Establishing the Taxa, Functional prole, and in-silico Ayurvedic Remedy of Microbiota implicated in West Nile Fever

West Nile fever causing microbiome is taken in this work. Culex nigripalpus mosquito is the causative factor for West Nile Virus. Using Metatranscriptomic sequencing, identied the taxa and functional prole of the microbiome is identied. Again, the receptor genes involved in West Nile fever is taken and using computer aided drug design, the novel ligands from Ayurvedic medicinal plants Ginkgo biloba, Uncaria tomentosa, Lycoris radiate and Glycyrrhiza glabra. Further, in-vitro and in-vivo studies can be done on the selected ligands to prove their eciency as drugs for the disease

Next, using FASTQ INTERLACE tool [18] paired end FASTQ reads from two separate les were joined.
MetaPhlAn tool [19] was used for pro ling the composition of microbial communities (Bacteria, Archaea and Eukaryotes) from our microbiota.
Krona tool [20,21] was used to visualize the results of a metagenomic pro ling as a zoomable pie chart and GraPhlAn tool [22] for visualizing high-quality circular representations of taxonomic and phylogenetic trees.
Further, HUMAnN [23] pipeline was used for e ciently and accurately pro ling the presence/absence and abundance of microbial pathways in our microbiota.
Next, using the genes present in our microbiota, their 3d structure was modeled using SWISS-MODEL [8].
Phyto-compounds were downloaded from PUBCHEM.
Using, molinspiration software [24], following the principles of Lipinski's rule of ve, phytocompounds were selected for docking.

Results And Discussion
Metagenome, having accession number SRR10017187, for West Nile virus was downloaded from SRA database.
As, per Per base sequence quality results of FASTQC and MultiQC, the sequence quality is not good hence we go ahead with trimming the sequence.
CUTADAPT tool [27] is used for trimming. It nds and removes adapter sequences, primers, poly-A tails, and other types of unwanted sequence from our data.
It searches for the adapter in all reads and removes it when it nds it. Further, sequence quality of the cutadapt output is checked using FASTQC and MultiQC and it is found within the range.
SortMeRNA tool removes any reads identi ed as rRNA from our dataset. Fastq Interlace tool joins paired end FASTQ reads from two separate les. Taxonomic pro ling [28] was done using MetaPhlAn tool (Fig. 1, Table 1). The output is visualized using Krona and Graphlan (Fig. 2). After generation of taxonomy, we move to functional information of our microbiome. Functional information of the above microbiome community [28] was done using HUMAnN pipeline (Table 2). Next, from the gene family information, we obtain the functional information of our microbiome using Superfamily server. The Functional information of 1st ve families from Normalized gene families as detected by Superfamily (HMM library and genome assignments server) is given below (Fig. 3).

Structure based drug designing of West Nile Fever
Since, West Nile feveris a mosquito-borne disease, we further go ahead towards designing novel drug for the disease. From the MetaPhlAn: Bowtie2 output we get the gene ids. Corresponding gene receptors are taken from NCBI for our work (Table 3). Homology modeling Homology modeling of the above receptors are done using SWISS-MODEL server. The receptor model and corresponding ramachandran plot results are given in Fig. 4. Template used for modeling is given in Table 3.
Ayurvedic Medicinal plants Ginkgo biloba, Uncaria tomentosa, Lycoris radiate and Glycyrrhiza glabra are traditionally used to treat many diseases, such as respiratory disorders and fever. The potency of their phytocompounds in treating West Nile Fever is studied here.

Conclusion
The taxonomy and functional information of West Nile fever microbiome are identi ed. Again, as per docking studies and ADME analysis it is seen that phytocompounds Ginkgolide A, Ginkgolide B, Luteolin and Protocatechuic acid from Ginkgo biloba can be potential ligands for the receptors implicated in West Nile Fever. Again, phytocompounds Liquiritin, Cortison and Chlorozotocin from Glycyrrhiza glabra can be potential ligands for the receptors implicated in   Swiss-model generated receptor models with their ramachandran plot