform chemistry (Xu *et al*., 2007). The accumulation of proteomic information of fungal plant pathogens may be an incentive to the development of new and environmentally friendly fungicides. Particularly, Proteomics is another is a highthroughput technology that allows an in depth study of the sets of proteins synthesized in a specific sample at any specific moment. By protein profile comparison between samples, the proteins involved in specific biological processes may be revealed. One of the most interesting applications of the proteomics is its use in discovering new protein targets for drug design including fungicides (Fernandez-Acero *et al.,* 2010; Ferrer-Alarcon *et al.;* 2009). It

The accumulation of information over the last decades, relating to a) fungal molecular genetic data, b) pathogenicity/virulence factors and c) proteomic approaches, has led to the appearance of several web-accessible databases which contribute to the fungal scientific community's development in this field. More than 50 genomes of pathogenic fungi are published in the Broad Institute Database for public perusal (www.broadinstitute.org/science/projects/fungal-genomeinitiative); and further data in the Phytopathogenic Fungi and Oomycete EST Database, COGEME, http://cogeme.ex.ac.uk/). In spite of the incredible amount of biological information about fungal plant pathogens, there

As fungal pathogens have an enormous impact on plant production worldwide, the strategies they use to infect plants and to cause disease are a topic of great interest (Van De Wouw & Howlett, 2011). Knowledge of the pathogenicity/virulence factors essential for fungal infections is very important because it represent the targets that researches must

We define pathogenicity gene as those necessary for disease development but not essential for pathogen to complete its lifecycle *in vitro.* Pathogenicity genes are of interest not only to increase our overall knowledge of disease process, but also because any such gene could

The types of genes essential for pathogenesis depend on the infection process of a particular fungus. Some fungi degrade the cuticle and cell wall to enter the plant; others form specialized structures, such as appressoria, to penetrate the epidermis, while others enter the host through wounds or natural openings (Idnurm & Howlett, 2001). Once the fungus has colonized plant, it may grow obtaining nutrients from its host without killing cells (as a biotroph); some fungi produce specialized infection structures (e.g. haustoria) during biotrophic stage. Other fungi species act killing host cells with the use of toxins (as necrotrophs) or act as hemibiotroph (biotroph and necrotroph at different stages if infection). Toxins often are major components of the arsenal or virulence determinants by necrotrophic fungi. They can be host specific or non host specific, and they kill or disable

A number of fungal mechanisms and molecules have been shown to contribute to fungal pathogenicity or virulence, understood as the capacity to cause damage in a host, in absolute or relative terms. Among them, cell wall degrading proteins, inhibitory proteins, and

involves the identification and early validation of disease-associated targets.

is no commercial fungicide developed from a molecular approach.

attack in the fight against these pathogens (Fernandez-Acero *et al.,* 2011).

**3. Pathogenesis**

became a target for disease control.

functions of host cells (Van De Wouw & Howlett, 2011).

enzymes involved in the synthesis of toxins are included. These virulence factors are typically involved in evolutionary arms races between plants and pathogens (Gonzalez Fernandez *et al*., 2010).

Knowledge of the pathogenic cycle and virulence factors of the fungus is crucial for designing effective crop protection strategies, including the development of resistant plant genotypes through classical plant breeding or genetic engineering, fungicides or the use of biological control strategies (Gonzalez-Fernandez *et al.,* 2010). The determination of a specific factor as virulence or pathogenicity has been achieved by constructing defective mutants in the specific genes. The infection power of the analyzed mutants should at least decrease or disappear compared to the wild type, if the deflections of these genes in mutants produce a loss of vegetative lesion, it is logical to assume that the inhibition of this enzyme or set of enzymes by targeted strategies, should produce new fungicides. In this context, the use of natural products or related compounds as specific enzymes inhibitors is an archetype, as they would be species specific and the environmental impact would be reduced to a minimum (Fernandez-Acero *et al.,* 2011).

A diversity of fungi, oomycetes secrete proteins and other molecules to different cellular compartments of their hosts to modulate plant defense circuitry and enable parasitic colonization, these molecules have been called "effectors". The usage of the term "effector" became popular in the field of plant-microbe interactions with the discovery that plant pathogenic gram-negative bacteria utilize a specialized machinery to deliver proteins inside host cells. More recently, a broader range of plant microbiologists have adopted the term effector and its associated concepts (Abramovitch et al., 2006). This term is now also routinely used in the fungal and oomycete literature and is becoming increasingly popular in nematology to describe secreted proteins that exert some effect on plant cells (Hogenhout et al., 2009).

Some effectors are avirulence proteins and have a 'gene-for gene' relationship with resistance proteins in the host. When a fungal avirulence gene is mutated, hosts with the corresponding resistance gene no longer detect the pathogen; this leads to a compatible interaction. Host-specific proteinaceous toxins that have an 'inverse' gene-for-gene relationship with the host, whereby the interaction leads to disease such genes would be classified as pathogenicity genes (Oliver & Solomon, 2010). Small proteins encoded by fungal genes involved at various stage of infection, alter host cell structure and function facilitate infection. These proteins are often cysteine rich (hogenhout *et al*., 2009).

Fungi use signaling cascades to respond to changes in the environment by altering their gene expression. The interruption of these signaling genes results in the loss and/ or reduction in pathogenicity, as well as pleiotrophic effects on cellular processes, including mating, conidiation, growth rate and toxin production. Therefore, it is difficult to determine which aspect of fungal physiology is responsible for the loss of pathogenicity. The components of these signal transduction cascades may represent targets for the development of fungicides (Van De Wouw & Howlett, 2011). *Phytophtora infestans,* one of the most destructive pathogen of potato in the history, have a remarkable speed of adaptation to control strategies such as genetically resistant cultivars, comparison with two other *Phytophthora* genomes showed rapid turnover and extensive expansion of specific families of secreted disease effector proteins, including many genes that are induced during infection

Target-Site-Specific Screening System for Antifungal Compounds 187

compounds are structurally based on natural products and interfere with the ubiquinol

There are numerous antifungal compounds that were discovered from diverse microbial sources using traditional activity-based screening techniques. These microbial compounds showed potent control efficacy against various plant diseases, including chronic diseases which are difficult to control with conventional synthetic fungicides. Advances in screening systems directed to specific targets of fungal metabolism have increased the opportunities to discover novel antifungal agents with selectivity over non-target organisms. Microbial metabolites have also been exploited as a source for non-fungicidal disease control agents that do not inhibit vegetative hyphal growth, but rather interfere specifically with the infection process of pathogenic fungi, such as spore germination, the formation of penetration structures and sporulation (Seok & Kook, 2007). Infection structures of phytopathogenic fungi are modified hyphae specialized for the invasion of plant tissue, initial events are adhesion to the cuticule and directed growth of the germ tube on the plant surface (Mendgen *et al.,* 1996). The specificity of microbial fungicides is a highly preferred characteristic in terms of impacting the environment, where it is closely related to the occurrence of fungicide resistance. The most recently developed fungicides from microbial metabolites, the strobilurins, provide a cue for the high risk of resistance development of

These compounds have long been applied to control fungal diseases of rice, vegetables and fruits, and their effectiveness in controlling these diseases has been tested in the field and proven over many years. The importance of microbial fungicides, compared to synthetic compounds, may have been under evaluated in the past due to the limitation in their activity spectrum and in certain instances, the development of resistance (Knight *et al.,* 1997). Nevertheless, the excellent fungicidal activity of these microbial metabolites and their potential as lead candidates for further fungicide development continue to stimulate research and screening for antifungal microbial metabolites, some examples of this

**Kasugamycin** is an amino-sugar compound discovered from the metabolites of *Streptomyces kasugaensis, in vivo* studies have shown that kasugamycin efficiently suppresses the development of *M. grisea* mycelia on rice plants in both preventive and curative treatments, to overcome potential resistance problems, mixtures of kasugamycin with different

**Polyoxins** are peptidylpyrimidine nucleoside antibiotics isolated from the culture broth of *Streptomyces cacaoi* var. *asoensis*, such excellent characteristics come from the fact that polyoxins selectively inhibit the synthesis of cell-wall chitin in sensitive fungi but have no

**Validamycin A** produced by *Streptomyces hygroscopicus* var. *limoneus* has been effective in controlling rice sheath blight caused by *R. solani*. Validamycin A is converted within fungal cells to validoxylamine A, an extremely strong inhibitor of trehalose. The mode of action of validamycin A is favorable for biological selectivity, because vertebrates do not depend on

synthetic fungicides having different modes of action are currently in use.

adverse effects on organisms lacking chitinous cell walls.

the hydrolysis of trehalose (Doumbou *et al.,* 2001).

cytochrome C oxidoreductase (Foster & Thines, 2009).

site-specific fungicides.

compounds are:

stage. These fast-evolving effector genes are localized to highly dynamic and expanded regions of the *P*. *infestans* genome. This probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential (Haas *et al.,* 2009). Other example of pathogen trainer of virulence factors is *Botrytis cinerea* to date have been identified a wide range of compounds and enzymes that uses the fungus to exerts its pathogenicity, thanks to the arsenal of degrading enzymes, *B. cinerea* is able to feed on different plant tissues, this fungus shares conserved virulence factors with other phytopathogens (Choquer *et al.,* 2007). *Botrytis cinerea* is a ascomycete necrothrofic, this fungi alone is responsible for 10% of the global fungicide market (Fernandez-Acero *et al.,* 2011), is thought to enter the host mainly by producing degrading enzymes and causing an oxidative burst, specifically because secretes nonspecific phytotoxins to kill cells from a large spectrum of plants. Among the numerous metabolites isolated from fermentation broths, the most well known is the sesquiterpene botrydial (Deighton *et al.,* 2001). This fungus is notably equipped with multiple cell wall-degrading enzymes that allow plant tissue colonization and the release of carbohydrates for consumption. Pectin, the major host cell wall component, can be degraded by a set of fungal pectinases (Ten Have *et al,* 2001; Choquer *et al,* 2007). Xilanase (Xyn11A) from *Botrytis cinerea* contributes to the infection process with the necrotizing and not with the xylan hydrolyzing activity. The main contribution of the xylanase Xyn11A to the infection process of *B. cinerea* is to induce necrosis of the infected plant tissue. A conserved 30-amino acids region on the enzyme surface, away from the xylanase active site, is responsible for this effect and mediates binding to plant cells (Noda *et al,* 2010).

New technologies like proteomics are very good tools for obtain information about proteins secreted by pathogenic fungi. Nowadays, there is lot of candidate pathogenicity genes, but there is stagnation for their functional analysis, since experiments are time-consuming and difficult to realize for some fungi. However, genomic tools are already providing a much more integrated picture of pathogenicity mechanisms, compared with the previous focus on individual genes. Many fungal genes affecting disease progression are involved in growth and development, and there are few genes for which the only effect is on disease, proteomics allowed to identify between 10 and 100 different biological functions from each gene (Van De Wouw & Howlett, 2011; Fernandez-Acero *et al.,* 2011). This is an important progress in the new fungicide discovery because pathogenic genes with function in growth and development could be target site for new fungicides.

### **4. Morphogenesis**

Since fungi are a eukaryotic organism, they have diverse metabolic profiles similar to many mammalian and plant. Hence, several antifungal agents discovered to be potentially active against plant pathogenic fungi have failed to survive during the testing process because the target site of the fungicide is found in another organism (Thines *et al.,* 2004).

The most successful fungicide in the market today acts relatively broadly by targeting fungal vegetative growth and thus the entire fungal life cycle. Examples of a successful mode of action classes interfering with biochemical progresses essential in fungi include compounds targeting respiration and sterol biosynthesis. An example of the former mode of action class is given by compounds which target mitochondrial electron transport within the respiration chain. Fungicides of the strobilurin class have this mode of action. These

stage. These fast-evolving effector genes are localized to highly dynamic and expanded regions of the *P*. *infestans* genome. This probably plays a crucial part in the rapid adaptability of the pathogen to host plants and underpins its evolutionary potential (Haas *et al.,* 2009). Other example of pathogen trainer of virulence factors is *Botrytis cinerea* to date have been identified a wide range of compounds and enzymes that uses the fungus to exerts its pathogenicity, thanks to the arsenal of degrading enzymes, *B. cinerea* is able to feed on different plant tissues, this fungus shares conserved virulence factors with other phytopathogens (Choquer *et al.,* 2007). *Botrytis cinerea* is a ascomycete necrothrofic, this fungi alone is responsible for 10% of the global fungicide market (Fernandez-Acero *et al.,* 2011), is thought to enter the host mainly by producing degrading enzymes and causing an oxidative burst, specifically because secretes nonspecific phytotoxins to kill cells from a large spectrum of plants. Among the numerous metabolites isolated from fermentation broths, the most well known is the sesquiterpene botrydial (Deighton *et al.,* 2001). This fungus is notably equipped with multiple cell wall-degrading enzymes that allow plant tissue colonization and the release of carbohydrates for consumption. Pectin, the major host cell wall component, can be degraded by a set of fungal pectinases (Ten Have *et al,* 2001; Choquer *et al,* 2007). Xilanase (Xyn11A) from *Botrytis cinerea* contributes to the infection process with the necrotizing and not with the xylan hydrolyzing activity. The main contribution of the xylanase Xyn11A to the infection process of *B. cinerea* is to induce necrosis of the infected plant tissue. A conserved 30-amino acids region on the enzyme surface, away from the xylanase active site, is responsible for this effect and mediates

New technologies like proteomics are very good tools for obtain information about proteins secreted by pathogenic fungi. Nowadays, there is lot of candidate pathogenicity genes, but there is stagnation for their functional analysis, since experiments are time-consuming and difficult to realize for some fungi. However, genomic tools are already providing a much more integrated picture of pathogenicity mechanisms, compared with the previous focus on individual genes. Many fungal genes affecting disease progression are involved in growth and development, and there are few genes for which the only effect is on disease, proteomics allowed to identify between 10 and 100 different biological functions from each gene (Van De Wouw & Howlett, 2011; Fernandez-Acero *et al.,* 2011). This is an important progress in the new fungicide discovery because pathogenic genes with function in growth

Since fungi are a eukaryotic organism, they have diverse metabolic profiles similar to many mammalian and plant. Hence, several antifungal agents discovered to be potentially active against plant pathogenic fungi have failed to survive during the testing process because the

The most successful fungicide in the market today acts relatively broadly by targeting fungal vegetative growth and thus the entire fungal life cycle. Examples of a successful mode of action classes interfering with biochemical progresses essential in fungi include compounds targeting respiration and sterol biosynthesis. An example of the former mode of action class is given by compounds which target mitochondrial electron transport within the respiration chain. Fungicides of the strobilurin class have this mode of action. These

target site of the fungicide is found in another organism (Thines *et al.,* 2004).

binding to plant cells (Noda *et al,* 2010).

**4. Morphogenesis**

and development could be target site for new fungicides.

compounds are structurally based on natural products and interfere with the ubiquinol cytochrome C oxidoreductase (Foster & Thines, 2009).

There are numerous antifungal compounds that were discovered from diverse microbial sources using traditional activity-based screening techniques. These microbial compounds showed potent control efficacy against various plant diseases, including chronic diseases which are difficult to control with conventional synthetic fungicides. Advances in screening systems directed to specific targets of fungal metabolism have increased the opportunities to discover novel antifungal agents with selectivity over non-target organisms. Microbial metabolites have also been exploited as a source for non-fungicidal disease control agents that do not inhibit vegetative hyphal growth, but rather interfere specifically with the infection process of pathogenic fungi, such as spore germination, the formation of penetration structures and sporulation (Seok & Kook, 2007). Infection structures of phytopathogenic fungi are modified hyphae specialized for the invasion of plant tissue, initial events are adhesion to the cuticule and directed growth of the germ tube on the plant surface (Mendgen *et al.,* 1996). The specificity of microbial fungicides is a highly preferred characteristic in terms of impacting the environment, where it is closely related to the occurrence of fungicide resistance. The most recently developed fungicides from microbial metabolites, the strobilurins, provide a cue for the high risk of resistance development of site-specific fungicides.

These compounds have long been applied to control fungal diseases of rice, vegetables and fruits, and their effectiveness in controlling these diseases has been tested in the field and proven over many years. The importance of microbial fungicides, compared to synthetic compounds, may have been under evaluated in the past due to the limitation in their activity spectrum and in certain instances, the development of resistance (Knight *et al.,* 1997). Nevertheless, the excellent fungicidal activity of these microbial metabolites and their potential as lead candidates for further fungicide development continue to stimulate research and screening for antifungal microbial metabolites, some examples of this compounds are:

**Kasugamycin** is an amino-sugar compound discovered from the metabolites of *Streptomyces kasugaensis, in vivo* studies have shown that kasugamycin efficiently suppresses the development of *M. grisea* mycelia on rice plants in both preventive and curative treatments, to overcome potential resistance problems, mixtures of kasugamycin with different synthetic fungicides having different modes of action are currently in use.

**Polyoxins** are peptidylpyrimidine nucleoside antibiotics isolated from the culture broth of *Streptomyces cacaoi* var. *asoensis*, such excellent characteristics come from the fact that polyoxins selectively inhibit the synthesis of cell-wall chitin in sensitive fungi but have no adverse effects on organisms lacking chitinous cell walls.

**Validamycin A** produced by *Streptomyces hygroscopicus* var. *limoneus* has been effective in controlling rice sheath blight caused by *R. solani*. Validamycin A is converted within fungal cells to validoxylamine A, an extremely strong inhibitor of trehalose. The mode of action of validamycin A is favorable for biological selectivity, because vertebrates do not depend on the hydrolysis of trehalose (Doumbou *et al.,* 2001).

Target-Site-Specific Screening System for Antifungal Compounds 189

A major challenge for drug development today is how best to employ the new genome wide technologies to identify which metabolic pathways and gene products are critical for disease establishment and progression and thus to increase the probability of finding novel fungicide targets. Novel targets can be located either in biochemical or signaling pathways essential for vegetative growth or for pathogenic development of the fungus. Targets with high specificity can thereby be expected in pathways involved in adhesion, hostrecognition/pre-penetration processes, host colonization and the final reproductive differentiation processes during pathogenic development. An attractive proposition is the development of fungicides interfering with pathogenic development but not with vegetative growth. Such a strategy could prevent or cure infections by fungal pathogens without

We would like to conclude by stating that antifungal targets-site are extremely diverse. However, substances that acts on these target-sites needs to fulfill several prerequisites such as antifungal activity *in vivo* and lack of effects on the host cells. Furthermore, resistance mechanisms need to be excluded as far as possible. Therefore, investigation of the target site and the mode of action of an antifungal compound can be explored by statistical learning algorithms. Performance and applicability of the statistical learning methods in studying "fungal-target likeness" may be further improved by incorporation of new information from advances in genomic, proteomics, pathogenesis and morphogenesis studies. Efficiency and accuracy of statistical learning methods in the prediction of fungal-target like proteins can also be enhanced from new progress in

Abramovitch, R. B., Anderson, J. C. & Martin, G. B. (2006). Bacterial elicitation and evasion of plant innate immunity. *Nature Reviews Molecular Cell Biology*. 7:601-611. Albeck, S., Alzari, P., Andreini, C. , Banci, L., Berry, M., Bertini, I.,Cambillau, C., Canard, B.,

Barakat, H. Spielvogel, A., Hassan, M., El-Desouky A., El-Mansy H., Rath, F. Meyer, V. &

Stahl, U. (2010). The antifungal protein AFP from *Aspergillus giganteus* prevents secondary growth of different *Fusarium* species on barley.  SPINE bioinformatics and data management aspects of high throughput structural biology. *Acta Chrystallographic*. D62:1184-

affecting neutral or benign species (Foster & Thines, 2009).

learning algorithms and sequence descriptors.

**5. Conclusion**

**6. References**

1195.

*Biotechnology*. 87:617–624.

Promising microbial metabolites continue to be discovered using traditional activity-based screening procedures against various plant pathogenic fungi. In particular, many of the sitespecific antifungal metabolites have recently been discovered from microbial metabolites. These microbial metabolites include non-fungicidal compounds that interfere with the infection process of pathogenic fungi, and specific inhibitors of the fungal biosynthetic pathways for chitin, fatty acids and nucleic acids (Seok & Kook, 2007).

Other kind of antifungal agents are proteins; antifungal proteins have been isolated from various organisms ranging from bacteria, plants, insects and amphibians to human beings. Both their fungal target site and their mode of action are extremely diverse. In order for it to be applied, an antifungal protein needs to fulfill several prerequisites such as antifungal activity *in vivo* and lack of effects on the host cells. Furthermore, resistance mechanisms need to be excluded as far as possible. Therefore, investigation of the target site and the mode of action of an antifungal protein should reveal whether the protein is suitable for an application (Theis *et al.,* 2005). The antifungal protein (AFP) are abundantly secreted by the filamentous fungus *Aspergillus giganteus*, this cysteine-rich protein have ability to disturb the integrity of fungal cell walls and plasma membranes but does not interfere with the viability of other eukaryotic systems (Barakat *et al.,* 2010; Meyer, 2008).

Severe membrane alterations in *A. niger* were observed, whereas the membrane of *P. chrysogenum* was not affected after treatment with AFP. The protein localized predominantly to a cell wall attached outer layer which is probably composed of glycoproteins, as well as to the cell wall of *A. niger*. It was found to accumulate within defined areas of the cell wall, pointing towards a specific interaction of AFP with cell wall components. In contrast, very little protein was bound to the outer layer and cell wall of *P. chrysogenum*. The protein was found to act in a dose-dependent manner: it was fungistatic when applied at concentrations below the minimal inhibitory concentration, but fungicidal at higher concentrations. Using an *in vivo* model system was demonstrated that AFP indeed prevented the infection of tomato roots (*Lycopersicon esculentum*) by the plant-pathogenic fungus *Fusarium oxysporum* f. sp. *Lycopersici* (Theis *et al*., 2005).

The fungal profilins, small actin-binding proteins that share limited homology to human profilin, can operate as a potential drug target, since these proteins are essential for the growth of most eukaryotic cells, including *S. cerevisiae* (Witke, 2004). Addition, the existence of structural information can support the design of structure-based ligands for profilins. Peptides are generally used as lead compounds in drug development, to design a novel peptide ligand, an *in vitro* evolution approach has often been used. Although this approach can be used without three-dimensional (3D) structural information about the target protein, it requires laborious experimental procedures, including library constructions and the screening of bioactive peptide ligands. In this respect, if information on the structure and the active site of the target protein is known, an *in silico* approach based on the 3D structure of the target protein is a useful approach to designing the peptide ligand. The validity of the profilin as antifungal drug target was evaluated by Ueno *et al*. 2010, amino acid alignments showed the low homology between human and fungal profilins. This implies that the fungal profilin could be a target with high selectivity. Furthermore, a mouse infection study showed that the suppression of profilin expression attenuated the fungal burden in the kidney and indicated that the profilin was required for survival in the host's body (Ueno *et al.,* 2010).

A major challenge for drug development today is how best to employ the new genome wide technologies to identify which metabolic pathways and gene products are critical for disease establishment and progression and thus to increase the probability of finding novel fungicide targets. Novel targets can be located either in biochemical or signaling pathways essential for vegetative growth or for pathogenic development of the fungus. Targets with high specificity can thereby be expected in pathways involved in adhesion, hostrecognition/pre-penetration processes, host colonization and the final reproductive differentiation processes during pathogenic development. An attractive proposition is the development of fungicides interfering with pathogenic development but not with vegetative growth. Such a strategy could prevent or cure infections by fungal pathogens without affecting neutral or benign species (Foster & Thines, 2009).


**CDDO-Me Selectively Attenuates CA1 Neuronal Death Induced by Status Epilepticus via Facilitating Mitochondrial Fission Independent of LONP1**

**Ji-Eun Kim 1,2, Hana Park 1,2, Seo-Hyeon Choi 1,2, Min-Jeong Kong 1,2 and Tae-Cheon Kang 1,2,\***

Received: 26 June 2019; Accepted: 3 August 2019; Published: 5 August 2019

**Abstract:** 2-Cyano-3,12-dioxo-oleana-1,9(11)-dien-28-oic acid methyl ester (CDDO-Me) is a triterpenoid analogue of oleanolic acid that exhibits promising anti-cancer, anti-inflammatory, antioxidant and neuroprotective activities. In addition, CDDO-Me affects cellular differentiation and cell cycle arrest, and irreversibly inhibits Lon protease-1 (LONP1). In the present study, we evaluate the effects of CDDO-Me on mitochondrial dynamics and its downstream effectors in order to understand the underlying mechanism of the neuronal death following status epilepticus (SE, a prolonged seizure activity). CDDO-Me increased dynamin-related proteins 1 (DRP1)-serine 616 phosphorylation via activating extracellular-signal-regulated kinase 1/2 (ERK1/2) and c-Jun *N*-terminal kinase (JNK), but not protein kinase A (PKA) or protein phosphatases (PPs). In addition, CDDO-Me facilitated DRP1-mediated mitochondrial fissions, which selectively attenuated SE-induced CA1 neuronal death. Unlike CDDO-Me, LONP1 knockdown led to SE-induced massive degeneration of dentate granule cells, CA1 neurons and hilus interneurons without altering the expression and phosphorylation of DRP1, ERK1/2, JNK and PP2B. LONP1 knockdown could not inhibit SE-induced mitochondrial elongation in CA1 neurons. Co-treatment of CDDO-Me with LONP1 siRNA ameliorated only CA1 neuronal death, concomitant with abrogation of mitochondrial elongation induced by SE. Thus, our findings suggest that CDDO-Me may selectively attenuate SE-induced CA1 neuronal death by rescuing the abnormal mitochondrial machinery, independent of LONP1 activity.

**Keywords:** 4-HNE; DRP1; ERK1/2; hippocampus; JNK; mitochondrial dynamics; PKA; protein phosphatases; TUNEL