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# Open Chemistry

### formerly Central European Journal of Chemistry

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Volume 15, Issue 1

# ‘Capiture’ plants with interesting biological activities: a case to go

Nassifatou Koko Tittikpina
• Corresponding author
• Faculty of Pharmacy, Department of Bio-organic Chemistry, Building B 2.1., Room 1.13. Saarland State University, Campus D-66123 Saarbrücken, Germany
• Laboratoire de Botanique et Ecologie Végétale, Université de Lomé, BP 1515, Lomé, Togo
• Université de Lorraine, SRSMC, UMR 7565, 54001 NANCY Cedex. France
• CNRS, SRSMC, UMR 7565, ICPM, 1 boulevard Arago 57078 METZ Cedex 3. NANCY Cedex France
• Email
• Other articles by this author:
/ Wouyo Atakpama
/ Hodabalo Pereki
• School of Pharmacy, Division of Bioorganic Chemistry, Building B 2.1., Room 1.13. University of Saarland, Campus D-66123 Saarbrücken, Germany
• Other articles by this author:
/ Wesam Ali
• School of Pharmacy, Division of Bioorganic Chemistry, Building B 2.1., Room 1.13. University of Saarland, Campus D-66123 Saarbrücken, Germany
• Other articles by this author:
/ Stéphane Fontanay
• CNRS, UMR 7565, SRSMC, Vandoeuvre-lès-Nancy, F-54506 Nancy, France
• Université de Lorraine, UMR 7565, SRSMC, Faculté de Pharmacie, F-54001, Nancy, France
• ABC Platform®, Faculté de Pharmacie, F-54001 Nancy, France
• Other articles by this author:
/ Frédéric Nana
• Université de Lorraine, SRSMC, UMR 7565, 54001 NANCY Cedex. France
• CNRS, SRSMC, UMR 7565, ICPM, 1 boulevard Arago 57078 METZ Cedex 3. NANCY Cedex France
• Other articles by this author:
/ Chukwunonso Ecc Ejike
• Department of Medical Biochemistry, Faculty of Basic Medical Sciences, Federal University Ndufu-Alike, Ikwo, PMB 1010 Abakaliki, Ebonyi State, Nigeria
• Other articles by this author:
/ Gilbert Kirsch
• Université de Lorraine, SRSMC, UMR 7565, 54001 NANCY Cedex. France
• CNRS, SRSMC, UMR 7565, ICPM, 1 boulevard Arago 57078 METZ Cedex 3. NANCY Cedex France
• Other articles by this author:
/ Raphaël Emmanuel Duval
• CNRS, UMR 7565, SRSMC, Vandoeuvre-lès-Nancy, F-54506 Nancy, France
• Université de Lorraine, UMR 7565, SRSMC, Faculté de Pharmacie, F-54001, Nancy, France
• ABC Platform®, Faculté de Pharmacie, F-54001 Nancy, France
• Other articles by this author:
/ Patrick Chaimbault
• Université de Lorraine, SRSMC, UMR 7565, 54001 NANCY Cedex. France
• CNRS, SRSMC, UMR 7565, ICPM, 1 boulevard Arago 57078 METZ Cedex 3. NANCY Cedex France
• Other articles by this author:
/ Simplice D. Karou
• Ecole Supérieure des Techniques Biologiques et Alimentaires (ESTBA-UL), Université de Lomé, Lomé, Togo
• Other articles by this author:
/ Komlan Batawila
/ Koffi Akpagana
/ Claus Jacob
• School of Pharmacy, Division of Bioorganic Chemistry, Building B 2.1., Room 1.13. University of Saarland, Campus D-66123 Saarbrücken, Germany
• Other articles by this author:
Published Online: 2017-10-18 | DOI: https://doi.org/10.1515/chem-2017-0024

## Abstract

The investigation of natural products used in Traditional Medicine in Africa is complicated as modern analytical and screening methods are often not available. Computer aided product identification from traditional usage records (CAPITURE) may provide an interesting alternative and has been evaluated in the context of an ethnobotanical survey on fungal diseases and their traditional treatment in Tchamba District (Togo). 53 traditional healers were interviewed and their knowledge recorded. Several indicators, the Use Value (UV), Plant Part Value (PPV), Specific Use (SU) Value, Intraspecific Use Value (IUV) and Informant Consensus Factor (ICF), were applied to the data. Those indices, in addition to a bibliographic review, were then fed into a computer-aided approach which predicted two interesting plants out of the 43 species survey-recorded and their specific activities: Pterocarpus erinaceus sap against ringworm, Daniellia oliveri sap against intertrigo and respectively their roots and trunk barks against candidiasis. Subsequent laboratory-based studies have confirmed the predicted antimicrobial activities with MIC (128 μg/mL to 30 mg/mL) and without any notable toxicity on a normal human cell (MRC-5 cells). Although such a method may not be flawless, it is able to provide first leads, and in the face of limited resources, is an attractive alternative worth considering.

## 1 Introduction

Nature provides a treasure chest of natural products which often have amazing biological activities and have been used for agricultural and medical applications for centuries throughout the world. The lush vegetation in Western Africa is particularly rich in medical plants, and the native tribes in countries such as Togo employ a vast arsenal of plants and plant-derived products as part of their Traditional Medicine [1, 2, 3, 4, 5, 6]. However, identifying which plants, plant products and substances contained therein are active and may be applied against certain diseases, and which may be toxic or less attractive because of (traditionally) known side effects is far from trivial. Admittedly, modern analytical methods of sample analysis and compound identification, such as automated chromatography coupled with mass spectrometry can identify specific substances from crude materials within hours. At the same time, equally automated activity screens can reveal an activity or toxicity profile against target (micro-) organisms or cells within a day or two. Hence our ability to screen for (new) medically active substances in the laboratory today is rather advanced compared to the cumbersome studies of the generation before us.

However, even the most advanced toolbox of analysis, compound identification and robotic activity screens cannot analyze the entire flora of the planet. Even those powerful methods a priori require a certain narrowing down of particularly interesting plants, and here often rely heavily on the century-old knowledge of Traditional Medicine. Indeed, whilst most developing countries, for instance in Africa, Asia or South America can hardly afford the kind of expensive methodology for (bio)analysis and activity screens, those countries are exceptionally rich in medical plants and traditional knowledge related to them. The World Health Organization (WHO) has estimated that 80% of the population in the developing world still rely traditional medicine to meet their healthcare needs [7].

In this situation, the famous question “Where to begin?” may well be answered most efficiently by a brief consultation of the Medicine (Wo)man. Let’s therefore consider one country in Africa which stands for the plight and opportunities of many others: Togo. In Togo, economic hardship and an uneven access to healthcare facilities and modern medication allow the spread of infectious diseases, which in this country rank among the top ten priority diseases [8,9]. Natural remedies based on locally grown plants and traditional knowledge related to them often represents the only source and resource to treat such bacterial and fungal infections. Consequently, it is imperative to investigate such plants further, and various studies have been run in the country already to bring the traditional therapeutic approach to the forefront [10, 11, 12].

Nonetheless, it is impossible to screen all plants of Togo associated with one or more medical uses for all (kind of) possible medical applications. In contrast, it may also be risky to simply rely on one’s first impression and gut feeling. Here, a more structured and ultimately also more focused approach is warranted. We have therefore developed a simple computer-aided “pre-selection method” which (a) records hitherto unstructured and orally passed on traditional knowledge in semi-structured interviews, (b) extracts quantitative numerical values from these testimonies, (c) uses these numerical values in a computer-aided method to (d) rank, select and hence identify the most promising plants or plant parts as leads for further laboratory based investigations. This method has several advances when compared to a simple subjective “selection by experience” or literature survey. On the one hand, it generates a record of traditional uses which can be archived and preserved for future generations. On the other hand, it can be employed rather successfully to narrow down the field of possible plant candidates by applying an objective algorithm to an ethnobotanical study, as we will demonstrate for plants used to treat antimicrobial (antifungal) diseases in the Tchamba prefecture of Togo.

## 2.1 Area of study: The Tchamba district of Togo

Togo is a country with a lush and also facet-rich vegetation, and home to numerous known and suspected medical plants (Figure 1) [13, 14, 15, 16]. It is also ethnographically highly diverse, and hence features a rich and diverse, often tribal knowledge of traditional medicine, which is still the main (re)source for the treatment of many diseases [9]. The Tchamba District in Togo, which is located in the central eastern part of the country, is unique as it is the only district which brings together people from nine different ethnic groups: Tchamba, Koussountou, Tem, Tem Fulani, Kabyè, Ana-Ifè, Bassar, Lamba and Logba. We have therefore selected this specific, narrow, local ethnical melting pot of people, their cultures and traditions as it (a) promises extensive yet also varied local traditional medical knowledge and (b) can be surveyed efficiently with its high concentration of traditional healers within short travel distances. Furthermore, there has been no previous investigation of traditional uses of plants against infectious (fungal) diseases in this district, hence our study will be unbiased and generate records and data which in any case will be novel and original.

Figure 1

Map of Togo showing the study area. A: Togo in West Africa. B: Togo and its different regions and districts. C: Tchamba District with the localities prospected during the survey.

## 2.2 Ethnobotanical survey

In the Tchamba District of Togo (Figure 1), semi-structured individual interviews on plants used for the treatment of fungal diseases have been conducted with 53 traditional healers (TH) in the main localities of the district in September 2010. The questionnaire used, recorded information on (a) personal data of the interviewee (name, age, sex, level of education, ethnicity, living place, specialty, knowledge origin) (b) the type of fungal diseases treated, i.e. the name of the disease in the local language and the symptoms, (c) the plant part(s) used, and its/ their mode of preparation and administration, as well as (d) other diseases treated with the plant (s) mentioned by the TH. The interviews were complemented by a brief field inspection of the plant species described and a collection of small specimens of the mentioned plant species for further, professional identification and authentication at the Laboratory of Botany and Plants Ecology of University of Lomé, with cross-reference to the website www.ipni.org and for depositing voucher specimens at the Herbarium of the University of Lomé. This field trip followed strict rules in order to protect the rights of the TH with regard to the information they provided and also to safeguard the biodiversity of the area. Here, consent from the National Association of Traditional Healers in Togo (CERMETRA) was obtained prior to the survey and CERMETRA also delegated two representatives who accompanied the authors throughout the survey.

## 2.3 Turning testimonies into data

To convert structured interviews into quantitative, numerical data, the information contained within the questionnaire sheets collected was entered into Microsoft Excel spreadsheets and analyzed. The analysis was based on the computation of general and specific indices, some of which have been described previously [11, 12, 17]. This analysis was designed as robust yet also simple and “doable” with access to limited resources. For instance, Microsoft Excel spreadsheets, rather than expensive statistic programs, were chosen as they are widely available and enable simple calculations of parameters. Besides Microsoft Excel, free software, such as Free Office, Libre Office or WPS Office would also be suitable to conduct such simple calculations.

The Informant Consensus Factor (ICF) was determined to evaluate the consensus among traditional healers as follows: $ICF=Nur−ntNur−1$

where Nur is the number of uses reported by respondents for a particular disease and nt the number of plants species reported to be used to treat this particular disease [12, 18].

The Reported Use (RU) was defined as the total number of uses reported for each plant and was subsequently used to calculate the Use Value (UV) as indicator of the relative importance of the species: $UV=∑UorRUn$

where ∑U (same as the RU, is the total number of citations per species) and n the number of informants [11, 12, 18].

Not all parts of a given plant are equally used for treatment; hence the Plant Part Value (PPV) provides information on the parts of a plant most used to treat a disease. The PPV is equal to the ratio between the total number of reported uses for the plant’s part and the total number of reported uses for that plant: RUplant part/ RUplant*

Similarly, not all plants are used to treat all (kinds of) diseases, hence the Specific Use (SU) value was introduced to reflect the number of times a plant part is applied for a more specific use against a specific disease.

Finally, Intraspecific Use Value (IUV) was defined as the ratio between the SU value of a plant part and the RU for this plant: SUplant part/ RUplant*. The IUV is probably the most refined of the parameters discussed as it enables a comparison between different parts of a plant used to treat a specific type of disease [11, 17, 18].

## 2.4 Selection criteria to cap(i)ture plants of interest

Equipped with the various parameters and values calculated as described above, reliable selection criteria has been developed to rank the 43 plants put forward by the traditional healers. These criteria were crucial in order to select a reasonable number of promising plants and plant parts for further laboratory based assessment, without, of course, ruling out any of the others (Figure 2). After the RU and the UV for all plants were calculated, a long-list of likely candidates was obtained. A cut-off based on a RU (≥2) or a UV (≥ 0.0377) was applied to obtain a short list with a reasonable number of entries. Subsequently, a bibliographic review on the plants with the highest UV (≥ 0.0377) or RU (≥2) was conducted. This resulted in a final list of a small number of plants which were (a) frequently used in the Tchamba District to treat (various) fungal diseases, (b) were independently mentioned as medical plants in the literature and (c) were still of sufficient novelty to warrant further investigation.

Figure 2

A schematic overview of the CAPITURE approach.

The first step is usually carried out after an ethnobotanical survey: where researchers are able give an overall global view on the plants used in a certain community to treat certain diseases, and are able to deduce the most important ones due to their high indices. But researchers who would like to continue on a particular plant, to confirm or infirm its traditional use and or study its interesting chemistry, are impeded by questions they ask themselves: which plant to choose? Which plant part to focus on as a start? Which disease? And as a results of these ambiguous questions, researchers end up making selections of plants based on ‘good feeling’, or just working on all the plants to find out the ‘most interesting ones’.

We are taking the example of this study to propose a ‘more objective’ approach in the selection of the most interesting plant(s)/plant part (s) on which to conduct deeper research either in the pharmacology or natural products chemistry. Subsequently after the first general step selection, we are proposing two possible avenues to proceed further, where the choice of avenue depends on the particular situation at hand. We will introduce both avenues here.

As part of the first avenue, one may initially define the plant and then consider possible targets or target diseases this plant may be effective against. The selection here is based on the specific indices PPV, SU and IUV, which need to be computed on the plants of the final list. The most interesting plants will be the ones with the highest SU and IUV.

The second avenue is more focused on the treatment of a specific disease of interest, which is defined upfront, and one may then hunt for the most promising plant or plant part to treat this specific disease. It narrows down the type of disease which may be treated (in our case different kinds of fungal infections) and can rely on the ICF, SU and IUV. As a first step, the ICF needs to be calculated for the different types of fungal diseases reported by the TH. This, places a focus on fungal diseases that have the highest ICF. The next steps are to identify the plants parts used to treat fungal diseases with the highest ICF and to compute the SU and IUV on these plants parts. The most promising plant parts that will come out from this computation will also be the ones with the highest SU and IUV.

This method is preferably employed as an ethnobiological recording and pre-screening exercise before more eloquent and expensive analytical and activity screening methods are unleashed.

## 2.5 Collection of plant material and preparation of extracts

For the plants pre-selected by the algorithm described above, an official letter of authorization from the ‘Direction de la Protection des Végétaux’ was obtained to collect specimens, and those were collected in the central region of Togo (GPS coordinates: 09°11′689″ North, 001°15′942″ East) on the 19 June 2014 after a formal identification by a botanist. A voucher specimen was deposited at the Herbarium of the University of Lomé under the number: TOGO 15076 for D. oliveri and TOGO 15077 for P. erinaceus. After collection, trunk barks and roots were dried at 25°C in the laboratory of Botany and Plants Ecology of the University of Lomé at 25°C and milled. After milling, they were sealed and brought to Europe by plane under the official licence mentioned above. They were kept in a dry and dark place until further use. Trunk barks (containing sap) were collected in replacement of the fresh sap because collection and biological testing of fresh sap as used by traditional healers was not possible (the patient is brought towards the tree, the trunk bark is cut and the sap is applied directly onto the ringworm or intertrigo).

In order to prepare suitable extracts for biological activity studies, a preliminary assessment with different mixtures of solvents and TLC analysis was performed (TLC silica gel 60 F254, Merck Millipore, 1.05554.0001). The best separation was obtained with a mixture of methanol and dichloromethane MeOH-DCM (1:1, v/v) with Pterocarpus erinaceus and MeOH (100%) with Daniellia oliveri (solvents of a grade suitable for chemical synthesis were used). Consequently, 3 Kg of powdered trunk barks and roots, respectively, were saturated/soaked in these solvents at room temperature for 48 h. The resulting mixtures were filtered, the marc discarded and the eluates evaporated under reduced pressure using a rotavapor to obtain raw extracts. The raw extracts have further been fractionated using liquid-liquid partition with solvents of different polarities, ranging from 1 to 5: (1) petroleum ether, (2) dichloromethane, (3) ethyl acetate, (4) 1-butanol and finally (5) distilled water.

## 2.6 Antibacterial and antifungal assays

To assess the antimicrobial activity of the extracts, selected strains of bacteria and fungi were employed, with a particular focus on infections identified as part of the CAPITURE method. Indeed, candidiasis is usually caused by Candida albicans, Trycophyton rubrum is the pathogen behind ringworm and in the case of intertrigo, the causes could mainly be Candida albicans, Staphylococcus aureus and Pseudomonas aeruginosa [19].

The activity assays therefore included Staphylococcus aureus (ATCC 29213, ABC 1),Pseudomonas aeruginosa (ATCC 27853, ABC 4), as well as Candida albicans. All strains were kindly provided by the ABC Platform® Bugs Bank. Activity against Trycophyton rubrum was investigated previously and there was no need to reproduce these studies.

Bacterial strains were grown on Mueller Hinton Agar (MHA, Difco 225250) or Mueller Hinton Broth (MHB, Difco, 275730). C. albicans was grown on Sabourhaud agar (SA) plates. The purity of the isolates was checked throughout the study by examination of colony morphology and employing the Gram staining procedure.

The antimicrobial activity on the raw extracts and their fractions was estimated by employing the broth dilution method to determine the Minimal Inhibitory Concentration (MIC, the concentration that inhibits 100% of bacterial growth) [20]. To determine the MIC, bacterial suspensions were prepared by suspending one isolated colony from MHA plates in 5 mL of MHB. After 24 h of growth, the suspensions were diluted in distilled water to obtain a final inoculum of 5×105 to 5×106 CFU (Colony Forming Units).

Inoculum of C. albicans was prepared by suspending 5 isolated colonies from SA plates in 5 mL of distilled water. This solution was diluted using Roswell Park Memorial Institute medium without carbonates and with phosphates (RPMI-1640, Sigma R6504) to obtain a suspension whose concentration was equal to 0.5 McFarland units.

At this stage, twofold serial dilutions of extracts were prepared in MHB for anti-bacterial activities and RPMI-1640 medium for anti-fungal activities, in 96-well plates (Greiner, 650161), starting from a stock solution of 120 mg/mL.

An equal volume of bacterial or fungal inoculum was added to each well on the microtiter plate containing 0.05 mL of the serial extract. After incubation for 18-24 h at 35°C for bacteria, 18-24 h for yeast, the MICs were determined with a 96-wells plate reader at 540 nm (Multiskan EX, Thermo Electron Corporation, France) as the lowest concentration of compound whose absorbance was comparable with the negative control wells (broth only or broth with extract or compound, without inoculum). Oxacillin, ticarcillin and Amphotericin B served as positive controls and benchmark antibiotics and anti-fungal agents for comparison and reference [21, 22]. Each condition was repeated in 8 wells and results were expressed as means of three independent experiments.

## 2.7 Cytotoxicity assay

In order to compare the - desired - activity of extracts against microbes with their - rather undesired - cytotoxicity against normal human cells, MRC-5 (ATCC CCL-171) human lung fibroblasts were used as model. Cells were grown in Minimum Essential Medium (MEM, 31095-029, Life Technologies-Gibco®) supplemented with 10% heat-inactivated fetal calf serum (CVFSV00-0U, Eurobio, Courtaboeuf, France) and 2 mM L-glutamine (G7513-100 mL, Sigma Aldrich), at 37°C in a 5% CO2 humidified atmosphere. Cells were then plated at 104 cells per well in 96-well tissue culture plates (83.1835, Sarstedt, Germany) and grown for 48 h at 37 °C in a 5% CO2 atmosphere. Medium was discarded and replaced by fresh medium containing increasing amounts of plant extract (range 1 μg/mL to 30 mg/mL) dissolved in dimethylsulfoxide (DMSO). The final concentration of DMSO never exceeded 2% of the final volume. Three different (negative) controls were added: medium alone, cells in medium and extract in medium. Each condition was repeated in eight wells. After 24 h incubation, medium was discarded and cells were washed with PBS.

The MTT assay was employed to quantify cytotoxic impact [23]. 100 μL of medium containing 0.5 mg/mL MTT previously prepared in PBS were added to each well and the plates were incubated for 4 h at 37°C. Then formazan crystals were dissolved by the addition of 100 μL of SDS (100 μg/mL), followed by incubation for 3 h at 37°C. Finally, the absorbance was measured at 540 nm vs 690 nm using a 96-wells plate reader (Multiskan EX, Thermo Electron Corporation, France). Percentages of survival and the half maximal inhibitory concentration (IC50) were calculated. Experiments were repeated three times [21].

## 3.1 Identification of plants for focused screening using the CAPITURE algorithm

Based on our interviews with 53 traditional healers in the Tchamba District, 43 plant species belonging to 43 genera and 27 botanical families have been identified in the context of the treatment of fungal diseases. These plant species form a long-list of plants that is provided in Table 1. For these 43 plants, the use value (UV) and the reported use (RU) have been computed and compared. Eventually, P. erinaceus (UV = 0.28), D. oliveri (UV = 0.11), F. virosa (UV = 0.05) and P. pinnata (UV = 0.05) have yielded the highest scores among the 43 species and, based on these values, it appears that they are the preferred plants administered by traditional healers to treat fungal diseases.

Table 1

Long list of plants obtained after the survey.

Indices. ∑RU: sum of Reported Uses, UV: Use Value. Local names. Tch: Tchamba, Te: Tem, La: Lamba, K (Kounssountou), Lo: Logba, Ka: Kabyè. Type of fungal and related diseases. R: Ringworm; I: Intertrigo; OC: Oral Candidiasis; SC: Sexual Candidiasis; F: Felon; Ony: Onychomycosis. Plants parts. Bu: bulb; B: barks; Fr: fruits; FrS: fruits shell; R: roots; Rhi: rhizome; S: sap; Wp: whole plant; L: leaves; Se: seeds; Tr: Trunk. Voucher number. NA: not appropriate.

Since the UV values differ considerably between the plants, we have been able to implement a fairly strict cutoff RU at 2 or UV at 0.04, which allows us to consider only those plants with a RU ≥ 2 or an UV ≥ 0.04, yielding the following short list of plants: Allium sativum, Anacardium occidentale, Calotropis procera, Cochlospermum planchoni, Quisqualis indica, Ricinus communis, Desmodium gangeticum, Flueggea virosa, Daniellia oliveri, Pterocarpus erinaceus, Xeroderris stuhlmannii, Milicia excels, Musa sapientum, Piper guineense, Zea mays, Paullinia pinnata, Nicotiana tabacu and Vitex doniana.

At this point, the bibliographic survey was performed to complement the testimonies. To our great surprise, this survey reveals that virtually none of plant species identified have previously been studied in vivo for antifungal activity (except P. erinaceus) [24]. Furthermore, the underlying chemical composition and activity of the materials so far is also not well documented. It also appears that none of them, with the notable exceptions of P. erinaceus and Ricinus communis, have been cited previously by other ethnopharmacological studies [24, 25]. In contrast, plants such as Allium sativum (the common garlic), Calotropis procera and Annacardium occidentale have been studied extensively before, yet those species do not score highly in our own CAPITURE analysis [26, 27, 28, 29, 30, 31, 32, 33, 34]. Conducting this review has helped identify a final list of plants as promising candidates and as the most original plants to be analyzed and studied further considering the feeble data of previous biological or chemical studies on them: P. erinaceus, D. oliveri, Ficus virosa and P. pinnata. The four plants are also the most used ones by traditional healers as revealed by the survey. To this final list, either the first or the second avenues of the CAPITURE approach could be applied as described in the methodology section.

Following the guidelines of the first option, the more specific and informative PPV, SU and IUV parameters were computed on the four species, identified as the most promising candidates. The results obtained for the PPV are summarized in Table 2.

Table 2

RU and PPV of most valuable plants parts.

The PPV parameter indicates which parts of a particular plant are most frequently utilized by TH, hence narrowing down the plant material to be studied. In the case of P. erinaceus, the trunk bark (0.4) and the sap (0.53) represent the parts most frequently employed by TH to treat fungal infections. Similarly, in the case of D. oliveri, the sap (0.71) and trunk bark (0.28) are most frequently used, whilst for F. virosa and P. pinnata, the roots are the only parts utilized. To address the question which fungal infections to consider, the SU and the IUV parameters were calculated. It becomes immediately apparent that the sap of P. erinaceus is frequently used in the treatment of ringworm and its roots to treat candidiasis, whilst the sap of D. oliveri is utilized in the context of intertrigo and its stems barks to treat candidiasis (Table 3).

Table 3

SU and IUV as indicators of potential uses of the preselected plants.

Considering the second avenue of the CAPITURE approach, we have calculated the Informant Consensus Factor (ICF) as discussed in the previous section, on the diseases identified by traditional healers: candidiasis (oral and sexual), intertrigo, ringworm, onychomycosis and felon (Table 4).

Table 4

The main Symptoms of the fungal diseases and the Informant Consensus Factor (ICF).

Indices. Nur: number of uses; nt: number of plants species; ICF: Informant Consensus Factor.

It has helped to identify ringworm (0.59), intertrigo (0.57) and candidiasis (0.41) are the fungal diseases with the highest ICF. This high value of ICF implies that most of the TH agree on a set of plants from the short list, which they use preferably to treat those three infections. Consequently, we have computed the SU and IUV of those plants, just focusing on their use in the treatment of the three ailments. This has conducted to obtain the same information as provided in Table 3.

To direct our in vitro biological screens, we have combined both sides of the coin to see which parts of the plants are used for the treatment of which specific fungal infections. It seems that the sap of P. erinaceus is the most attractive plant material employed against ringworm, whilst the roots of this plant seem to be particularly effective against candidiasis. The sap of D. oliveri appears to be effective against intertrigo, and the trunk barks of this tree bear promise in the treatment of candidiasis.

## 3.2 Screens for antimicrobial activity

We have therefore decided to follow this lead and to investigate further the activity of extracts of D oliveri and P. erinaceus against microbial infections: the trunk barks of the first one and the roots of the second one against Candida albicans, the trunk barks of the first one against Staphylococcus aureus and Pseudomonas aeruginosa and the trunk barks of the second one against Trycophyton rubrum. As anticipated, the water extract of the roots of P. erinaceus, the ethyl acetate fraction and water extracts of the trunk barks of the other plant, are active against Candida albicans with respective MIC values at 1.875 mg/mL, 30 mg/mL and 1.875 mg/mL. The activity of P. erinaceus against Tricophyton rubrum was previously tested with a total inhibition of fungal growth at 40 mg/ mL in vitro (97%) and in vivo (100%), values that were superior to the ones obtained with Griseofulvine as benchmark antifungal agent (92% at 40 mg/mL) [24]. D. oliveri trunk barks were also tested against S. aureus and P. aeruginosa (the other two germs involved in intertrigo). As anticipated with the CAPITURE approach, activity was observed on the two germs, with the methanolic raw extract on S. aureus at 128 μg/mL and on P. aeruginosa at 256 μg/mL. The following extracts derived from a fractionation of the methanolic raw extract of the stems barks of D. oliveri, were further been tested on the two germs: petroleum ether, dichloromethane, ethyl acetate, butanol and water fractions. Interestingly on S. aureus, the MIC at 128 μg/mL obtained with the raw extract was kept with almost all the fractions, except a non-significant difference with the petroleum ether and dichloromethane fractions where a MIC at 256 μg/mL was obtained. On P. aeruginosa, no MIC has been observed with the non-polar fractions, only with the butanol and water fractions with also a conservation of the MIC at 256 μg/mL for the butanol fraction and 128 μg/mL for the water fraction. The toxicity of the active extracts and fractions of the two plants were consequently tested on normal human cell lines, namely MRC-5 cell lines. No toxicity has been observed at the concentration at which the extracts or fractions were active. To the best of our knowledge, no previous study has reported the toxicity activities of these two plants on MRC-5 cells. Besides, no previous study has also reported the anti-bacterial activity of the two plants using the broth dilution method as investigated in this study.

Eventually, it seems that the combination of a semiquantitative ethnopharmacological and literature survey has provided one correct lead worth following up with more detailed laboratory based studies. It should be mentioned that there are some caveats associated with such an approach and always room for improvement and refinement. The specific indices PPV, IUV and SU, for instance, have been first reported by Gomez-Beloz in 2002; who employed them to widen the knowledge about specific pre-defined plants by interviewing 40 members of the Winikina Warao community in Venezuela [11]. CAPITURE, on the other hand has explicitly avoided a narrow focus on one community because of possible bias, for instance based on a narrow tradition, superstition or magic. Indeed, the results obtained do not disagree with the information gathered from individual TH. Besides, in CAPITURE, we did not compute the Disease Consensus Index (DCI) indicative of specific plants used to treat a single disease within a specific community [35]. In the CAPITURE method, we have rather computed the ICF. Indeed, the survey of TH did not focus on just one specific disease but on fungal diseases in more general terms, hence representing a broad disease category. Only towards the final steps, the ICF has been employed to narrow down this broad disease category to a more focused number of specific fungal infections. Crucially, the latter were not preset but defined by the TH themselves.

## 4 Conclusions

In summary, we have been able to use our method to move on from a basic ethnopharmacological survey of 53 traditional healers in the Tchamba District of Togo to a more structured, objective appraisal of existing knowledge on the use of natural plant products against a spectrum of common fungal infections. Whilst our approach still leaves various questions unanswered (e.g. about plant species eliminated from the list) and provides sufficient room for improvement (e.g. by introducing further chemical and environmental parameters), it nonetheless has allowed us to narrow down the vast number of medical plants found in Togo to a selected few which were also proven to be highly active biologically (MIC as low as 128 μg/mL).

In future, we will expand this method to involve more TH and to consider additional diseases. This way we will not only identify additional leads for promising medical plants, but we will also be able to record, store and safeguard the century-old knowledge of TH which has been passed on through the generations and is always at risk of “getting lost” in the mist of time. Importantly, this kind of recording is structured and hence can capture tens or even hundreds of testimonies, not in form of traditional “stories from the forest” but as focused, comprehensive yet down to the point questionnaires.

At the same time, we are investigating more closely the few leads identified so far, especially in the context of P erinaceus and D. oliveri, bearing in mind that the CAPITURE approach is only a pre-screen to be followed by a full laboratory based analysis of the (active) chemical ingredients found in the plants, an assessment of their spectrum of biological activities and potential uses and a full investigation of the underlying mode(s) of action. The long-list with a total of 43 plants will always be around for a reappraisal of plants, plant parts and infections they may be active against should the need arise.

Eventually, the method described here not only serves as an objective “selection tool” for promising plants based on traditional knowledge which goes beyond the kind of subjective inkling often used by researchers whilst sifting through the woodlands or the literature associated with it. It helps researchers save time and resources by allowing them to directly work on the most interesting plants (not all the plants recorded during an ethnobotanical survey), as well as saving resources, which is crucial for countries from the developing world. Equally it saves the same resources and funding in the developed countries because research could not be carried out on all the plants of the world. Hence there is an apparent need for a certain set of narrow(er) criteria. It also records, archives, preserves and disseminates century-old knowledge held by traditional healers which has been passed on orally from generation to generation, which otherwise is bound to be lost. Furthermore, the method demands a site visit, personal contact with the TH and, above all, a professional inspection of the plants employed, and eventually creates an inventory of medical plants of the region, with voucher specimen available for further studies. For all these reasons, it is therefore certainly worth considering and amending for future investigations.

## Acknowledgements

We are thankful to the traditional healers of Tchamba District in Togo for sharing their knowledge with us. Mr. Figui Nandji and Mr. Amoussou Sadoukou from the CERMETRA (Centre de Recherche en Medecine Traditionnelle et Appliquee) are also acknowledged not only for the sharing but also for their help during the survey. The leading members and all the members of CERMETRA are warmly acknowledged. We acknowledge the ‘Schlumberger Foundation’ for its Faculty For The Future (FFTF) fellowship to NKT. Financial support has also been provided by the Universities involved, namely the University of Saarland, the University of Lorraine and the University of Lome.

We also acknowledge financial support from ‘GradUS’ (University of Saarland, Germany), the French Ministry of Further Education and Research (MRES), the French National Scientific Research Centre (CNRS) and Region Lorraine.

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Accepted: 2017-07-11

Published Online: 2017-10-18

Author contributions: NKT carried out the research, performed the different experiments, elaborated the CAPITURE methodology and wrote the manuscript. WA and HP helped run the research (plants identification, treatment of the data) and mapped the area. MJN and WA helped conceive some of the figures. SDK critically reviewed the methodology and the manuscript. KB, KA, CJ, PC, RED and GK, supervised the research. CECCE, FN, SF and all the other authors read, improved the manuscript and approved its final version.

Conflict of interest: The authors declare no conflict of interest.

Citation Information: Open Chemistry, Volume 15, Issue 1, Pages 208–218, ISSN (Online) 2391-5420,

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