Compound’s Pre-Screening of Withania somnifera , Bacopa monnieri and Centella asiatica Extracts

Spectral fluorescence signature, Gas Chromatography-Mass Spectrometry and Liquid Chromatography-Mass Spectrometry for identification of chemical and bioactive compounds were applied to study the plant extracts of Withania somnifera, Centella asiatica and Bacopa monnieri which are related to the possible treatment of mental diseases as Alzheimer, Parkinson and De-pression. These plants are known for different positive phytotherapeutic effects on the human brain without negative post-, adverse or after effects to the treated individuals, and have been recommended in several medical studies. Therefore, we selected these plants for further analysis, based on the inhibition results of in vitro Amyloid Beta fibrillation tests made by previous measurements. With this study a first screening of the complex plant extract mixtures was performed, to get an initial overview about known and unknown ingredients. In all three plants, similar main compounds were identified, however in different quality and quantity. These may provide substantial information on which compound combinations might be mainly responsible for the positive effects and should be further investigated being responsible for reducing the fibrillation process of Amyloid Beta.


Introduction
In contrast to plant-derived synthetic medicines which are often associated with adverse effects and mostly target onto a single symptom, phytotherapy is commonly based on traditional knowledge of plants and their expected medical functions on so-called "medicinal wisdom of centuries" [1] [2] [3] and its increasing importance has been discussed [2] [3] [4] [5]. This motivates the usage of natural products which provides promoting medical effects without complications [4]. Such herbal medicines and medical plant extracts are complex bioactive compound mixtures for which an improved insight with specifications and proof-of-effectiveness of the ingredients is recommended [6] [7] [8] [9] raising several questions. What are the compounds within these extracts? What makes the plant mixtures more efficient than a pure synthetic drug? Why the plants' extracts have in the obtained dosages and mixtures almost none negative side effects?
In this study we performed an ingredients' screening of promising Ayurvedic plants-Withania somnifera, Centella asiatica, and Bacopa monnieri-to make first steps gaining insight into the prevention or treatment of diverse mental disorders like Alzheimer, Parkinson, Schizophrenia, and Depressions [10]. Extracts were selected from eight traditional Indian medicines-used since more than 2000 years-for a possible Alzheimer treatment and are known for several positive phytotherapeutic effects on the human brain and body without negative post-, adverse or after effects to the treated individuals (positive memory influence, stress reduction, mental health regeneration and reduction of anxiety), and have been recommended in several medical studies [11]- [22] which we previously investigated by in vitro Amyloid Beta fibrillation inhibition measurements by luminescence spectroscopy [10] [23]. Here, we applied Gas Chroma-
Breeding conditions in the green house were kept stable at 20˚C -24˚C with humidity of 40% -60%.
For the investigations, the powder material interior of capsules was removed for usage. The nutraceuticals were stored at 4˚C, but 30 minutes before experimental application, samples were taken out of the fridge, to equilibrate and handle them at room temperature.

Extraction Methods
SFS extracts were prepared with maceration with mortar and pestle (3 g plant material with 30 ml solvent) and were directly used after [10] [23].
For Gas Chromatography-Mass Spectrometry (GC-MS) and Liquid Chromatography-Mass Spectrometry (LC-MS) measurements two different kinds of plant extractions were utilized:

Soxhlet Extraction
Soxhlet Extraction (SE) was applied to obtain ingredients of the fresh and green plant material. The stock solvent of 96.7% ethanol (EtOH) with MilliQ water was used to prepare 65% and 50% EtOH solution (EtS). The 65% EtS was added to 15 g fresh plant material shortly before the extraction process which was initialized at a temperature of 95˚C for 30 minutes and continued at a stable temperature of 90˚C for 16 h. The SE of 50% EtS with 15 g green and fresh plant material run at a stabilized temperature of 100˚C for 14 h. Hereby, an initial temperature of 120˚C for 30 minutes was applied. The SEs were annealed and stored at 4˚C and at −80˚C in 2 ml tubes till further usage [10] [23]- [28]. All prepared extracts were centrifuged at 15.000 rpm (4˚C) to separate solutions from suspended particles and poorly dissolved materials. The upper solvent layer was pipette into marked tubes and stored in an ice box until experimental application [10] [23].

Methanol Extraction
Methanol (MeOH, Sigma Aldrich) extraction for compound analysis was tested with MeOH 95% (5% MilliQ water). 10 ml MeOH was put into a marked falcon tube and 3 g green and freshly harvested plant leaves were added to the solvent.
The sample was stored overnight at room temperature (12 hours) to soak for an extract. This solution was sterilized via centrifugation (1 min at 15.000 rpm and room temperature) and further membrane filtrated into the measurement tube.

Liquid Chromatography-Mass Spectrometry (LC-MS)
The Chromatographic separation was performed by use of an  All applied chemicals were obtained from Sigma Aldrich and industrial gases were provided by AS Linde Gas, Estonia.

Gas Chromatography-Mass Spectrometry (GC-MS)
The GC-MS analysis was performed utilizing an Agilent 5973N system with a with the splitless injector mode by a mass scan of m/z 50 -700. The relative percentage of each extract constituent was expressed as a percentage with peak area normalization. Interpretation of the mass spectrum of the plant extracts was conducted using the database of the National Institute of Standard and Technology (NIST11) library [30].
The evaporated SE samples for the GC-MS measurements were dissolved in 5 ml methanol before usage. Hereby, 1 ml of this methanol solution was filtrated through a micro-filter.
All applied chemicals were obtained from Sigma Aldrich.

Principal Component Analysis (PCA)
The PCA were used to preprocess the SFS data with the program named "Stan-dardScaler" (StSc). Hereby the StSc assumes the SFS produced data. Those data are normally distributed within each feature and scaled them in a way, that the distribution is centered around 0, with a standard deviation of 1. Nevertheless, the mean and standard deviation are calculated for the feature and its scale based on: xi-mean(x)/stdev(x) [38].
Furthermore allows the PCA to transform the high dimensional into low dimensional data for the best representation of entire data.

Withania somnifera (Ashwagandha, AS)
AS extracts and nutraceuticals affirmed to be complex mixtures consisting of many substances. Different measurements with LC-MS, GC-MS, and SFS were carried out. Hereby, with LC-MS and GC-MS around 10 k possible compounds were denoted, from which around 6 k were identified with 80% -100% Q Score.
The final list of all identified substances without duplicates was found to be [38]- [60]. In addition, approximately 4 k unknown possible ingredients remain unresolved.
The SFS data were analyzed via Principal Component Analysis (PCA), see

Bacopa monnieri (Brahmi, BR)
BR data were investigated and analyzed as described above (AS data) with LC-MS, GC-MS, and SFS. Hereby, we found several proteins, amino acids, vitamins and most of the expected compounds which are listed in  [63], as betulinic acid, alkaloids, and phenols, even brassinolide. However, we could not find the most expected ingredients: bacosides.
The PCA score plots (Figure 3 and Figure 4)  Notably, there is a certain difference between ethanol (EtOH) and the other samples ( Figure 3).

Centella asiatica (Gotu kola, GK)
GK LC-MS and GC-MS data are listed in  10.000 components and fragments were identified based on a Q Score of 80% -100%. Hereby, approximate thousand compounds were specified. Otherwise, several thousand peaks were analyzed but yet not be known. The PCA and score plot of the SFS measurements ( Figure 5 and Figure 6) show that between all GK samples ( Figure 5) exists the highest considerable differences of 64.13% for the first component and only-18.08% of variance for the second component.

Discussion
Based  Bacopa monnieri's expected main components were bacoside A and B which could not be found with LC-MS and GC-MS measurements, which might be due to fragmentation through the Soxhlet extraction or hard ionization: long extraction time with heating and the possible presence of enzymes or high ionization voltages. Nevertheless, we found numerous alkaloids, amino acids, proteins, betulinic acid, phenols and vitamins, from which some of them were expected compounds (Table 2). Furthermore, approximately 50% of the entire extracts and 60% of the dried nutraceuticals' contents were proteins, peptides, vitamins, amino acids, and other substances. Hereby, the SFS measurements ( Figure 1 and   Notably, in all three sample classes stearic acid, asiaticosides and asiatic acid were found which might have been caused by fragmentation through Soxhlet extraction, i.e. degradation (maybe the sterilization of the extraction filter was not sufficient enough). Still, we may not exclude these compounds which are essential for all three plants and maybe even the reason of their medicinal basic functioning-all three plants were used in the Ayurveda medicine against brain diseases [58]-which has to be verified further.
Also, we noted relevant differences between liquid and pure powder samples which may indicate, that it has to be analyzed, which kind of supply for the treatment might be more efficient: via solid food for dissolving or provided liquid to the stomach, inhalation, rectal, injection, and transdermal.
For future progressing, extended investigations are recommended to clarify unknown compounds and to distinguish between original and metabolized compounds. Quantity and quality of the known ingredients have to be specified.
Nevertheless, in this work, we made a step forward in identifying the complexity of ingredients and could provide suggestions in which direction to lead next investigational steps, in order to gain more profound knowledge to develop a natural and simple treatment path for preventing or curing Alzheimer´s disease and other brain maladies.