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\begin{document}

\title{18S rDNA as a tool for molecular characterization of mosquito species
from various regions within Limpopo.}



\author[1]{Mzwandile Hadebe}%
\author[1]{Moses Okpeku}%
\affil[1]{University of KwaZulu-Natal}%


\vspace{-1em}



  
  \date{June 10, 2024}


\begingroup
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\selectlanguage{english}
\begin{abstract}
Anopheles mosquitos are the primary vectors for the rapid spread of
malaria in Limpopo, South Africa, negatively impacting all malaria
elimination agenda; particularly for a country with vector control as
one of the major malaria elimination strategies. The implementation of
vector control strategies, however, depends on the accurate
identification of mosquito vectors, which has been lacking in Limpopo as
a result of earlier studies that mainly relied on morphological
identification of vectors, which has numerous drawbacks that lead to
misidentification of mosquitoes, thus resulting in the development and
assignment of ineffective control strategies. All this together set back
elimination strategies and programs. The present study therefore aimed
to molecularly identify mosquitoes collected from various regions within
Limpopo province. This was accomplished by examining genetic composition
of mosquitos from different regions within Limpopo province, using
molecular genetics techniques such as 18S rDNA-based PCR analysis, 18S
rDNA sequencing, etc. This investigation was successful since 18S rDNA
was able to identify every one of the 42 mosquito samples that were
analysed, revealing that the samples belonged to 7 different Anopheles
species and the majority of the species were molecularly demonstrated to
have been misidentified morphologically. The outcomes of the molecular
analysis, which involved comparing the query sequences to the sequences
in GenBank, were supported by the close relationship among mosquitoes of
the same species in maximum likelihood trees and the presence of high to
100\% bootstrap support values, giving confidence to conclude that
mosquitoes of the same species under study are genetically related. Due
to a number of constraints covered in this study, morphological
identification of mosquitoes is prone to misidentification of species,
hence genetic characterization is recommended to be used as a
confirmatory approach in the identification of the species.%
\end{abstract}%



\sloppy


\textbf{18S rDNA as a tool for molecular characterization of mosquito
species from various regions within Limpopo.}

\textbf{Mzwandile Thabani Hadebe\textsuperscript{1} and Moses
Okpeku\textsuperscript{1}*}

\textsuperscript{1}Discipline of Genetics, School of Life Sciences,
University of KwaZulu-Natal, Westville, Durban 4000, South Africa.

*Corresponding Author:\emph{okpekum@ukzn.ac.za}.

MH:\emph{hadebemzwandile160@gmail.com}.

MO: \emph{okpekum@ukzn.ac.za}.

\textbf{Abstract}

\emph{Anopheles} mosquitos are the primary vectors for the rapid spread
of malaria in Limpopo, South Africa, negatively impacting all malaria
elimination agenda; particularly for a country with vector control as
one of the major malaria elimination strategies. The implementation of
vector control strategies, however, depends on the accurate
identification of mosquito vectors, which has been lacking in Limpopo as
a result of earlier studies that mainly relied on morphological
identification of vectors, which has numerous drawbacks that lead to
misidentification of mosquitoes, thus resulting in the development and
assignment of ineffective control strategies. All this together set back
elimination strategies and programs. The present study therefore aimed
to molecularly identify mosquitoes collected from various regions within
Limpopo province. This was accomplished by examining genetic composition
of mosquitos from different regions within Limpopo province, using
molecular genetics techniques such as 18S rDNA-based PCR analysis, 18S
rDNA sequencing, etc. This investigation was successful since 18S rDNA
was able to identify every one of the 42 mosquito samples that were
analysed, revealing that the samples belonged to 7 different
\emph{Anopheles} species and the majority of the species were
molecularly demonstrated to have been misidentified morphologically. The
outcomes of the molecular analysis, which involved comparing the query
sequences to the sequences in GenBank, were supported by the close
relationship among mosquitoes of the same species in maximum likelihood
trees and the presence of high to 100\% bootstrap support values, giving
confidence to conclude that mosquitoes of the same species under study
are genetically related. Due to a number of constraints covered in this
study, morphological identification of mosquitoes is prone to
misidentification of species, hence genetic characterization is
recommended to be used as a confirmatory approach in the identification
of the species.

\textbf{Keywords} : \emph{Anopheles} , Multiple Alignment sequencing,
Phylogenetic construction, 18S rDNA, Genetic variation.

\textbf{Introduction}

\emph{Anopheles} mosquitoes are essential vectors in the distribution of
the malarial parasite, \emph{Plasmodium} , hence monitoring mosquito
populations is a crucial factor in predicting malaria risk in a
geographic~region of interest. The number of mosquito species is
estimated to be 3500, and they are divided into 41 genera (Zheng, 2020).
Anopheles, Aedes, and Culex are three of these 41 genera that are
thought to be crucial in the spread of human illness caused by
mosquitoes (Adugna et al., 2021). Of the 530 species of\emph{Anopheles}
, only 30 to 40 naturally spread malaria (Nicoletti et al., 2020).
Various Anopheles mosquito species have been found to prefer distinct
habitats; thus, the \emph{plasmodium} parasite is spread by different
Anopheles species depending on geographic locations (Nicoletti et al.,
2020).

According to Adugna et al., (2020), identification of
\emph{Anopheles}species is crucial since each species has a different
treatment or preventative strategy. However, identification of
\emph{Anopheles}mosquitoes in Limpopo has mainly concentrated on
morphological characterization, which is likely to misidentify
\emph{Anopheles}species due to high similarity of phenotypic features
(Jones et al., 2021), leading to assignment of certain insecticides or
treatment to incorrect \emph{Anopheles} species which may be the reason
why some insecticides do not kill some Anopheles mosquitoes present in
the geographic region of interest. As a results, previous studies found
it more convenient to confirm morphological characterisation with
molecular characterization through studying genetic diversity of
\emph{Anopheles}mosquito species present in the area of interest.
Geneticists predominantly believe in molecular characterization since it
employs extremely precise molecular procedures such as PCR, Agarose gel
electrophoresis, DNA sequencing, and so on, which employ very sensitive
components such as genetic markers. Genetic markers are DNA sequences
with known positions on chromosomes. They play crucial role in the study
of populations, cell identification, as well as species classification
(Safdar, 2011).

One of the genetic markers of interest employed in this study's
molecular analysis of the \emph{Anopheles} mosquito species is 18S
ribosomal DNA (18S rDNA). According to Carranza et al., (1996), all
prokaryotic and eukaryotic cells use rDNA~as a critical component of
their protein production machinery. Due to its high conservation among
species and the presence of variable regions, 18S rDNA has been
frequently employed for identifying and assessing the genetic~diversity
of~eukaryotes (Kounosu et al., 2019). This sequence conservation is
thought to represent functional limitations on the molecules necessary
for best translational effectiveness. According to Rackevei et al.,
(2022), V1 to V9 variable regions of 18S rDNA are commonly used in
biodiversity studies. Despite being a member of a multigene family, the
18S rDNA has undergone concerted development to keep all of its copies
homogenous(Carranza et al., 1996). This marker is also being used to
determine phylogenetic connections between living organisms (Carranza et
al., 1996). There are lot of reason for this maker to be used for
studying phylogenetic analysis and those reason are detailed in a review
by Woese (1987); Sogin (1991); and Adoutte et al., (1993).

PCR, Agarose gel electrophoresis, Multiple sequence alignment (MSA), and
phylogenetic analysis were used to examine the genetic variance of
distinct mosquito species. Genetic variation is simply the variance in
genomic DNA~sequence~between individuals within a community/same species
(Al-Koofee et al., 2020). PCR was mainly utilized to amplify the areas
of interest, and the existence of the target region was determined by
agarose gel electrophoresis. Following Agarose gel electrophoresis,
samples must be further analyzed with MSA. This method is used to
determine the evolutionary links and common patterns among target genes
(Sofi et al., 2022). According to a genetic concept, MSA is the
alignment of at least three genomic~DNA sequences of same length.
Computational methods are used to produce and analyze these alignments
(Sofi et al., 2022).Identification of a novel protein members after
comparing them to related sequences is an additional role played by MSA
(Shukla et al., 2022). Since~further analysis of research~is dependent
on the outcome of the MSA, the accuracy of the MSA plays a crucial role.
Consequently, creating trustworthy and accurate MSA tools will always be
a worthwhile endeavor(Shukla et al., 2022). These techniques, along with
targeted genetic markers, are considered to be exceedingly sensitive and
very specific, which is why they were chosen to measure mosquito
diversity and give trustworthy findings.

\textbf{Material and Methods}

Collection and processing of samples.

A total of one hundred and thirty-four (134) mosquito samples were
utilized in this investigation. These specimens were obtained from
different regions in Limpopo province including Masisi, Mutale,
Tshivaloni, Xikukwani, Makoxa, Thomo, Seloane, Domboni and Musunda as
shown in figure 1 and these regions have a unique geographic coordinate
(Table 1). Samples were obtained using two different techniques: pits or
larvae collecting methods. Stored samples acquired by the Limpopo
Malaria Institute were transferred safely and securely from Limpopo to
the University of KwaZulu-Natal and stored in the freezer at Genetic
Laboratory 3, Dr Moses's laboratory before DNA extraction. In order to
prevent DNA mixing in case that mosquitoes were able to feed prior to
collection, the abdomen was removed from all samples. Only the legs,
head, and thorax were utilized for DNA extraction. The abdomen was
removed while the specimen was viewed under the microscope. PCR was used
to amplify regions of interest where the successful amplification was
confirmed by presence of either one or more bands per tube. The majority
of tubes contained a pool of three mosquitoes, however some tubes
contained fewer or more than three mosquitoes. The main purpose of this
was to simply determine whether the quantity of mosquitoes had any
impact on the concentration of DNA after extraction. In this
investigation, a total of 42 tubes containing pooled mosquitoes were
employed. According to the absorbance at 260/280, which was at least 1.6
for all tubes, the DNA produced was of excellent quality.

\textbf{Figure 1:} South Africa Map showing different geographic areas
where mosquito samples were collected.

\textbf{Table 1} : Different regions of collection and their
corresponding geographic coordinate

DNA extraction

Some of the samples that were gathered were undocumented, and those
samples were utilized to evaluate the best DNA extraction tool. The
first kit used to extract DNA from a pool of mosquitoes was the Promega
Wizard\selectlanguage{ngerman}® Genomic DNA Purification Kit, but this kit produced very little
DNA yield as it employs a micro pestle, which doesn't crush mosquitoes
very effectively. However, the beads utilized by the Zymo-Research
Quick-DNA Tissue/Insect Miniprep Kit for crushing mosquitos properly
crushed the mosquitos, resulting in the best DNA yield suitable for PCR.
As a result, the Zymo-Research Quick-DNA Tissue/Insect Miniprep Kit was
employed for DNA extraction in this investigation. As previously stated,
DNA was obtained from the legs, thorax, and head of mosquitos, with the
abdomen left out to avoid DNA mixing if mosquitos were allowed to feed
before collection. In this study, 134 mosquito samples were examined;
however, mosquitos were pooled, with the majority of tubes holding a
pool of three mosquitos, resulting in 42 tubes containing diverse DNA
samples. DNA was successfully extracted according to manufacturer's
instruction; no modifications were made. The quantity and purity of the
extracted DNA were evaluated using a NanoDrop 2000 UV Visible
Spectrophotometer, and the DNA was then kept at -20 C until it was
utilized for genetic analysis by polymerase chain reaction (PCR).

Amplification of 18S rDNA gene using PCR .

The polymerase chain reaction was employed to amplify the 18S rDNA
region in DNA obtained from pooled mosquitos. Primers that were utilized
to amplify 18S rDNA were; Forward primer 5' GAG GGA GCC TGA GAA ACG GCT
AC 3' and Reverse primer 5' CCT TCC GTC AAT TCC TTT AAG TTT C 3' (Beebe
et al. 1996). The Bio-Rad T100 Thermal Cycler was employed for PCR
amplification. A 25\selectlanguage{greek}µ\selectlanguage{english}L PCR reaction was set up as follows: 12.5\selectlanguage{greek}µ\selectlanguage{english}L of
Dream Taq Master Mix, 1\selectlanguage{greek}µ\selectlanguage{english}L of each primer (1.9 \selectlanguage{greek}µ\selectlanguage{english}M concentration), 1 \selectlanguage{greek}µ\selectlanguage{english}L of
genomic DNA, and 9.5\selectlanguage{greek}µ\selectlanguage{english}L of nuclease-free water. Since the conditions
often employed by prior research didn't work well for the primer, it
needed to be optimized. As a result, 62.2\selectlanguage{ngerman}°C annealing temperature
yielded the best results, thus the following PCR conditions were used to
amplify 18S rDNA: Denaturation: 94°C for 4 minutes, 1 cycle; annealing:
95°C for 1 minute, 62.2°C for 1 minute, and 72°C for 1 minute, 35
cycles; final extension: 72 C for 7 minutes, 1 cycle; hold: 4 C.

Agarose gel electrophoresis and viewing of amplified PCR products of 18S
rDNA.

Availability of target DNA region was checked using agarose gel
electrophoresis. A 1.5\% agarose gel stained with EtBr was used to run 5
\selectlanguage{greek}µ\selectlanguage{english}L of each sample. This type of agarose gel was made by just mixing 100
mL of 1X TAE buffer (Bio Concept, Switzerland) with 1.5g of agarose
powder (Cleaver scientific, United Kingdom) in a 1000ml beaker. The
powder was dissolved in a buffer by heating the mixture in the microwave
for~approximately three minutes. The mixture was then allowed to cool
before being poured into a gel casting tray with a comb in~~to produce
wells. Then after, the mixture was allowed solidified to form a gel that
was used to run 5\selectlanguage{greek}µ\selectlanguage{english}L of PCR product in electrophoresis. A hundred bp
(100bp) molecular weight marker (New England Biolabs, China) was
employed as a reference for comparing DNA fragment sizes of PCR
products. One \selectlanguage{greek}µ\selectlanguage{english}L of the molecular weight marker was combined with two \selectlanguage{greek}µ\selectlanguage{english}L
of 6X purple dye. This dye aided in the visualization of a molecular
weight marker. Electrophoresis was performed at 100 volts for 60 minutes
utilizing Enduro gel XL electrophoresis system (Labnet, United States of
America). The ChemiDoc MP imaging machine (Bio-Rad, United States of
America)~was used to visualize the DNA bands in the gel.

Phylogenetic Analysis.

The 18S ribosomal DNA mosquito samples were sent to Stellenbosch for
sequencing. The base calling and trimming were done utilizing FinchTV.
The sequences were aligned using the Clustal W multiple alignment
function of the BioEdit program, version 7.2.5. MEGA version 6 (Tamura
et al., 2013) was used to create phylogenetic trees using the maximum
likelihood (ML) technique.

\textbf{Result}

The only mosquito genera investigated in this research were
\emph{Culex}and \emph{Anopheles} , although there is one species of
mosquito that does not belong to any of the three discovered mosquito
genera (\emph{Anopheles} , \emph{Aedes} , and \emph{Culex} ); this newly
morphologically recognized species is known as \emph{Dimelion} . These
different species of mosquitos were collected at different locations
within Limpopo province (Figure 1). Among mosquito samples
collected,\emph{Anopheles} genera was more prevalent over the other
genera,\emph{Culex} . Only six mosquito samples were \emph{Culex} of the
134 species collected, and they were all obtained from Makoxa. 128
Samples belonged to \emph{Anopheles} genera and were collected from
different regions in Limpopo (Table 2.). After Polymerase chain reaction
amplification, DNA for different samples was run in a 1.5\% agarose gel
electrophoresis. To amplify samples Tube1- Tube42, which were labelled
as T1, T2, etc, 18S r DNA was utilized. As seen in table 3, tubes (T1
-T42) contained a pool of mosquitos of the same species. The marker of
interest previously mentioned (18S rDNA) produced varying amplicon sizes
(900bp -- 910bp) after running them on agarose gel electrophoresis as
shown in gel images in figure 2. When repeated for the
3\textsuperscript{rd} time 18S rDNA successfully amplified T26 which
didn't amplify at first place. 5ml of PCR mixture was added into each
well for each sample and ran at 100 volts for 60 minutes and ChemiDoc
imaging system was used to view DNA profiles. A 100bp ladder stained
with purple dye was used as a reference to estimate sizes of PCR
products. Prior to sequencing, amplicons were purified to eliminate any
residues that may cause interference if not removed, such as
non-specific bands.

\textbf{Table 2.} Various mosquito species, their numbers, and the area
where they were collected in South Africa, Limpopo province.

\textbf{Table 3.} Pools of mosquito species per Tube ( T1-T42) and their
corresponding geographic locations and coordinates.

\textbf{Figure 2.} T1-T42 mosquito samples' 18S rDNA amplification
profiles. Lane MW indicates a 100bp DNA ladder (New England Biolabs,
China). It is also known as molecular weight marker (MWM). It was
basically used to estimate PCR product sizes. Lane NC symbolizes the
negative control. The obtained PCR products were then run at 100 volts
on 1.5\% agarose gel with 1X TAE running buffer. To obtain optimal
separation of the DNA fragment on the agarose gel, the DNA agarose gel
electrophoresis was allowed to run for~60 minutes. In certain mosquito
species, the 18S rDNA amplicon is 900 bp in size, whereas in others, it
is 910 bp. As a result, some tubes contained two bands (900 bp and 910
bp), showing that the pooled mosquitoes were not all from the same
species.

The outcomes of multiple sequence alignment (MSA) in figures 3 do not
show any discernible variation in the 18S rDNA region among the mosquito
species under investigation. By comparing sequences found in this study
with those on Genbank, this study was able to determine whether or not
the Limpopo malaria institute's morphological identification of mosquito
species was accurate. Even though there are some gaps in the query
sequences after alignment, they display little to no variation compared
with the reference sequences. However multiple sequence alignment
wouldn't give reliable results alone, hence phytogenic diagram of 18S
rDNA (Figure 4) was constructed to support MSA results by showing
relationship that exist among the species of mosquitos under
investigation. Multiple alignment sequences and phylogenetic analysis
proved that the ''\emph{Dimelion} '' species of mosquito, which was once
believed to be an entirely novel species identified based only on its
morphology, is in fact \emph{An.gambiae} . An additional piece of
evidence that \emph{Dimelion} is not a new species of mosquito
discovered in Limpopo, but rather \emph{An.gambiae} , is that its
sequence revealed a 99.65\%~identity with \emph{An.gambiae} \_OM350318.1
and no \emph{Dimelion} species was observed in hits after blasting the
query sequence. \emph{An.gambiae} was not the only species that was
mistakenly recognized morphologically; nonetheless, molecular
identification disapproved other species' names that were given to them
by morphological procedures (Table 3). These mosquito species are
believed to have been misclassified based on morphology because, when
their 18S rDNA sequences were blasted, they displayed high percentage
identities to other mosquito species, but the name assigned to them
based on morphological features did not appear in possible hits.
However, some sequences (T25\_18S rDNA, T26\_18S rDNA, and
T28\_18Sr\_DNA) did not match any sequence~when blasted on NCBI blast
and were too divergent from other sequences to be included in the
construction of a phylogenetic tree. As a result, they were not included
in the MSA or phylogenetic construction. Five sequences were too short
to be aligned with other sequences, leading in an error while attempting
to match them with other sequences; hence, they were omitted from MSA.
These sequences include T7\_18S rDNA (\emph{An.gambiae} ), T17\_18S rDNA
(\emph{An.gambiae} ), T33\_18S rDNA(\emph{An.listeri} ), T36\_18S rDNA
(\emph{An.pretoriensis} ), T42\_18S rDNA (unknown).

Looking at the phylogenetic tree for 18S rDNA in figure 4, the existence
of an elevated percentage of bootstrap support values, some of which are
100\%, indicates that the data in table 3 is accurate. As a result, 18S
rDNA phylogenetic analysis verified that the information acquired by
comparing query sequences with reference sequences (Table 3) on Genbank
through blasting is valid, implying that a large number of mosquitos
were mistakenly classified based on their morphological traits. The 18S
rDNA phylogenetic tree (figure 4) shows that \emph{tsetse flies} which
were used as outgroup are the most recent common ancestor and that two
major clades diverged from the 95\% node as a common ancestor. A high
percentage of bootstrap support values guarantees that each of the
involved species is closely linked. Regardless of what morphological
traits ~suggests, species within the same clade~and closer to one
another are thought to be genetically linked. Despite the six species
reported by morphological identification, genetic identification
confirmed only seven mosquito species and one non-mosquito
species\emph{(Diaphorina} ) among the samples collected.~These mosquito
species include \emph{An.gambiae} , \emph{An.sundaicus} ,
\emph{An.melas} ,\emph{An.coluzzii} , \emph{An.merus} ,
\emph{An.maculipalpis} , and\emph{An.funestus} . The phylogenetic tree
(Figure 4) shows that mosquitos of the same species are closely related,
suggesting that molecular identification was accurate. However, there
are notable exceptions of species that are closely related to various
other species due to some~reasons that are highlighted in the discussion
section.

\textbf{Figure 3} : DNA bases of Multiple sequence alignment of 18S rDNA
targeted in various species of mosquitoes collected from Limpopo. To
generate alignment, the BioEdit program was utilized in conjunction with
the Clustal W multiple alignment tool.

\textbf{Table 4} : Molecular characterisation of different mosquito
species through database searching and availability of 18S rDNA
sequences.

\textbf{Figure 4:} Phylogenetic reconstruction of the various species of
mosquitos using the 18S rDNA gene (900bp). Mega X software was used to
generate phylogenetic tree, whereby the Maximum likelihood method
inferred by kimura 2 parameter model after 100 replicates was utilized.
Sequences from the present study start with letter ``T'', T1-T41 .
Bootstrap supports values are shown in percentage (\%) , and the scale
for the above phylogenetic tree is 0.2.

\textbf{Discussion}

The present investigation portrays genetic characterisation of several
mosquito species that have been morphologically defined by the Limpopo
Malaria Institute. According to morphological characterization, the
species under examination are from the \emph{Anopheles} and
\emph{Culex}subfamilies, and there has never been a study like this one
in Limpopo. The main aim of this investigation was just basically~to
confirm or disprove Limpopo Malaria Institute's morphological
categorization of mosquito species, as well as to investigate the
accuracy of genetic markers in identifying closely related species. The
Limpopo Malaria Institute employed the two techniques of collecting
mosquitos indicated in 3.2.1 (pits or larvae), and after collection,
they utilized standard morphology-based taxonomy approach to identify
mosquitos morphologically, and two genera (\emph{Anopheles} and
\emph{Culex} ) were detected. As previously demonstrated (Table 2), the
majority of species identified by morphological features belonged to
\emph{Anopheles} (102 species), only 6 were classified as Culex, and 26
were thought to be new species (\emph{Dimelion} ) that had not been
classified previously, however molecular characterization disproved
that.

Gel images show positive results for all samples when the 18S rDNA
region were amplified; however, some samples displayed multiple bands
per sample, which was thought to be caused by the presence of various
species in the pool of mosquitos. However, sequencing only produced one
sequence per sample, i.e., one sequence per sample for 18S rDNA marker,
with no varying sequences per sample as an indication of various species
present in a pool of mosquitoes. Therefore, gel pictures that displayed
more than one DNA~band per well may be an indication that non-specific
bands have been amplified (Bovo et al., 1999). DNA barcoding using 18S
rDNA was able to identify species that were mistakenly classified
morphologically. The occurrence of high percentage identity (81\%-100\%)
between query and reference sequences on GenBank is evidence of
successful molecular characterisation and validation of morphological
identification of distinct mosquito species (Tables 3.3). Some sequences
of samples that were~morphologically described as~\emph{An.rufipes}
~(T25, T26, and T28)~matched no sequence on~GenBank, suggesting that
these are new haplotype of \emph{An.rufipes} ~found by the current study
using 18S rDNA.

The results reported in this study~(Table 3) demonstrates that many
samples were incorrectly categorized morphologically. This was proven by
molecular~analysis, which makes use of highly specific molecular
techniques (Wilson et al., 2000). Damage to essential distinguishing
features, human error, the occurrence of novel or cryptic species, the
presence of species showing overlapping or unreported traits, and
intraspecific morphological changes are all potential causes of
misclassification of mosquito species (Zhang et al., 2022). Despite the
fact that the majority of mosquito species were incorrectly classified
morphologically, Molecular characterisation using 18S rDNA revealed that
certain species were accurately identified. The identification of
samples T5, T8, T9, T18, T19, T20, and T21 as \emph{An.gambiae} by 18S
rDNA and morphological~characterization~indicates that the morphological
characterization of these species was valid. Individual pools of
mosquito species were represented by highly supported clades, with high
percentages of bootstrap values up to 100\%, validating the
morphological identification of diverse mosquito species investigated.

According to morphological characterization of mosquito species, six
different species of mosquitos were obtained; however, molecular
characterization by 18S rDNA demonstrated that there were actually seven
different mosquitos studied plus one non-mosquito species, and among
these species of mosquitos, some had been overlooked by morphological
characterization and others were mischaracterized (Table 3). These eight
species found by molecular characterisation comprise species that were
mistakenly categorized by morphology as well as species that were
verified to be appropriately classified morphologically by molecular
analysis. Seven species of mosquitos found by molecular characterization
using 18S rDNA includes \emph{An.gambiae} , \emph{An.sundaicus}
,\emph{An.melas} , \emph{An.culuzzi} , \emph{An.merus}
,\emph{An.maculipalpis} , and \emph{An.funestus} . In addition to these
species, 18S rDNA also discovered a non-mosquito species
,\emph{Diaphorina} , which was thought to be \emph{Culex} species, and
this serves as a proof that morphological identification alone cannot be
trusted when it comes to characterization of various species of
mosquitos. Unknown species (T42) were recognized by 18S rDNA as\emph{An.
gambiae} . The 18S rDNA based molecular characterization of samples that
were not documented , T42(Unknown), discovered that the pool of
mosquitos in this sample belong to \emph{An.gambiae} and this was
supported by a very high percentage similarity of 18S rDNA query
sequence to MG753768.1 (\emph{An.gambiae} ) reference (81.32\%) and a
being relatively small e value (3e-95). The accuracy of 18S rDNA
characterization results (Table 3) was supported by a close relationship
that exist between mosquitos of the same species and their reference
sequences in the phylogenetic construction (Figure 4)

In a phylogenetic tree, species in the same clade and near to one
another are genetically connected, i.e., the closer the species are to
one another, the closer their genetic relationship is (HAMZAOLU et al.,
2017). Other studies made an effort to modify the aforementioned claim
in order to conform to the world of science; they claimed that two
species are more connected if they share a most recent common ancestor
and less related if they share a less recent common ancestor (Lo et al.,
2003; Gregory,2008). Furthermore, the presence of a node with a high
bootstrap value close to 100\% suggests that the species that diverged
from that node, also known as a common ancestor, are closely related to
one another and that their genetic makeup is identical or contains very
little variation. Since previous studies have shown that a very high
bootstrap value up to 100\% gives researchers confidence in concluding
that particular species are siblings. Hence, high bootstraps support
values in the 18S rDNA phylogenetic construction and relatively small
scale (0.2) imply a close relationship between the species being
studied. Phytogenic trees (Figures 4) investigated variation well
because it shows that mosquitos of the same species are more closely
related, sharing clades and most recent common ancestors.

It is evident from a detailed examination of the 18S rDNA phylogenetic
tree that mosquitoes belonging to the same species are genetically
related to one another. This tree diagram demonstrates two significant
branches that diverged from the 95\% node that was determined to
represent the most recent common ancestor of all the species analyzed in
the current study, and that divergence resulted in the formation of two
major clades. \emph{An. gambiae} species are found to be closely linked
to one another in the top clade, and their tight relationship is
supported by the occurrence of a high bootstrap value of 99\% where all
of these species diverged from. Regardless of An.maculipalpis being
closely related to each other , but their divergence from a common
ancestor with \emph{An.gambiae} , supported by 85\% bootstrap value,
provides evidence that \emph{An.maculipalpis} and \emph{An.gambiae} are
genetically linked. Additionally, this tree diagram was able to show
that \emph{An. sundaicus} are related to each other, \emph{An. melas} as
a reference species, and \emph{An.maculipalpis} , however they are
indeed distantly related to \emph{An.gambiae} . \emph{Diaphorina} , a
non-mosquito species, was demonstrated to be genetically~linked
to\emph{An.gambiae} , \emph{An.maculipalpis} , \emph{An. melas} ,
and\emph{An.sundaicus} by sharing a clade and diverging from a common
ancestor. This relationship is supported by a 100\% bootstrap support
value. Looking at the bottom branch, there are \emph{An. gambiae}
and\emph{An.maculipalpis} species that are closer to one another and
their~reference sequences, providing proof that these species are in
fact \emph{An.gambiae} and \emph{An.maculipalpis} . These species,
however, are distantly related to the same species in the upper clade,
and the occurrence of these species in various geographical locations
may be the cause of this variability (Marcus et al., 2017). There is
also the presence of \emph{An.funestus} reference species in this clade,
which is distantly linked to T22 \emph{An.funestus} from this study, and
this variation might be attributable to a variety of factors, including
the one~previously stated,~mutation, geneflow, or sexual reproduction
(Barton, 2010 ). This reasoning also applies to other species that are
distantly linked to their phylogenetic references, such
as\emph{Diaphorina} , \emph{An.gambiae} , and others. This information
combined offers a~proof that 18S rDNA molecular identification was more
accurate than morphological identification, as it can seen that the
species stated to be linked by molecular characterisation appear to be
connected in the phylogenetic tree too (Figure 4).

It is possible that there is still a significant danger of malaria
transmission in Limpopo given the presence of so many
distinct\emph{Anopheles} species in this province. According to 18S
rDNA, this study has discovered a possibly novel haplotype of the
\emph{Anopheles}species (T25, T26, and T28 and T32). The main reason
behind this fact is that the sequences for these sample show no match
when compared to sequences on Genbank. \emph{Anopheles} species are
constantly being discovered via the use of molecular methods; for
example, new species of\emph{Anopheles nuneztovari} have been discovered
in Brazil (Scarpassa et al., 2016). Based on the results, it can be
inferred that there is a significant and widespread group of mosquitoes
in all of the Limpopo regions that are close to the coast and along the
border (Table 1). This is in line with earlier research which showed
that the majority of Anopheline mosquito species are found in temperate
and tropical climates (Sch\selectlanguage{ngerman}äfer et al., 2001). All this together causes a
rapid spread of malaria in Limpopo and contributes to a rise in malaria
cases and malaria-related deaths. According to earlier research,
\emph{An. funestus} , \emph{An. arabiensis} , \emph{An.pretoriensis}
,\emph{An.quadriannulatus} , and \emph{An.gambiae} are the only species
of Anopheles present and in charge of transmitting malaria in South
Africa, specifically in Limpopo (Burke et al., 2019; Dahan-Moss et al.,
2020; Braack et al., 2020; Dahan et al., 2020). However, molecular
characterisation carried out in the present study discovered numerous
more \emph{Anopheles} species that were assumed to be missing in South
Africa, including as \emph{An.sundaicus} , \emph{An.melas}
,\emph{An.coluzzii} , \emph{An.merus} , \emph{An.maculipalpis}
,\emph{An.triannulatus} , and \emph{An.darlingi} . These Anopheline
mosquito species may have been imported to South Africa by immigrants
via luggage or flights from various regions of the world. The rising
incidence of arbovirus (malaria)~epidemics in Limpopo, and the rapid
propagation of such diseases, as well as high volume~of the public
health consequences (Charrel et al., 2007; Enserink, 2007; Semenza et
al., 2014), have prompted multiple calls for South Africa to practice
greater vigilance regarding arboviruses, as well as an associated need
to comprehend the population status of existing or potential vector
mosquitoes (Cornel et al., 2018). Hence prior research investigated the
diversity of mosquito species since some scientists observed that
mosquitos are treated based on the type or kind of species found in a
specific location. Presence of these various species as vectors of
malaria which were not known to be present in Limpopo really contributed
to increasing cases of malaria in Limpopo due to the fact that they are
given wrong treatment. The necessity of understanding the genetic makeup
of different mosquito species is demonstrated by the information
presented here, and it also made it~clear that morphological
characterisation of mosquito species alone does not provide trustworthy
findings due to its numerous restrictions and lack of specificity.

\textbf{Conclusion}

This study demonstrated that \emph{Anopheles~} mosquito species
recognition may be accomplished with success using molecular
characterization. DNA barcoding results, which utilized the genetic
marker 18S rDNA, were equivalent to the morphological identification of
some species and also allowed for~identification~ of~morphologically
misidentified species. It is crucial to highlight that in situations
when conventional morphological classification was unsuccessful owing to
damaged specimens and unidentifiable characteristics, DNA barcoding
successfully identified~these~species. The newly discovered
sequence~could potentially be utilized as reference sequences in future
mosquito taxonomy investigations. The successful identification of
numerous mosquito species in this study will assist with malaria
research by determining the real and prospective danger of arbovirus or
parasite transmission, as well as providing fundamental knowledge for
vector surveillance and enhancing vector control strategies. In the
future, molecular~identification implementations should include
barcoding a greater number of species and incorporating other genetic
markers that improve the discriminatory strength of this identification
approach. DNA barcoding might also be used in conjunction with next
generation sequencing to identify huge numbers of mosquitos at
once,~considerably reducing the processing time required for species
characterization.

\textbf{Author Contributions}

Mzwandile Thabani Hadebe: Designed and drafted the manuscript -
Methodology, Software, Formal analysis, Investigation, Data curation.
Moses Okpeku: corrected the drafts and approved the final draft of the
manuscript.

\textbf{Acknowledgments}

I acknowledge the support of NRF (National Research Foundation) and SMRC
(South African Medical Research Council) for their contributions to this
research. I would also like to extend my gratitude to Mr George
Makhubela of the Malaria Limpopo Institute for his contribution with
sample collection.

\textbf{Funding Information}

This work was supported by NRF---PMDS22061523254

\textbf{Conflict of interest statement}

The authors declare no conflict of interest.

\textbf{Availability of data}

The data supporting findings of this manuscript are available within the
article

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\textbf{Hosted file}

\verb`Figure 1.South Africa Map showing different geographic areas where mosquito samples were collected..docx`  available at \url{https://authorea.com/users/764590/articles/743199-18s-rdna-as-a-tool-for-molecular-characterization-of-mosquito-species-from-various-regions-within-limpopo}

\textbf{Hosted file}

\verb`Figure 2. T1-T42 mosquito samples' 18S rDNA amplification profiles. Lane MW indicates a 100bp DNA ladder (New England Biolabs, China). .docx`  available at \url{https://authorea.com/users/764590/articles/743199-18s-rdna-as-a-tool-for-molecular-characterization-of-mosquito-species-from-various-regions-within-limpopo}

\textbf{Hosted file}

\verb`Figure 3. DNA bases of Multiple sequence alignment of 18S rDNA targeted in various species of mosquitoes collected from Limpopo..docx`  available at \url{https://authorea.com/users/764590/articles/743199-18s-rdna-as-a-tool-for-molecular-characterization-of-mosquito-species-from-various-regions-within-limpopo}

\textbf{Hosted file}

\verb`Fihure 4. Phylogenetic reconstruction of the various species of mosquitos using the 18S rDNA gene (900bp).docx`  available at \url{https://authorea.com/users/764590/articles/743199-18s-rdna-as-a-tool-for-molecular-characterization-of-mosquito-species-from-various-regions-within-limpopo}

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\verb`Tables.docx`  available at \url{https://authorea.com/users/764590/articles/743199-18s-rdna-as-a-tool-for-molecular-characterization-of-mosquito-species-from-various-regions-within-limpopo}\selectlanguage{english}
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