PHYLOGENETIC ANALYSIS, DRUG RESISTENCE PATTERN AND

PHYLOGENETIC ANALYSIS, DRUG RESISTENCE PATTERN AND

HYBRIDIZATION OF LIVER FLUKES IN LARGE RUMINANTS

ZIA UR REHMAN

2017-VA-33

A THESIS SUBMITTED IN THE PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE

OF

DOCTOR OF PHILOSOPHY

IN

PARASITOLOGY

UNIVERSITY OF VETERINARYAND ANIMAL SCIENCES,

LAHORE

2021

In the name of Allah, the most gracious, the most merciful

"Attainment of knowledge is a must for every Muslim”

"Seek knowledge from the Cradle to the Grave”

HADIS – E – NABVI

(PEACE BE UPON HIM)

To,

The Controller of Examinations,

University of Veterinary and Animal Sciences,

Lahore.

We, the supervisory committee, certify that the contents and form of the thesis submitted by Mr.

Zia ur Rehman, Regd. No. 2017-VA-33, have been found satisfactory and recommend that it to

be processed for evaluation by the External Examiner(s) for the award of the degree.

.

SUPERVISORY COMMITTEE:

Supervisor: ----------------------------------------------------------------

(Prof. Dr. Muhammad Imran Rashid)

Co-Supervisor: --------------- ------------------------------

(Dr. Umer Naveed Ch)

Member: ----------------------------------------------------------------

(Prof. Dr. Kamran Ashraf)

Member: ----------------------------------------------------------------

(Dr. Wasim Shehzad)

CONTENTS

DEDICATION --------------------------------------------------------------------------------- i

ACKNOWLEDGEMENTS ----------------------------------------------------------------- ii

LIST OF TABLES ---------------------------------------------------------------------------- iii

LIST OF FIGURES --------------------------------------------------------------------------- iv

SR. NO. CHAPTERS PAGE NO.

1. INTRODUCTION 1

2 REVIEW OF LITERATURE 4

3 MATERIALS ND METHODS 18

4 RESULTS 28

5 DISCUSSION 50

6 SUMMARY 56

7 LITERATURE CITED 58

I

DEDICATION

I

DEDICATE THIS HUMBLE EFFORT,

THE FRUIT OF MY THOUGHTS,

AND STUDY TO

MY

PARENTS, FAMILY AND TEACHERS WHO

INSPIRED ME

HIGHER IDEAS OF LIFE

II

ACKNOWLEDGEMENTS

Alhamdulillah, all praises to “ALLAH”, The Almighty, most Gracious, the most Merciful

and the Sustainer of the worlds, who sent us Holy Prophet “MUHAMMAD (Peace be

upon Him)” as a blessing for whole universe and the best teacher with the ultimate

source of wisdom “HOLY QURAN”.

I am very thankful to Almighty ALLAH, for blessing me with the opportunity to

work in a prestigious institute; University of Veterinary and Animal Sciences Lahore

under the supervision of Prof. Dr. Muhammad Imran Rashid (Director ORIC). I offer

my special and sincerest gratitude to my supervisor and my co-supervisor Dr Umer

Naveed Ch (Roslin institute, Scotland) for his supervision and constant support. His

invaluable, persuasive and sincere efforts, constructive comments and suggestions

throughout the experimental and thesis works have contributed to the success of this

research. Not forgotten, my appreciation to my Major member, Prof. Dr. Kamran Ashraf

(Chairman Department of Parasitology) and Dr. Qasim ali for their support and

knowledge regarding this research work. I am whole heartedly thankful to, Dr.

Muhammad Haroon Akbar Assistant Professor, Department of Parasitology, University

of Veterinary and Animal Sciences, Lahore and Rehman ullah

I would like to express my appreciation to my fellows especially Dr Mohammad

Sajid hasni who inspired me to join Department of parasitology.

Thanks to all my friends’ especially Dr Rehman ullah, Dr Mehboob Qasrani Dr

Shahid Farooqi, Dr Ghazanfar, Zia ul Rehman for their kindness and moral support during

my study. Thanks for the friendship and memories. I am also thankful to the Laboratory

staff of Parasitology Department of University of Veterinary and Animal Sciences

Lahore.

Last but not least, my deepest gratitude goes to my beloved father, my beloved

Mother, my beloved wife, my sisters, brothers, , my prince Ahmad Zia Kakar Mohammad

Zia Kakar my princess Wazhma Zia kakar and relatives for their endless love, prayers and

encouragement. Special credit goes to those who indirectly contributed in this research. Your

kindness means a lot to me. Thank you very much.

Zia ur Rehman Kakar

III

LIST OF TABLES

TABLE NO. TITLE PAGE NO.

2.1 List of research work done on speciation of Fasciola by using

different tools in ascending order 14

3.1 ITS-2 and mt-ND-1 primers. Primer sequences for the amplification of

Fasciola rDNA ITS-2 and mt-ND-1 21

3.2 Sequences of barcoded primers 23

4.1 Species identification of individual worms. From twenty-six

Fasciola population were performed 31

4.2 Profiles of Fasciola flukes used in this study 33

4.3 Diversity indices of F. hepatica populations in Pakistan based on

the nucleotide sequences of mt DNA genes 40

4.4 Pairwise fixation index (FST values) of mitochondrial genes

between F. gigantica populations from Buffalo and Goat 40

4.5 Genetic diversity estimation of mt-ND-1 haplotypes identified from

twenty populations of Fasciola gigantica in Pakistan 44

4.6 Diversity indices of F. gigantica populations in Pakistan based on

the nucleotide sequences of mt DNA genes 46

4.7 Pairwise fixation index (FST values) of mitochondrial genes

between F. gigantica populations from Buffalo and Goat 47

4.8 Diversity indices of Fasciola gigantica within haplogroup A based

on the nucleotide sequences of nad1 genes 49

IV

LIST OF FIGURES

FIGURE NO TITLE

PAGE NO

2.1 Zoological classification of Platyhelminthes 4

2.2 Life cycle of Fasciola 7

2.3 Microscopic examination of F. hepatica and F. gigantica 8

2.4 Comparison of Fasciola species along with hybrid 10

2.5 Main geographical spread routes followed by F.gigantica in post

domestication period 12

3.1 overall scheme of the metabarcoding sequencing approach using

Illumina MiSeq platform 19

4.1 Flukes examined macroscopically 28

4.2 Eggs of flukes examined under microscope 29

4.3

The maximum-likelihood tree was obtained from the BLAST

searched F. gigantica and F. hepatica rDNA ITS-2 and mt-ND-1

loci

30

4.4 Relative allele frequencies of twenty F. gigantica populations from

Punjab (A) and Balochistan (B) provinces of Pakistan 36

4.5 Split tree of twenty-six mt-ND-1 haplotypes generated from

twenty F. gigantica populations 37

4.6 Mitochondrial haplotypes detected from Pakistan 39

4.7 Network tree of twenty-six mt-ND-1 haplotypes sequenced from

twenty F. gigantica populations 42

4.8 Comparison of mitochondrial nad1 haplotypes with those from the

reference countries 48

1

Fascioliosis or fascioliasis is an important neglected worldwide disease of ruminant

livestock and humans. Fasciola spp. cause production losses of worth billion of dollar

annually in farm animals (Aghayan et al. 2019; Mungube et al. 2006). According to World

Health Organization, liver fluke cause food and water borne zoonoses in human estimated to

have above 180 million people at risk and 2.4 million people are infected (Haseeb et al. 2002;

Henok et al. 2011). The genus Fasciola comprises of two important species, Fasciola

gigantica and Fasciola hepatica (Mas-Coma et al. 2005). F. gigantica is mostly found in

tropical zone (Amor et al. 2011), while F. hepatica is found in temperate area (Mazeri et al.

2017). Overlap between these two species has been found in moderate temperature

(subtropical) regions with hybrid (intermadiate forms) (Ichikawa et al. 2010). By the

ingestion of contaminated herbage with infective metacercariae, the animal becomes infected

with liver fluke, and the parasite’s life cycle involves different snail species of Lymnaeidae

family as intermediate hosts. The Juvenile/immature fluke penetrates the intestinal wall and

migrates through liver parenchyma to the bile duct to form adult fluke in the definitive host

damaging it’s the hepatic parenchyma and biliary tract (Geadkaew et al. 2011; Usip et al.

2014). Several potential factors may influence the emergence of F. gigantica infection. First,

the seasonal presence of suitable intermediate hosts in areas with high rainfall, moderate

temperatures, and humidity, and poor drainage (Claxton et al. 1997; Kaplan. 2001; Malek.

2018; Portugaliza et al. 2019; Rana et al. 2014; Rowcliffe et al. 1960) resulting in high

prevalence during certain months of the year (Phiri et al. 2005; Rangel-Ruiz et al. 1999).

Secondly, managemental stress, host immunity, and co-infection with intestinal nematodes;

determined infection rates of F. gigantic (Ahmad et al. 2017; Elelu et al. 2018; Phiri et al.

2005). Thirdly, the clonal expansion of Fasciola within its intermediate snail host resulted in

pasture contamination and subsequent host infection by metacercariae of the same genetic

origin. This clonal expansion can also produce a genetic bottleneck effect when levels of

infection in the snail populations are low (Beesley et al. 2017).

Over past few decades, high levels of animal movement have been reported in

domestic ruminants in many Asian and European regions (Kelley et al. 2016; Vilas et al.

2012); hence genetic analyses are needed to understand the corresponding spread of F.

CHAPTER 1

INTRODUCTION

INTRODUCTION

2

gigantica infections and aid in the development of parasite control strategies (Hayashi et al.

2016). Animal movement patterns differ between farms and F. gigantica infects human

livestock and also wild animals. This potentially enables wildlife reservoirs of infection and

cross-infection between different host species complicating control strategies (Rojo-Vázquez

et al. 2012).

Genetic relationships between parasite species and populations can be analyzed using

internal transcribed spacer region 2 (rDNA ITS-2) and mitochondrial nicotinamide adenine

dinucleotide (NADH) dehydrogenase 1 (mt-ND-1) sequence data. Meta-barcoding, deep

amplicon sequencing techniques and Illumina Mi-seq program allow the research work of

large and diverse fluke populations to show if infection has emerged recently in the host at a

single point of time or if burdens have been established repeatedly at different times before

scattering of disease as a result of animal movement. In recent times, these approaches have

been used in genetic analyses of Calicophoron daubneyi in cattle herds in United Kingdom.

These findings are consistent with numerous free emergence of Calicophoron daubneyi

infection, while in numerous population a variety of terrestrial location, the identification of

common mt-COX-1 haplotypes highlighted the role of animal movements in its spread

(Sargison et al. 2019).

In the present study, firstly, we collected the samples of liver fluke from slaughtered

goats, sheep, cattle, and buffaloes in three different abattoirs of Punjab and Balochistan

provinces of Pakistan through the following aims: i) to check the Fasciola spp; ii) to find out

the presence of single and multiple genotype in a single host and iii) to determine the spread

of F. gigantica mt-ND-1 hapoltypes. On the basis of deep amplicon sequencing approach,

these Fasciola spp were identified by using metabarcoded rDNA ITS2 genetic marker of 483

bp. From three different geographical locations, a population of liver flukes was collected

from single infected animal, haplotype diversity in 20 F. gigantic populations were shown by

deep amplicon sequencing technique by using metabarcoded mt-ND-1 genetic marker of 311

bp. The multiple infections and the spread of F. gigantica mt-ND-1 haplotypes were

examined. We also analysed Fasciola samples collected from goats and buffaloes from the

slaughter house (PAMCO), Lahore, Punjab with the following goals: i) to use the most

reliable genetic marker; polymerase delta (pold) and phosphoenolpyruvate carboxykinase

(pepck) genes, for the identification of Fasciola spp; ii) to use cytochrome C oxidase subunit

1 (cox1) and mitochondrial NADH dehydrogenase subunit 1 (nad1) genes to determine the

spread out of F. gigantica in the Indian subcontinent. Neural network and split tree analyses

INTRODUCTION

3

were done to provide proof of concept for a novel technique for epidemiological studies of

fasciolosis and validation of parasite control strategies.

4

CHAPTER 2

REVIEW OF LITERATURE

2.1 Parasitic Trematode and their importance in Livestock and human health

Class Trematoda and Cestoda are also known as a parasitic flat worm belongs to phylum

Platyhelminths. A cestode completes its life cycle only in a single host called Monogenea while a

trematode which requires two hosts (Intermediate and Definitive hosts) to complete its life cycle

is known as Digenia. Trematodes are hermaphrodites in which both self and cross fertilization

can occur e.g. Fasciolidae, Schistosomatidae, Parampistomatidae, Opisthorchiidae and

Troglotermatidae. Class Trematoda has major parasitic importance in veterinary and human

health (Urquhart 1996). Schistosoma species infected about 165 million cattle population

worldwide (Dar et al. 2011). In human and farm animals, trematodal infections cause significant

losses in numerous regions of the world (Asia Europe, and Latin America) (Mas-Coma et al.

2005; Żbikowska et al. 2009). A total of 191 larval trematode samples were collected from the

livestock and human infections from five different areas in two towns of Elâzığ province of

Turkey and they recorded 14(7.3%) Lymnea truncatula under stereomicroscope (Kaplan et al.

2012). A total of 686 samples were analyzed through fecal examination, the prevalence %age

was recorded of different trematodes; Schistosoma bovis (1.2 %), Dicrocoelium hospes (7.3 %),

Paramphistomum (16.1 %,) and Fasciola gigantica (74.9 %,) in Cattle at Kwara State in Turkey

(Elelu et al. 2016).

Figure 2.1: Zoological classification of Trematode (Olson et al. 2003).


5

2.2 Geographical distribution of Fasciola species

Fasciola is also known as liver fluke. The two main Fasciola spp namely F. hepatica and F.

gigantica, were taxonomically recognized in humans and domestic animals (Nakamura et al.

1998). Both species exist on different environmental conditions; F. hepatica found in temperate

region (in low temperature) where Galba truncatula is the most important intermediate host

mainly found in cold region (Mas et al. 1997), while F. gigantica is found in sub-tropical and

tropical climatic regions (high temperature) of Asia and Africa, whereas snail species (Lymnaea

spp) like Lymnaea natalensis and Lymnaea rubignosa are the main intermediate hosts. However,

Galba truncatula, Radix peragra and L. natalensis are suitable intermediate hosts for both F.

hepatica and F. gigantica. These two species overlap in African and Asian regions (Chaudhry et

al. 2016; Graczyk et al. 1999; Ichikawa et al. 2010; Mas-Coma et al. 2005) .

In Iran, Snails collected from 28 freshwater tube wells from May 2010 to December

2010, where two snail species infected with F. hepatica were found to be G. truncatula and L.

stagnalis with 16.6 % and 1.1 %, respectively through PCR (Yakhchali et al. 2015). On the basis

of ITS-1, 20 (24.7%) flukes were observed as F. gigantica and 61 (75.3%) were F. hepatica out

of total 81 Nepalian Fasciola isolates. For phylogenetic study with other Asian flukes on the

basis of nd1 gene, 61 (75.3%) flukes were aspermic while 21 (24.7%) were identified as

Fasciola spp and F. gigantica. All of the aspermic liver flukes displayed Fg/Fh type on the basis

of ITS-1 which was predominantly aspermic similar to Chinese Fasciola isolates. They

concluded that the aspermic Fasciola spp (hybrid) distributed in Nepal from China and F.

hepatica speedily distributed as compared to F. gigantica (Shoriki et al. 2014). In another study,

the researchers analyzed 147 liver flukes on the basis of spermatogenetic ability with ITS-1 and

ND-1 in Thailand. One hundred and twenty eight liver flukes were identified as F. gigantica

having abundant sperms in their seminal vesicle through Polymerase Chain Reaction-Refraction

Fragment Length Polymorphism (PCR-FLP) approach on the basis of ITS-1. The other 19 liver

flukes were aspermic Fasciola spp having no sperm in the seminal vesicles with the same

pattern. Out of total 128 F. gigantica liver flukes, 29 haplotypes were prominent in Thailand and

also common in other neighboring countries. They suggested that there might be possibility of

introduction of ancestral haplotypes into Thailand from other countries. Geographically, only

one haplotype of (Fg-ND1) was obtained from nineteen aspermic Fasciola spp. Thai 1 haplotype


6

nucleotide sequence showed uniqueness to that of aspermic Fasciola of Myanmar, Vietnam,

Korea, Japan and China. They concluded that they shared a common ancestral lineage and in

recent past they were spread in these countries (Chaichanasak et al. 2012; Dar et al. 2012).

2.3 Effects of Fasciolosis on animal and human

Fasciolosis is a major parasitic disease of the livestock and human throughout the world causing

huge economic hurdle to agriculture directly and indirectly (Cwiklinski et al. 2015). Liver flukes

are trematodal helminthes which are predominant in livestock. Due to crude vegetable

consumption, it emerged as a disease in human especially in chronic form (Abdel Aal et al.

1999; Curtale et al. 2005). Fasciolosis is a food-borne disease worldwide (Abe et al. 2004;

Bargues et al. 2001; Hertz et al. 2001; Hussain et al. 1995; Mas-Coma et al. 2001). WHO

included the human fasciolosis in neglected tropical diseases in 2008. The research work was

designed to investigate the epidemiological aspect of Fasciola spp in humans of Lahore, Pakistan

(Khan et al. 2005). In the African cattle population of 200 million, fasciolosis causes economic

losses about 840 million US $ per annum (Elelu et al. 2016). Worldwide, F. hepatica infects

more than 250 to 300 million sheep and cattle respectively which causes more than 3.2 billion

US $ annual loss of production in meat and milk (Mas-Coma et al., 2005; Charlier et al., 2007).

Fasciolosis directly increases the liver condemnation and indirectly weight loss, anemia and

sudden death and these effects have been observed in livestock. In the liver of mammalians

(definitive host), Fasciola species reside and produce associated pathologies and an adult liver

fluke produces 20,000 eggs per day in feces (Durbin. 1952; Mas-Coma et al. 1999). Mature

Fasciola gigantica reported in small as well as large ruminants from 7 different zones of two

provinces (Balochistan and Punjab) of Pakistan on the basis of ITS-2 rDNA sequencing. Both

species of liver flukes (F. hepatica, F. gigantica) cause infection in animals and also reduce the

meat and milk production. Throughout the world, fasciolosis is also a common zoonosis

(Chaudhry et al. 2016).

2.4 Life cycle of Fasciola

Mammals and Snails serve as definitive and intermediate hosts respectively (Urquhart et al.

1996). In moisture condition after discharge of miracidium from the egg, it invades the

intermediate host (snail) within few minutes where the parasite undergoes three developmental


7

stages namely sporocysts, rediae and cercariae. From the snail, the cercariae are released and

encysted on vegetation. The cercaria in cyst form is known as metacercaria which is the infective

stage for the next mammalian host. After ingestion in the duodenal part of intestine, the

metacercariae is excysted then migrates to the liver parenchyma and then it becomes adult in

biliary duct (Thanh. 2012; Urquhart. 1996).

Figure 2.2: Life cycle of Fasciola (Taylor. 2010)


8

2.5 Fasciola Speciation

(a) Microscopic Examination of Fasciola spp

The two species of liver fluke “F. hepatica and F. gigantica” were based traditionally on

morphological discrimination (Ayele et al. 2016). One such method is computer image analysis

system (CIAS) which is the most modern method and is based on the standardized measurement

of distance between two organs of liver flukes. Fasciola spp were collected from bovines’ liver

in Gilan, Iran and in the Nile Delta, Egypt where F. hepatica and F. gigantica reside in the same

geographical area. Morphometric characteristics obtained by CIAS and compared with standard

population of both species from other geographical regions, they found flukes with another

intermediate species (Ashrafi et al. 2006; Periago et al. 2008). Morphologically Fasciola species

have been detected in many countries like Japan, Korea, Taiwan, China and Vietnam. In

definitive host, specie-wise prevalence %age of fasciolosis was reported lower in cattle (20.42%)

than in buffaloes (30.50%). Overall, F. hepatica was found lower (3.06%) than F. gigantica

(22.40 %) in bovines, but seasonally, prevalence of fasciolosis was recorded 12.92 %, 20.33 %,

29.50 % and 39.08% in summer, autumn, spring and winter, respectively on the bases of egg

morphology. (Kakar et al. 2011; Khan et al. 2009) showed high prevelance (45.70 %) in cattle

than in buffaloes (37.50 %) through microscopic examination. Fasciola spp. affected old age

animals more as compaired to the young ones (Haleem et al. 2016).

Figure 2.3: Microscopic Examination of F. hepatica and F. gigantica (Graczyk et al. 1999)


9

(b) Cytogenetic identification of Fasciola spp

The morphology and number of metaphase chromosomes have been used to characterise the

species. The difference in number of chromosome, size of metacentric and subtelocentric was

first described in the Japanese flukes by Sakaguchi (1980). Number and morphology of

chromosomes have been used in high level comparisons through phylogenetic analysis

(Ahmad et al. 2016) Many studies on Karyotyping of abnormal chromosomes demonstrated

differences in chromosome number of diploid (2n), triploid (3n) and mixoploid (2n/3n)

populations of F. gigantica and F. hepatica from Japan, Korea (Romanenko et al. 1975),

Vietnam, China (Puqin. 1990), Britian and Ireland (Fletcher et al. 2004). They conculded that

mostly triploid forms were smaller than diploid forms, but some triploid flukes tend to be

larger. Triploid and diploid Fasciola organisms were found aspermic which tend to be

parthenogenetic (Terasaki et al. 2000).

(c) Molecular identification of Fasciola species

PCR and sequencing of DNA help to explain strains, species identification and genetic

populations (Shyamala et al. 1989). In GenBank, thousands of complete metazoan

mitochondrial (mt) genome and 90,000 of ITS-2 are available. For phylogenetic analysis, the

gene or target sequence must be long enough to provide informative characters. In animal

evolution, biogeography, phylogeny, population genetics and related fields’ mitochondrial

genomes and ITS gene have been extensively studied through several molecular techniques

such as DNA sequencing, PCR, RFLP analysis and Single–Strand Conformation

Polymorphism (SSCP) (Thanh. 2012).

The sequencing results of nad1 genetic marker from the Japanese Fasciola isolates were

observed 8.3% nucleotide differences in triploid (3n) which could be categorized as F.

gigantica, however there was homology of nucleotide at 8th

position in ITS-2 sequence. The

isolates of Fasciola species collected from Japan were found to be as F. gigantica (Itagaki et

al. 1998). Rather, same isolates from Japan were observed to be F. hepatica, when ITS-2

sequence was analyzed. These researchers concluded that the triploid worms in the isolates

might be hybrid between F. gigantica and F. hepatica (Agatsuma et al. 2000; Itagaki et al.

1998). Similar studies were conducted in Nigeria (Ali et al. 2008), Russia (Morozova et al.

2004), Vietnam (Itagaki et al. 2009; Le et al. 2008), Korea (Itagaki et al. 2005b), and China

(Huang et al. 2004; Le et al. 2007). From the above studies, it is concluded that the

intermediate forms have been originated between F. hepatica and F. gigantica, maternally F.


10

gigantica and paternally F. hepatica resulting hybrid forms of the parasite. The Fasciola

isolates were found to be F. gigantica from Korea on the basis of CO1 and NAD1 genetic

markers and on the other hand, they showed different results with ITS-2 and D-2 genetic

markers. Out of five isolates, two possessed F. gigantica, one F. hepatica and the remaining

two specimens showed hybrid (Fh/Fg) characters. These two genetic markers namely ITS-2

and D-2 were represented by 2 F. gigantica, 1 F. hepatica and 2 hybrid worms containing

mixture of 2 sequences from Fg and Fh. This strongly suggested that interspecies cross

hybridization of F. hepatica and F. gigantica occurred in Korea (Agatsuma et al. 2000).

Figure 2.4: The sizes of different Fasciola parasites recoverd from the liver of animals; small

(S), medium (M) and large (L) (Nguyen et al. 2018).

Numerous studies provided the genetic evidence for the presence of hybrid when analysed

ITS-1 and ITS-2 of rDNA in Fasciola isolates collected in numerous hosts (sheep, Goat,

Cattle and human) in different geographical locations (China Vietnam, Korea and Japan)

(Huang et al. 2004; Itagaki et al. 2009; Le et al. 2007; Le et al. 2008; Lin et al. 2007; Peng et

al. 2009). They suggested that the hybrids (intermediates) of the two Fasciola spp in

countries like China, Japan and Korea were formed from the different parents of Fasciola spp

and become hybrid in next generation due to non-barrier movement of animals in different


11

geographical regions (Itagaki et al. 2005b; Le et al. 2008; Peng et al. 2009). Out of eighty

eight, 8 spermic flukes were F. gigantica and also 8 aspermic flukes were identified as F.

hepatica through PCR-RFLP. In phylogenetic study, 7 Fasciola ND-1 haplotype sequences

from Myitkyina showed uniqueness to that of aspermic Fasciola as existed in other Asian

countries like China, while, 17 nad1 haplotypes were identified as F. gigantica which were

identical to that of already reported in Myanmar. The authors concluded that the introduction

of F. gigantica in Myanmar might be due to the free movement of infected domestic

ruminants in neighboring countries (Ichikawa et al. 2011).

2.6 Gene flow (movement of animal)

Until 15th

century, Silk Road was used to connect the eastern city Xian in China (old

Changan) with the central Asian city; Samarkand of Uzbekistan which connects to western

localities in north and southern Himalayas such as Turkmenistan, Tajikistan and Kirgizstan

connecting at the end to India (Gasparini. 2019). For the transportation of goods meant for

the purpose of merchandise, Zebu cattle and dromedary camels were mainly used in the most

southern routes of Silk Road through Pakistan, Afghanistan and India (Collon. 1995). In

Samarkand Uzbekistan, total of 81 isolates of liver flukes were examined on the basis of

morphology, 45 of them were F. hepatica, 25 were F. gigantica and 11 were hybrids

(Widjajanti. 2004). Another trade route so called Fur road between forest area of Poland,

Russia and Siberia (Abdeljaouad. 2016) which might have exchanged fasciolosis between

Asian and European countries. Trade through animals was probably the way to spread the

liver flukes between pacific island and Indonesia (Abdeljaouad. 2016; Intong et al. 2003).

The prevalence of F. hepatica was elevated in the intermediate host i-e snail and a huge

population of the same parasitic genotype emerged on pastures; on the other hand, wide

spread movement of animals resulted high level of gene flow (Beesley. 2016).

Historically, it has been suggested that F. gigantica might originate and spread by Zebu cattle

(Bos indicus) and water buffalo (Bubalus bubalis) in the Indian subcontinent (Peng et al.

2009). Around 5,000 to 6,000 BC, Zebu cattle and water Buffaloes were domesticated in the

Northwestern region of Indian subcontinent (Pakistan) (Bradley et al. 1996; Loftus et al.

1994; Tanaka et al. 1996), the spread of F. gigantica might play a significant role due to the

free movement of Zebu cattle and water buffaloes before the creation of Pakistan. Over the

past few decades, high levels of the animal movements have been reported in domestic

ruminants in the Indian subcontinent (Kelley et al. 2016; Vilas et al. 2012). The animal


12

movement patterns differed between farms and F. gigantica infected domestic animals, wild

animals and humans potentially enabled the spread of this parasite (Rojo-Vázquez et al.

2012). In contrast, the farmers rear multiple species of animals to meet their livelihood in the

Indian subcontinent (Devendra. 2007). Mixed farming system played a significant role in the

spread of F. gigantica. Hence genetic analyses are needed to understand the corresponding

origin and spread of F. gigantica infections, aid in the development of parasite control

strategies (Hayashi et al. 2016; Shoriki et al. 2016).

Figure 2.5: Main geographical spread routes followed by Fasciola gigantica in the post-

domestication period (Mas‐ Coma et al. 2009)

2.7 prevention and Control of Fasciolosis

It is difficult to control fasciolosis completely. The following control measures are based on:

(1) Under highly controlled and managemental husbandry system, the parasites (Fasciola

spp) might be controlled; (2) properly and timely use of Anthelmintics; (3) Avoid the

movements of animal in natural grazing area for a few days after the use of Anthelmintics;

(4) combating of intermediate hosts; (5) adopt highly parasite resistance breed of animals; (6)

novel approaches for vaccination (Sanyal. 2009; Taylor. 2012). Control of the parasite can be


13

done through reducing the infection in the reservoir host, control of intermediate host and

intervention aiming at reducing transmission such as fencing and grazing management and

education (Parkinson et al. 2007; Spithill. 1999; Torgerson et al. 1999). For epidemiological

and cross-sectional studies on animals and human, fasciolosis should be screened through

coprological, molecular or serological techniques that could be used for obtaining correct

data on the distribution of Fasciolosis. Strategic use of anthelminthics after ending of rainy

season has potential effect on the control of liver fluke population (ANJUM. 2015;

Badirzadeh et al. 2017). The fluke eggs are inactivated at high temperature (60-70 °C),

moreover, the hatching of eggs can be hindered by treating or drying of the freshly passed

dung of cattle before to use it as a fertilizer, otherwise heavy rain may spread the eggs in the

neighboring fields (Doanh et al. 2012; Suhardono et al. 2006). Fasciolosis might be

controlled through avoiding the use of fresh animal dung for fertilizing the vegetable gardens,

rice fields and free grazing of animals on surrounding rivers and rice fields (Nguyen et al.

1996). Humans may be infected by eating poor hygienic, fresh and undercooked aquatic

plants (Bui et al. 2016; Phi. 2018).

For more than twenty years, triclabendazole has been the drug of choice for the

treatment of fasciolosis both in animals and also in humans (Fairweather. 2005).

Triclabendazole is more effective against both immature and mature flukes (Fairweather et

al. 1999). However, in some countries like UK, Spain, Australia, Netherland and Ireland,

triclabandozole resistance has been reported but Closantel and Clorsulon are the flukicidal

compounds which retain their efficacy against triclabendazole-resistant fluke population.

Vaccine approaches against Fasciola might reduce the incidence (Brennan et al. 2007).


14

Table 2.1: List of research work done on speciation of Fasciola by using different tools in ascending order

Sr.

No.

Fasciola

spp

Snail Type of

Host

Site of

study

Tool of

diagnosis

Animal condition

(slaughtered/infected/healt

hy)

Genetic

marker

Duration of

the study

Reference

1 Fasciola

spp

- Sheep UK Microscopy

Infected -

1952 Durbin. (1952)

2 Fh, Fg, Hb - Cattle

Goat

Japan PCR Slaughtered ND-1

CO-1

1997-1998 Itakagi et al.,(1998)

3 Fh, Fg, Hb Cattle Korea PCR Infected/Slaughtered ITS-1

CO-1

ND-1

1999-2000 Agatsuma et al.,

(2000)

4 Fg, - Cattle China PCR Slaughtered ITS-2

2003-2004 Hung et al.,(2004)

5 Fh, Fg, Hb - Cattle Japan PCR Slaughtered ITS-1

ITS-2

COX-1

ND-1

2004-2005 Itakagi et al.,(2005)

6 Fh Lt Human

Cattle

Sheep

Spain PCR Slaughtered ITS-1

ND-1

CO-1

2004-2005 Mas-Coma et al,.

(2005)


Buffalo

Iran Microscopy Infected - 2005-2006 Ashrafi et al., (2006)

8 Fh - Human Vietnam Microscopy/

PCR

Infected ITS-2 2006-2007 Le et al., (2007)


Buffalo

China PCR Slaughtered ITS-1

2006-2007 Lin et al., (2007)

10 Fh, Fg, Hb - Goat

Buffalo

Niger PCR Slaughtered

ITS-1

ITS-2

2007-2008 Ali et

al., (2008)


15

11 Fh, Fg, Hb - Human

Cattle

Buffalo

Vietnam PCR Infected/Slaughtered ITS-1 2007-

2008

Le et al., (2008)

12 Fg, Fg, Hb - Cattle

Buffalo

Egypt CIAS Slaughtered - 2007-2008 Periago et al., (2008)

13 Fg - Cattle Vietnam PCR Slaughtered ITS-1

ND-1

CO-1

2008-2009 Itagaki et al., (2009)

14 Fh, Fg - Cattle

Buffalo

Pakistan Microscopy infected - 2008-2009 Khan et al., (2009)

15 Fh, Fg, Hb

Hb

Lt, Gp,

Lv, La

Human

Cattle

Sheep

Buffalo

Globally Microscopy

PCR

Infected/Slaughter - 2008-2009 Mas-Coma et

al.,(2009)

16 Fh, Fg, Hb

Cattle China PCR Slaughter ITS-1 2008-2009 Peng et al., (2009)

17 Fh, Fg,

Hb

Buffalo Japan PCR Slaughter ITS-1

ND-1

CO-1

2009-2010 Ichikawa and Itagaki,

(2010)

18 Fh, Fg, Hb - Sheep Uruguay PCR slaughter ITS-1

2010-2011 Itagaki et al.,

(2011)

19

Fh, Fg - Cattle

Buffalo

Pak Microscopy Infected - 2010-20011 Kakar et al.,

(2011)

20 Fg - Cattle

Buffalo

Thailand /PCR Slaughtered ITS-1

ND-1

2011-2012 Chaichanasak et al.,

(2012)

21 Fh, Fg - Cattle

Sheep

Buffalo

Egypt PCR slaughtered ITS-2,

CO-1,

ND-1

2011-2012 Dar et al., (2012)

22 Fh, Fg,

- Cattle

Pak CIAS slaughter ITS-1

ITS-2

COX-1

2012-2013 Afshan et al.,

(2013)


16

NAD-1


Goat

Nepal PCR Slaughtered ITS-1

ND-1

1013-

2014

Shoriki et al., (2014)

24 Fh, Fg

- Cattle

Buffalo

Pak Microscopy Infected - 2015-

2016

Haleem et al.,(2016)

25 Fg - Cattle

Buffalo

Indonesia PCR Slaughtered PEPCK

POLD

ND-1

2015-2016 Hayashi et al., (2016)

Fh=Fasciola hepatica, Fg=Fasciola gigantica, Hb hybrid, Lt=Lymnea Truncatula, Lv Lymnaea viatrix, St= Stagnicola, Gp=Galba, Pseudosuccinea, La=

Lymnaea acuminata, CIAS=computer image analysing system, PEPCK= phosphoenolpyruvate Carboxykinase, POLD= Polymerase Delta

17

Statement of problem:

Fasciola hepatica and Fasciola gigantica are common flukes of the ruminants. The two

sympatric species of the parasites which are phylogenetically closely related species and co-

infection in the same host gives hybrid of these two trematode species.

Objectives:

To identify Fasciola spp. through PCR.

To observe phylogenetic profile of Fasciola spp.

To find out the hybrids of Fasciola spp.

18

CHAPTER 3

MATERIALS AND METHODS

3.1. Sample collection

In the Balochistan and Punjab provinces of Pakistan three abattoirs were selected

where there is known high prevalence of Fasciolosis. A total of 40 infected liver samples

were collected from three city abattoirs. Thirty one samples (buffalo=17, cattle=1, goat=13)

were collected from Lahore, Punjab (31.5204° N, 74.3587° E), 6 samples (sheep=2 cattle=4)

were collected from Murgha Kibzai, Balochistan (30.7384° N, 69.4136° E), and 6 samples

were collected from Loralai, Balochistan (30.3806° N, 68.5963° E), where liver flukes were

extracted from the biliary ducts by dissection. Total of 358 (236 from Punjab and 122 from

Balochistan) individual flukes were obtained from the populations. The flukes were identified

as Fasciola spp. morphologically, thoroughly washed with normal saline, and then preserved

in 70 % ethanol at -20 °C.

3.2 Collection of Eggs from Live Fasciola spp

Live Fasciola spp were collected from biliary duct of the final hosts with forceps,

placed in a 2 ml tube having normal saline and closed tightly. The liver fluke were brought to

Molecular Parasitology Laboratory. Only flukes were removed while the tubes centrifuged at

20,000 rpm for 10 minutes and discarded the supernatant. The tubes were centrifuged again at

15,000 rpm for 5 minutes and the supernatant was discarded. A 1 µl solution was taken from

the bottom of the tube with the help of micropipette and put on glass slide with cover slip

then examined under microscope with 400X magnification.

3.2.1 DNA extraction

A small piece of tissue of about 2 mg from the head region of each fluke was taken

for DNA extraction, each piece of flukes was rinsed two times in a petri dish for 4-5 minutes

with distilled water by avoiding the possible contamination with eggs and then lysed in 25 µl

lysis solution prepared by adding of 50 µl proteinase K (10 mg/ml, New England BioLabs)

and 50 µl 1M Dichloro Diphenyl Trichloroethane (DDT) in 1ml of Direct PCR Lysis Reagent

(Viagen). Then, lysates were incubated at 60 °C for 2 hrs, followed by 85 °C for 15 minutes.

Lysates were stored at -80°C until use. The slaughter house study was approved by the

Ethical Review Committee of the university of Veterinary and Animal sciences, Lahore,

Pakistan.

3.2.2 Genomic DNA extraction


19

Out of total 358, only 53 flukes of 14 buffalo and goat populations from two to four

worms using the High Pure PCR Template Preparation Kit (Roche, Mannheim, Germany) in

accordance with the manufacturer’s protocols. DNA was extracted from the individual fluke

and stored at -20 °C until use.

3.3. Metabarcoded sequencing approach

The complete scheme of the metabarcoding sequencing approach using Illumina

Miseq platform is shown in Fig. 6. The whole procedure was run in twice: first on the

individual worms for species identification using the rDNA ITS-2 marker; then on pooled F.

gigantica from each population, using the mt-ND-1 marker.

Figure 3.1: Schematic representation of the preparation and bioinformatics analysis of the

metabarcoding sequencing libraries. In the first round PCR amplification, over-hanging

primers were used to amplify the ITS-2 rDNA and mt ND1 fragments. The adapter base pairs

provide the target site for the primers used for sequencing the fragment. The random

nucleotides (0-3Ns) are inserted between the adopter and the primers to offset the reading

frame, thereby amplicons were sequenced to prevent the over saturation of the Miseq

sequencing channels. The second round PCR amplification was then performed using over-

hanging barcoded primers to bind to the adopter tag to add indices as well as the P5 and P7

regions required to bind to the Miseq flow cell. The analysis of both rDNA ITS-1 and mi-

ND-1 FASTQ files were performed in Mothur v1.39.5 software by using our modified

command prompt pipeline and the standard operating procedures of Illumina MiSeq.

3.3.1Adapter PCR amplification of rDNA ITS-2 and mt-ND-1 loci

The 1st round PCR amplification was performed on 483 bp fragments of the rDNA

ITS-2 region, complementary to the 5.8s and 28s rDNA coding sequences, using universal

sets of primers (Adlard et al. 1993; Chaudhry et al. 2016) and 311 bp mt-ND-1 fragments


20

using newly developed primers (supplementary Table S1). For allowing successive annealing

of primers, the adopter primers were added and to enhance the amplicons up to three random

nucleotides between each primer and adapter were added, resulting in a total of 4 forward and

4 reverse primers (Table 2). For both rDNA ITS-2 and ND-1 loci, equal proportions of 4

forward and 4 reverse primers were mixed and used for the adapter PCR with the following

conditions: 10mM dNTPs, 10 µM forward and reverse adaptor primers, 5X KAPA HiFi

Fidelity buffer, 0.5 UKAPA HiFi Fidelity polymerase (KAKA Biosystems USA), 14 µl

ddH2O and 1 µl of fluke lysate. The thermocycling conditions of PCR reaction were as

follows 95 °C for 2 min, followed by 35 cycles of 98 °C for 20 sec, 65°C for 15 sec for ITS-

2, and 60 °C for 15 sec for ND-1 and 72 °C for 15 sec, followed by a final extension at 72 °C

for 5 min. PCR products were then purified with AMPure XP Magnetic Beads (1X)

according to the manufacturer’s instructions (Beckman Coulter).


21

Table 3.1: ITS-2 and mt-ND-1 primers. Primer sequences for the amplification of Fasciola rDNA ITS-2 and mt-ND-1. Forward and reverse primer sets are

underlined, N’s are bolded, and adapters are in italic format.

Sequences (5'-3') Primer name Target region Direction

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGGTGGATCACTCGGCTCG*T*G AD_For rDNA ITS-2 Forward

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGNGGTGGATCACTCGGCTCG*T*G AD_For-1N rDNA ITS-2 Forward

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGNNGGTGGATCACTCGGCTCG*T*G AD_For-2N rDNA ITS-2 Forward

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGNNNGGTGGATCACTCGGCTCG*T*G AD_For-3N rDNA ITS-2 Forward

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGTTCCTCCGCTTAGTGATAT*G*C AD-Rev rDNA ITS-2 Reverse

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGNTTCCTCCGCTTAGTGATAT*G*C AD_Rev-1N rDNA ITS-2 Reverse

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGNNTTCCTCCGCTTAGTGATAT*G*C AD_ Rev-2N rDNA ITS-2 Reverse

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGNNNTTCCTCCGCTTAGTGATAT*G*C AD_ Rev-3N rDNA ITS-2 Reverse

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTTTAAGTTTGTGTTTTT*T*C UN2_For mt-ND-1 Forward

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGNGTTTAAGTTTGTGTTTTT*T*C UN2_For-1N mt-ND-1 Forward

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGNNGTTTAAGTTTGTGTTTTT*T*C UN2_For-2N mt-ND-1 Forward

TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGNNNGTTTAAGTTTGTGTTTTT*T*C UN2_For-3N mt-ND-1 Forward

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGCACCATAACTCCCCCAAAC*C*A ND1_Rev mt-ND-1 Reverse

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGNCACCATAACTCCCCCAAAC*C*A ND1_Rev-1N mt-ND-1 Reverse

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGNNCACCATAACTCCCCCAAAC*C*A ND1_Rev-2N mt-ND-1 Reverse

GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGNNNCACCATAACTCCCCCAAAC*C*A ND1_Rev-3N mt-ND-1 Reverse


22

3.3.2 Barcoded PCR amplification of rDNA ITS-2 and mt-ND-1 loci

In the 2nd

round metabarcoded PCR, sixteen primers forward (N501-N516) and

twenty-four reverse (N701-N724) primers were used (Table 3), each sample contained a

unique combination of primers forward and reverse in way. With the following conditions the

barcoded PCR was performed, 10 mM dNTPs, 10 µM barcoded forward and reverse primers,

5X KAPA HiFi Fidelity buffer, 0.5 U KAPA HiFi Fidelity polymerase (KAPA Biosystems,

USA), 14 µl ddH2O and 2µl of the first round PCR product. The thermocycling conditions

for 2nd

round of PCR were; 98 °C for 45 sec, followed by seven cycles of 63 °C for 20 sec

and final extension at 72 °C for two min. The PCR products were purified with AMPure XP

Magnetic Beads (1X) according to the manufacturer’s instructions (Beckman Coulter).


23

Table 3.2: List of barcoded primers. Sequences for forward and reverse barcoded primers

(Nextera XT Index Kit v2). Index sequences are highlighted in bold. The primers were used

in a way that each sample had a unique forward-reverse combination.

Primer Sequence, 5’-3’

S501 AATGATACGGCGACCACCGAGATCTACACTAGATCGCTCGTCGGCAGCGTC

S502 AATGATACGGCGACCACCGAGATCTACACCTCTCTATTCGTCGGCAGCGTC

S503 AATGATACGGCGACCACCGAGATCTACACTATCCTCTTCGTCGGCAGCGTC

S504 AATGATACGGCGACCACCGAGATCTACACAGAGTAGATCGTCGGCAGCGTC

S505 AATGATACGGCGACCACCGAGATCTACACGTAAGGAGTCGTCGGCAGCGTC

S506 AATGATACGGCGACCACCGAGATCTACACACTGCATATCGTCGGCAGCGTC

S507 AATGATACGGCGACCACCGAGATCTACACAAGGACTATCGTCGGCAGCGTC

S508 AATGATACGGCGACCACCGAGATCTACACCTAAGCCTTCGTCGGCAGCGTC

S510 AATGATACGGCGACCACCGAGATCTACACCGTCTAATTCGTCGGCAGCGTC

S511 AATGATACGGCGACCACCGAGATCTACACTCTCTCCGTCGTCGGCAGCGTC

S512 AATGATACGGCGACCACCGAGATCTACACTCGACTAGTCGTCGGCAGCGTC

S513 AATGATACGGCGACCACCGAGATCTACACTTCTAGCTTCGTCGGCAGCGTC

S514 AATGATACGGCGACCACCGAGATCTACACCCTAGAGTTCGTCGGCAGCGTC

S515 AATGATACGGCGACCACCGAGATCTACACGCGTAAGATCGTCGGCAGCGTC

S516 AATGATACGGCGACCACCGAGATCTACACCTATTAAGTCGTCGGCAGCGTC

N701 CAAGCAGAAGACGGCATACGAGATTAAGGCGAGTCTCGTGGGCTCGG

N702 CAAGCAGAAGACGGCATACGAGATCGTACTAGGTCTCGTGGGCTCGG

N703 CAAGCAGAAGACGGCATACGAGATAGGCAGAAGTCTCGTGGGCTCGG

N704 CAAGCAGAAGACGGCATACGAGATTCCTGAGCGTCTCGTGGGCTCGG

N705 CAAGCAGAAGACGGCATACGAGATGGACTCCTGTCTCGTGGGCTCGG

N706 CAAGCAGAAGACGGCATACGAGATTAGGCATGGTCTCGTGGGCTCGG

N707 CAAGCAGAAGACGGCATACGAGATGTGTGTAGGTCTCGTGGGCTCGG

N708 CAAGCAGAAGACGGCATACGAGATCAGAGAGGGTCTCGTGGGCTCGG

N709 CAAGCAGAAGACGGCATACGAGATGCTAGGGTGTCTCGTGGGCTCGG

N710 CAAGCAGAAGACGGCATACGAGATCGAGGCTGGTCTCGTGGGCTCGG

N711 CAAGCAGAAGACGGCATACGAGATAAGAGGCAGTCTCGTGGGCTCGG

N712 CAAGCAGAAGACGGCATACGAGATGTAGAGGAGTCTCGTGGGCTCGG

N713 CAAGCAGAAGACGGCATACGAGATGCTCATGAGTCTCGTGGGCTCGG

N714 CAAGCAGAAGACGGCATACGAGATATCTCAGGGTCTCGTGGGCTCGG

N715 CAAGCAGAAGACGGCATACGAGATACTCGCTAGTCTCGTGGGCTCGG

N716 CAAGCAGAAGACGGCATACGAGATGGAGCTACGTCTCGTGGGCTCGG

N717 CAAGCAGAAGACGGCATACGAGATGCGTAGTAGTCTCGTGGGCTCGG

N718 CAAGCAGAAGACGGCATACGAGATCGGAGCCTGTCTCGTGGGCTCGG

N719 CAAGCAGAAGACGGCATACGAGATTACGCTGCGTCTCGTGGGCTCGG

N720 CAAGCAGAAGACGGCATACGAGATATGCGCAGGTCTCGTGGGCTCGG

N721 CAAGCAGAAGACGGCATACGAGATTAGCGCTCGTCTCGTGGGCTCGG

N722 CAAGCAGAAGACGGCATACGAGATACTGAGCGGTCTCGTGGGCTCGG

N723 CAAGCAGAAGACGGCATACGAGATCCTAAGACGTCTCGTGGGCTCGG

N724 CAAGCAGAAGACGGCATACGAGATCGATCAGTGTCTCGTGGGCTCGG


24

3.4.1 Species identification based on the nuclear DNA markers

Previously, species identification for Fasciola flukes with Nuclear DNA markers were

described (Shoriki et al. 2016). Briefly, the fragments of pepck gene were amplified through

a multiplex PCR assay using primers Fh-pepck-F, Fg-pepck-F and Fcmn-pepck-R. The PCR

amplicons were electrophoresed on 1.8 % agarose gels and stained with an ethidium bromide

solution (10 mg/ml) for half an hour to visualize and detect F. hepatica (Fh), F. gigantica

(Fg), are both Fh and Fg (Fh/Fg: the hybrid ) fragment patterns. PCR amplicons of pold

generated using the Fasciola–pold-F1 and Fasciola-pold–R1 primers were subsequently

digested with A1ul (Toyobo, Osaka, Japan) at 37 °C for 3 hrs. The resultant DNA fragments

(Fh, Fg or Fh/Fg) were electrophoresed as described.

3.5 Illumina Mi-Seq run, bioinformatics data handling and analysis

The bead-purified products from each sample were mixed to prepare a pooled library

(Fig. 6) and measured with the KAPA qPCR library quantification kit (KAPA Biosystems,

USA) before running it on the Illumina Mi Seq sequencer using a five hundred-cycle pair–

end reagent kit (Miseq Reagent Kits v2,MS-103-3003) at a concentration of 15 nM with

addition of 15 % phix control v3 (Illumina,FC-11-2003). During the post–run processing, Mi

Seq splits all sequences by samples using the barcoded indices to produce FASTQ files

(Table 3). The analysis of both rDNA ITS-2 and mt-ND-1 FASTQ files were performed in

Mothur v1.39.5 software (Schloss et al. 2009) using the modified command prompt pipeline

(Sargison et al. 2019) and the standard operating procedures of Illumina Mi-Seq (Kozich et

al. 2013).

For both rDNA ITS-2 and mt–ND1, the raw paired end reads were analyzed to

combine the two sets of reads for each parasite population using make Contigs command,

which requires stability files as an input. The make contigs command extracts sequence and

quality score data from FASTQ files, creating complements of the reverse and forward reads

and joins them into contigs. It simply aligns the pairs of sequence reads and compares the

alignments to identify any positions where the two reads disagree. Next, there was a need to

remove any sequences with ambiguous bases using the screen sequence command The

alignment of the above dataset was performed with a F. gigantica and F. hepatica rDNA

ITS-2 and F. gigantica mt-ND-1 reference sequence taxonomy library created from the NCBI

database (for more details Table 2) based on where the sequences start and end corresponding

with the primer set (Table 3). The aligned sequence command was adapted for the reference

sequence taxonomy library to be aligned with rDNA ITS-2 and mt-Nd-1 Illumina Mi-seq

data set. To confirm that these filtered sequences overlap the same region of the reference


25

sequence taxonomy library, the screen sequences command was run to show the sequences

ending at the 483 bp rDNA ITS-2 and 311 bp mt-ND-2 position.

At this stage, the rDNA ITS-2 analysis was completed by classifying the sequences in

to either of the 2 groups (F. gigantica or F. hepatica), using the classify sequence command

and creating the taxonomy file by using the summary tax command. Overall thousands rDNA

ITS-2 reads were generated from the data set of 305 individual flukes from 26 populations.

The presence of each species was calculated by dividing the number of sequences reads of

each flukes by total number of reads.

Once all sequences were classified as F. gigantica mt-ND-1 based on the screen

sequence command, a count list of the consensus sequences of each population was created

using the unique sequence command followed by the use of pre cluster command to look for

sequences having up to 2 differences and to amalgamate them in groups based on their

abundance. Chimeras were known and removed to use the Chimera v search commands. To

create the FASTQ files, the count list was then used of the consensus sequences of the each

population by using the split groups command (Table 3 for more details). In Geneious v 9.0.1

software (Biomatters Ltd New Zealand) the accord sequences of F. gigantica mt-ND-1 were

separately analyzed (Kearse et al. 2012). As described previously, the MUSCLE alignment

tool was used to remove the polymorphisms happening only once as being artifacts due to

sequencing errors (Sargison et al. 2019). After corrections into single haplotype, these

aligned consensus sequences were imported into the FaBox 1.5 online tool to collapse the

sequences that showed 100% bp resemblance. By dividing the number of sequence reads of

each population with the total number of reads, the frequency of all the haplotypes present in

the total and at each population level was calculated.

3.5.1. Haplotype determination for mitochondrial nad-1 and cox-1 sequences

The primers Ita8/Ita9 and Ita10/Ita2 were used for the amplification of cox-1and

mitochondrial genes respectively (Itagaki et al. 2005a). In accordance with manufactures

manual, the PCR amplicons were purified to use NucleoSpin Gel and PCR Clean up Kit

(Macherey-Nagel, Duren, Germany). By Eurofin Genomics K.K. (Tokyo, Japan), the purified

amplicons were sequenced. The resultant DNA sequences were assembled using ATGC

ver.6.0.3(Genetyx Co, Tokyo, Japan) and haplotypes were identified using GENETYX

ver.10.0.2 (Genetyx Co) The concatenated nad-1 + cox-1 sequences were also generated and

haplotypes were determined.

3.6. Network and Split tree analysis


26

Based on a neighbor-joining algorithm using network 4.6.1 software (Fluxus

Technology Ltd), a network tree was produced built on a sparse network with the epsilon

parameter is set to 0 default. To use the UPGMA technique in the Jukes-Cantor model of

substation, a split tree was created in the splitTrees4 software (Huson et al. 2006). For

UPGMA analysis the appropriate model of nucleotide substitutions was selected by using the

jModel test 12.2.0 program (Posada et al. 2008). A maximum likelihood tree was constructed

in Mega 6.0 (Tamura et al. 2013) based on a neighbor joining algorithm using HKY+G+I

model. By thousand bootstraps of the data the branch supports were obtained.

For all the generated sequences within and between populations for genetic diversity

was calculated by using the DnaSP-5.10 software package (Librado et al. 2009) and the

following values were obtained: Nucleotide diversity (π), Haplotype diversity (Hd), the

number of segregating sites(S), the mean number of pairwise differences (K), the mutation

parameter based on an infinite site equilibrium model, and the number of segregating sites

(θS).

3.6.1 Median-joining network construction for mitochondrial markers

To determine the phylogenetic relationships among the nad1 (535 bp), Cox1 (430 bp)

and the concatenated nad1+cox1 (965 bp) haplotypes detected in the Pakistani flukes

Median-joining (MJ) network algorithm was employed by using Network 5.0.1.1 software

(Fluxus Technology) (Tajima. 1989). Another MJ network was prepared to compare the nad1

haplotypes obtained with the reference nad1 haplotypes of F. gigantica from India (Ichikawa

et al. 2010), Bangladesh (Mohanta et al. 2014; Peng et al. 2009), Nepal (Shoriki et al. 2014),

Myanmar (Ichikawa et al. 2011) Thailand (Chaichanasak et al. 2012), Vietnam (Itagaki et al.

2009), Indonesia (Hayashi et al. 2015), China (Peng et al. 2009), Korea (Ichikawa et al.

2012), and Japan (Itagaki et al. 2005a). From the GenBank, the reference sequences were

recovered.

The diversity indices including nucleotide diversity (π), number of variable sites (S),

number of haplotypes (h) and the number of flukes (N) were calculated using DnaSP

software ver.5.1 (Librado et al. 2009). To detect significant differences in π values among the

populations, Tukey’s test was performed by GraphPad Prism 7.04 (GraphPad software Inc,

San Diego, CA, USA). Between the populations, the pair wise fixation index (FST) values

were calculated to use Arlequin program version 3.5.2.2 (Loftus et al. 1994). Regarding

Pakistani Fasciola in the present study, those indices were compared between the host species

to find the differences.


27

The determined indices of the Pakistani Fasciola population were compared with

those in the reference populations of F. gigantica included in haplogroup A in previous

studies from India (Hayashi et al. 2015), Bangladesh (Mohanta et al. 2014), Nepal (Shoriki et

al. 2014), and Myanmar (Ichikawa et al. 2011) to find relationships between the countries.

The implemented dataset was identical to that used for the MJ network.

28

CHAPTER 4

RESULTS

4.1 Hybridization among liver flukes

The liver fluke samples were collected from sheep in Balochistan province of

Pakistan. The flukes were examined macroscopically. The first fluke showed the normal

shape of F. hepatica, the 3rd

one looks like F. gigantica and the 2nd

one resembled to F.

hepatica or intermediate form. It is very confusing to identify the Fasciola spp. on the bases

of morphological structure.

1 32

Figure 4.1: About 2 mg piece of tissue from the head region of each fluke was taken for DNA extraction.

RESULTS

29

A

BC

Figure 4.2: Eggs collected from live Fasciola spp. About 100 to 200 eggs were observed in 1

µl.

4.2.1 Consensus sequence taxonomy library preparation of F. hepatica and F. gigantica

mt-ND-1 and rDNA-ITS-2 loci

A total of 27 NCBI GeneBank sequences of the Fasciola rDNA ITS-2 locus (F.

gigantica=14, F. hepatica=13) and 167 NCBI GeneBank sequences of the Fasciola mt-ND-1

locus (F. gigantica=67, F. hepatica=100) were identified by BLAST search. By using the

MUSCLE alignment tool, the sequences were analyzed separately in Geneious v9.0.1

software (Biomatters Ltd, New Zealand) (Kearse et al. 2012). The construction of the full

RESULTS

30

probability tree demonstrate separate clustering of rDNA ITS-2 and mt-ND-1 loci of F.

gigantica and F. hepatica (Figure 9A & B).

Figure 4.3: The maximum likelihood tree was obtained from the BLAST searched F.

gigantica and F. hepatica rDNAITS-2 and mt-ND-1 loci. The NCBI GenBank sequences

were first aligned on the MUSCLE tool of the Geneious v9.0.1 software (A) 27 sequences of

the rDNAITS-2 were identified among F. gigantica and F. hepatica species (B) 40 identical

sequence of the mt-ND-1 were identified among 100 and 67 F. gigantica and F. hepatica

species. The neighbour-joining algorithm (kimura 2 and HKY+I- parameter model) was

computed with 1000 boots trap replicates using MEGA software created. Each species was

identified with different shade bars.

4.2.2. Confirmation of species identity and co-infection with rDNA ITS2 sequence analysis

A total 305 individual worms, comprising of 26 populations, were run through the Illumina

MiSeq platform, out of which 238 (77.6%) were confirmed to be F. gigantica, 56 (18.7%)

were F. hepatica and 11 (3.7%) showed heterozygous sequence reads (Table 1). All 183

worms collected in Punjab from buffalo, cattle, and goats were F. gigantica. In contrast, 122

worms collected from Balochistan were both F. gigantica (42.2%) and F. hepatica (48.3%),

as well as the intermediate forms (9.5%); except the buffalo populations contained only F.

gigantica (Table 4).

RESULTS

31

Table 4.1. Species identification of individual worms from twenty-six Fasciola populations was performed. Flukes collected from a single host

represent each population. The table is divided into two sections from where the sample is collected based on province.

Populations Host Area Province Total flukes F. gigantica F. hepatica Heterozygous

P2B Buffalo Lahore Punjab 16 16 - -







P26C Cattle Lahore Punjab 20 20 - -

P1G Goat Lahore Punjab 4 4 - -






P3B Buffalo Loralai Balochistan 11 11 - -



P17C Cattle Murgha Kibzai Balochistan 12 3 6 3




P21S Sheep Murgha Kibzai Balochistan 15 3 11 1

P22S Sheep Murgha Kibzai Balochistan 3 - 3 -

P23S Sheep Loralai Balochistan 1 - 1 -

P24S Sheep Loralai Balochistan 3 - 3 -

P25S Sheep Loralai Balochistan 8 - 7 1

Total 305 238 56 11

RESULTS

32

4.2.3. Species identification

All the 53 Fasciola flukes obtained from buffaloes and goats from central, northern and

eastern regions of Punjab showed the fragment pattern of Fg both in PCR-RFLP and

multiplex PCR for pold and pepck genes, respectively (Table 5), and they were identified as

F. gigantica

RESULTS

33

Table 4.2: Profiles of Fasciola flukes used in this study

Host ID Host

species

Number

of flukes

Nuclear DNA Mitochondrial DNA species

Pepck Pold nad1 Accession No. cox1 Accession No. nad1+cox1

B8 Buffalo 4 Fg Fg PAK-nad1Fg2

PAK-cox1Fg17 PAK-Fg27 F. gigantica

Fg Fg PAK-nad1Fg11


Fg Fg PAK-nad1Fg12


Fg Fg PAK-nad1Fg2 PAK-cox1Fg2 PAK-Fg18 F. gigantica


PAK-cox1Fg5

PAK-Fg9 F. gigantica

Fg Fg PAK-nad1Fg10

PAK-cox1Fg2


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1




PAK-cox1Fg4


Fg Fg PAK-nad1Fg14


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1





Fg Fg PAK-nad1Fg10

PAK-cox1Fg2


Fg Fg PAK-nad1Fg2




PAK-cox1Fg1


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1








Fg Fg PAK-nad1Fg13

PAK-cox1Fg2



Subtotal 7 25

G1 Goat 4 Fg Fg PAK-nad1Fg3

PAK-cox1Fg1


RESULTS

34

Fg Fg PAK-nad1Fg1

PAK-cox1Fg1


Fg Fg PAK-nad1Fg4

PAK-cox1Fg1




PAK-cox1Fg1


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1


Fg Fg PAK-nad1Fg2

PAK-cox1Fg2




PAK-cox1Fg1


Fg Fg PAK-nad1Fg6

PAK-cox1Fg1


Fg Fg PAK-nad1Fg2

PAK-cox1Fg2




PAK-cox1Fg1


Fg Fg PAK-nad1Fg15

PAK-cox1Fg1


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1




PAK-cox1Fg3


Fg Fg PAK-nad1Fg1

PAK-cox1Fg7


Fg Fg PAK-nad1Fg1

PAK-cox1Fg3




PAK-cox1Fg1


Fg Fg PAK-nad1Fg3


Fg Fg PAK-nad1Fg1

PAK-cox1Fg8




PAK-cox1Fg1


Fg Fg PAK-nad1Fg16


Fg Fg PAK-nad1Fg1

PAK-cox1Fg1



Subtotal 7 28

Total 14 53

RESULTS

35

4.2.4. Haplotype distribution of F. gigantica mt-ND-1 locus

The haplotype frequencies present at the individual population level were analyzed separately

from 20 selected F. gigantica populations (Figure 10). Only three populations (P8B, P12G,

and P18C) each containing between 7 and 8 worms, showed relatively high frequencies of

multiple haplotypes. These three populations contained 7, 3, and 13 haplotypes (Figure 10).

In contrast, single haplotypes predominated in 17 populations, each containing between 4 and

20 worms (Figure 10). Three of these populations (P13B, P7B, and P17C) contained 6

haplotypes; six populations (P2B, P14B, P15B, P16B, P19B, and P26C) had 5 haplotypes;

three populations (P4B, P6G, and P10G) had 4 haplotypes; four populations (P1G, P9G, P3B,

and P11G) had 3 haplotypes; and one population (P5B) contained only one haplotype (Figure

10).

Among all 20 populations twenty six haplotypes of the F. gigantica mt-ND-1 locus were

identified. The split tree analysis shows at least two distinct clades (Figure 11). Six

haplotypes (H13, H26, H4, H19, H9, and H20) in Clade I, were present only in Balochistan.

The remaining 20 haplotypes were in clade II, with 8 haplotypes (H17, H21, H14, H10, H12,

H5, H7, and H6) predominating in Balochistan. Contrastingly, the six haplotypes (H17, H21,

H14, H10, H12, H5, H7, and H6) were more common in Punjab. In addition, four equally

shared haplotypes (H2, H3, H11, and H23) were present in clade II.

RESULTS

36

.

Figure 4.4 Relative allele frequencies of twenty F. gigantica populations from Punjab (A) and Balochistan (B) provinces of Pakistan Each pie

chart displays the individual population, and each haplotype in the pie chart is represented by a different color codes. The pie chart circle

represents the population l distribution, and their frequency comes from each of the twenty-six haplotypes as indicated on the insert table. The

populations are also linked to the location from where they were collected.

RESULTS

37

Figure 4.5: Haplotypes generated from 20 F. gigantica populations with split tree of 26 mt-ND-1. The tree was constructed with the UPGMA

method in the Jukes-Cantor model of substation in the splitsTrees4 software. The appropriate model of nucleotide substitutions for UPGMA

analysis was selected by using the jModel test 12.2.0 program. The pie chart circles in the tree represent the haplotypes in two different clades

and the size of each circle is proportional to the frequency in the population.

RESULTS

38

4.2.5. Mitochondrial haplotypes detected from Pakistan

Seventeen nad1 (PAK-nad1Fg1 to 17), 17 cox1 (PAK-cox1Fg1 to 1) and 30

nad1+cox1 (PAK-Fg1 to 30) haplotypes from the 53 F. gigantica in Pakistan were detected

(Table 4.2).

The MJ network constructed for the nad1 haplotypes (Figure 4.5A) revealed that PAK-

nad1Fg1 and Fg2 were predominant in Punjab. They were found from both buffaloes and

goats. Four nucleotide substitutions were observed between the main two haplotypes. PAK-

nad1Fg16 and Fg17 detected from a goat (Table 4.2) showed seven nucleotide substitutions

from PAK-nad1Fg2. The other nad1 haplotypes were derived from the two main haplotypes

with one to three nucleotide substitutions.

PAK-cox1Fg1 and Fg2 were the predominant haplotype for the cox1 haplotypes, with

three nucleotide substitutions observed among them. They were found both in buffaloes and

goats. PAK-cox1Fg15 and Fg16 found in goats showed four and five nucleotide substitutions

between Fg2. Other haplotypes had one or two nucleotide substitutions when compared with

this predominant haplotype (Figure 4.5B).

PAK-Fg1 was the predominant in concatenated nad1+cox1 haplotypes and found in

both buffaloes and goats. PAK-Fg5 and Fg18 were also found in both the animals. The rest of

the haplotypes were found in either in buffalo and goat (Figure 4.5C).

RESULTS

39

Figure 4.6: Median joining network based on the mitochondrial (A) nad1, (B) cox1 and (C) nad1+cox1 haplotypes of Fasciola gigantica from

Pakistani origin. Black colour indicates the haplotypes from Buffaloes and white colour haplotypes from the goats. Small circles are the median

vectors needed to connect the haplotypes.

RESULTS

40

Table 4.3: Diversity indices of F. gigantica populations in Pakistan based on the nucleotide sequences of mt-DNA genes

Gene Population N S H Π SD

nad1 Buffalo 25 14 11 0,00533 0,00049

Goat 28 17 9 0.00668 0.00135

Total 53 26 17 0.00650a 0.00071

cox1 Buffalo 25 12 11 0,00612 0,00047

Goat 28 10 8 0.00493 0.00125

Total 53 18 17 0.00606 0.00065

nad1+cox1 Buffalo 25 26 17 0.00569b 0.00038

Goat 28 27 16 0.00590

b 0.00115

Total 53 44 30 0.00630a 0.00059

N: number of flukes accessed;S: number of variable sites; h:number of haplotypes;π; nucleotide diversity a,b

Statistically non-significant (P> 0.05), others were significant ( P < 0.05).

Table 4.4: Pairwise fixation index (FST values) of mitochondrial genes between F. gigantica populations Goats and Buffaloes

Gene Buffalo Goat

nad1 0.12931

cox1

0.16914

nad1+cox1 0.14657

Statistically all values were significant (P<005).

RESULTS

41

4.2.6. Phylogenetic analysis of F. gigantica mt-ND-1 locus

To examine the phylogenetic relationship between 26 different haplotypes of the F.

gigantica mt-ND-1 locus network and maximum likelihood trees were produced (Figure 4.7).

Sixteen haplotypes were comparatively rare as they collectively made less than 5 % of the

total reads. Five of these haplotypes (H15, H16, H18, H22, and H25) were only found in

Punjab, and they were present in four populations; whereas 11 haplotypes (H5, H7, H9, H12,

H13, H14, H17, H19, H20, H21 and H26) were present in Balochistan, originating from 5

populations (Figure 4.7). The rest of 10 haplotypes were shared between Punjab and

Balochistan, making more than 95 % of the total reads. Three of these haplotypes (H1, H8,

and H24) predominated in Punjab and were present in 13 populations in total, including 9

populations from Punjab and 4 from Balochistan (Figure 4.7). Three haplotypes (H4, H6, and

H10) were predominated in Balochistan and were present in 14 populations in total, including

5 from Balochistan and 9 from Punjab (Figure 4.7). In contrast, four haplotypes (H2, H3,

H11, and H23) were equally shared between Punjab and Balochistan (Figure 4.7); these were

present in a total of 19 populations, 13 coming from Punjab and 6 from Balochistan.

RESULTS

42

Figure 4.7: Network tree of 26 mt-ND-1 haplotypes sequenced from 20 F. gigantica populations. The tree was generated with the Neighbor-

Joining method in the Network 4.6.1 software (Fluxus Technology Ltd).All unnecessary median vectors and links were removed with the star

connections .Each pie-chart displaced the haplotype distribution and their frequency comes from each of the 20 populations as indicated on the

insert table. The color of haplotype circle represent the percentage of sequence reads generated per population shown in the insert table. The

number of mutations (in red) separating adjacent sequence nodes was indicated along with the connecting branches and the length of the lines

connecting the haplotypes is proportional to the number of nucleotide changes (for interpretation of the references to color in this figure legend.

RESULTS

43

4.2.7. Genetic diversity of F. gigantica mt-ND-1 locus

The values of haplotype diversity were found ranging from 0.727 to 0.960 and

nucleotide diversity from 0.00643 to 0.03118 within different populations with a high level of

genetic diversity at both haplotype and nucleotide levels (Table 4.4). For haplotype and

nucleotide diversity, the overall values between populations were 0.917 and 0.02466

respectively. This analysis confirms that high level of genetic diversity found in Pakistani F.

gigantica populations.

RESULTS

44

Table 4.5: Genetic diversity estimation of mtND-1 haplotypes identified from 20 populations of Fasciola gigantica in Pakistan. The table

shows these values both within populations and between the total populations.

Populations

No. of

Illumina

MiSeq reads

No. of

haplotype

generated

Haplotype

diversity

(Hd)

Segregating

sites (S)

Nucleotide

diversity (∏)

Mutation

parameter based

on S (Θ S)

Mean No. of

pairwise difference

(k)

P1G 82376 3 0.750 4 0.00643 0.00473 2.000

P2B 82495 5 0.857 7 0.00827 0.00692 2.571

P3B 12776 3 0.727 6 0.00935 0.00639 2.909

P4B 10532 4 0.800 6 0.00815 0.00581 2.533

P5B 12240 1 N/A

P6G 13237 4 0.818 21 0.02938 0.02236 9.136

P7B 46363 6 0.882 22 0.02326 0.02057 7.235

P8B 58506 7 0.900 21 0.02811 0.01877 8.743

P9G 79854 3 0.727 20 0.03118 0.02130 9.697

P10G 81470 4 0.818 21 0.02806 0.02236 8.727

P11G 71509 3 0.727 20 0.03118 0.02130 9.697

P12G 24854 3 0.727 5 0.00779 0.00532 2.424

P13B 92620 6 0.882 22 0.02194 0.02057 6.824

P14B 62230 5 0.857 21 0.02425 0.02077 7.543

P15B 92220 5 0.857 22 0.02591 0.02176 8.057

P16B 89654 5 0.857 21 0.02425 0.02077 7.543

P17C 57043 6 0.882 24 0.02383 0.02244 7.412

P18C 10428 13 0.960 21 0.03055 0.01770 9.502

P19B 11258 5 0.857 22 0.02591 0.02176 8.057

P26C 10730 5 0.857 21 0.02425 0.02077 7.543

Total 1002395 26 0.917 24 0.02466 0.01628 7.670

RESULTS

45

4.2.8 Nucleotide diversity

The nucleotide diversity (π) values for nad1, cox1, and nad1+cox1 were compared between

F. gigantica populations of buffaloes and goats from Punjab. Although a higher π value was

observed in nad1 gene of F. gigantica populations from goats than in buffaloes, the opposite

result was found in cox1 gene. Moreover, no significant difference was obtained between the

populations of both the animals for nad1+cox1 gene and indicated that there is no essential

difference between the F. gigantica populations from both animals when focusing on the

diversity of mitochondrial DNA (Table 4.5).

In contrast the Fst values between the F. gigantica populations of goats and buffaloes

of all the genes were significant indicating that F. gigantica populations from both animal

species were different (Table 4.6).

RESULTS

46

Table 4.6: Diversity indices of F. gigantica populations in Pakistan based on the nucleotide sequences of mt DNA genes

Gene Population N S H Π SD

nad1 Buffalo 25 14 11 0,00533 0,00049

Goat 28 17 9 0.00668 0.00135

Total 53 26 17 0.00650a 0.00071

cox1 Buffalo 25 12 11 0,00612 0,00047

Goat 28 10 8 0.00493 0.00125

Total 53 18 17 0.00606 0.00065

nad1+cox1 Buffalo 25 26 17 0.00569b 0.00038

Goat 28 27 16 0.00590

b 0.00115

Total 53 44 30 0.00630a 0.00059

N: of flukes accessed ;S: number of variable sites ; h:number of haplotypes π nucleotide diversity

a,bStatistically non-significant (P> 0.05), others were significant (P< 0.05).

RESULTS

47

Table 4.7: Pair-wise fixation index (FST values) of mitochondrial genes between F.

gigantica populations from Buffaloes and Goats

Gene Buffalo Goat

nad1

0.12931

cox1

0.16914

nad1+cox1 0.14657

Statistically all values were significant (P<0.05).

4.2.9 Comparison of mitochondrial nad1 haplotypes with those from the reference

countries

The MJ network constructed for the nad1 haplotypes (Figure 4.8) revealed that all the

haplotypes detected from Pakistan were included in haplogroup A. One of the predominant

haplotype, PAK-nad1Fg2 had an identical with the F. gigantica haplotypes from India (ND1-

E6), Nepal (Fg-ND1-N1), Myanmar (Fg-M15), Bangladesh (Fg-NDI-Bd9), and Thailand

(Fg-ND1-Thai13). PAK-nad1Fg13 had identical sequence with the haplotypes from India

(ND1-E7) and Myanmar (Fg-M16). Again, PAK-nad1Fg10 was identical to ND1-IN14 from

India. The other predominant haplotype, PAK-nad1Fg1 and its derivative haplotypes as well

as PAK-nad1Fg16 and 17 were independent from the reference haplotypes. The nucleotide

diversity suggests that the diversity of the Pakistan F. gigantica population was the highest π

value among the populations in haplogroup A (Table 4.7).

RESULTS

48

Figure 4.8: Median joining network based on the mitochondrial nad1 haplotypes of F.gigantica in Pakistan and other countries.

Fasciola flukes from Pakistan are shown in black color, each circle indicates a single haplotype. Small circles are the median vectors

which are needed to connect haplotypes. The haplotype codes are shown within or adjacent to the circles. Numbers on each circle and

node indicate the number of flukes and the number of substitution sites, respectively. Label No. indicates only one fluke and one

substitution.

RESULTS

49

Table 4.8: Diversity indices of Fasciola gigantica within haplogroup A based on the nucleotide sequence of ND- genes

Populations N S H Π SD

Pakistan 53 26 17 0,00650 0,00071

India 132 41 43 0.00252* 0,00023

Bangladesh 21 14 10 0,00312 0,00075

Nepal 20 16 10 0,00366 0,00088

Myanmar 13 7 6 0.00225* 0,00072

N: number of flukes accessed; S: number of variable Sites; h: number of haplotypes; π: nucleotide diversity; SD: standard deviation

*Statistically non-significant between the identical letter (P>0.05) ,others were significant (P <0.05) . F. gigantica from Thailand (n =

1) and Indonesia (n = 1) in haplogroup A was excluded from the calculation.

50

CHAPTER 5

DISCUSSION

In the present study, we collected the samples of liver fluke from slaughtered goats,

sheep, cattle, and buffaloes in three different abattoirs of Punjab and Balochistan provinces of

Pakistan to find out the presence of single and multiple genotypes in a single host and to

determine the spread of F. gigantica mt-ND-1 haplotypes. On the basis of deep amplicon

sequencing approach, these Fasciola spp were identified by using metabarcoded rDNA ITS-2

genetic marker of 483 bp. From three different geographical locations, a population of liver

flukes was collected from single infected animal, haplotype diversity in 20 F. gigantic

populations were shown by deep amplicon sequencing technique by using metabarcoded mt-ND-

1 genetic marker of 311 bp. The multiple infections and the spread of F. gigantica mt-ND-1

haplotypes were examined. We also analysed Fasciola samples collected from goats and

buffaloes from the slaughter house (PAMCO), Lahore, Punjab to use the most reliable genetic

marker; polymerase delta (pold) and phosphoenolpyruvate carboxykinase (pepck) genes, for the

identification of Fasciola spp and to use cytochrome C oxidase subunit 1 (cox1) and

mitochondrial NADH dehydrogenase subunit 1 (nad1) genes to determine the spread out of F.

gigantica in the Indian subcontinent.

The collected flukes were of different sizes macroscopically. There were smaller flukes

similar to F. hepatica, larger flukes similar to F. gigantic and some in intermediate forms (Figure

7). It is very confusing to identify the Fasciola spp on the bases of morphological structure,

because the intermediate forms are look like one of their parents. The morphology of the flukes

in our study agrees with the flukes collected from Vietnam (Nguyen et al. 2009). Deep amplicon

sequencing has highlighted the capability to identify the parasitic species (Melville et al. 2020).

The present study provided the proof-of-concept for hybridization of the both (Fasciola spp.)

first time in Pakistan. From live Fasciola spp, we observed about 100 to 200 eggs in 1 µl of

normal saline (Figure 8), our results of egg microscopy showed resemblance to the study done by

(Admassu et al. 2015). We have collected thousands of egg from a single liver fluke that may

produce up to 20,000 eggs in 24 hour time.

To investigate parasite species dynamics, co-infections, hybridization, multiplicity of

infection and the level of gene flow, in addition to assessment of population responses to drug

treatments, Next generation genomic sequencing provides solutions (Sargison et al. 2019).

DISCUSSION

51

Various PCR methods; RFLP, quantitative PCR, multiplex PCR and single-strand conformation

polymorphism PCR have been described to amplify the mt-ND-1 and rDNA ITS-2 regions for

cataloging determination (Ai et al. 2011). After that, these are throughput, hence relatively

exorbitant, and possibly more prone to error. In contrast, high data deep amplicon sequencing or

metabarcoded DNA derived from parasite populations by means of Illumina Miseq approach is

comparatively cost-effective and probably less prone to error. The study of blood protozoan and

nematode parasite technique has transmuted (Avramenko et al. 2015; Chaudhry et al. 2019); in

the study of trematode parasite societies has the capability to initiate new areas. In the UK, this

method has been used to study the multiplicity of infection of Calicophoron daubney infection

(Sargison et al. 2019). To identify trematode parasitic species (the tremobiome), the use of

primers binding to conserved site and analysis of up to 600 bp sequence reads permits. In a

single Mi-seq run, the use of barcoded primers allows a huge numbers of different parasite

samples to be pooled and sequenced by making the technology appropriate for high output

analysis. It is possible to run three hundred eighty four sample at once on a single Illumina Mi-

seq flow cell by multiplexing barcoded primer combinations help to reduce the cost (Chaudhry et

al. 2019; Sargison et al. 2019; Shahzad et al. 2019). In the present study, firstly the presence of

F. gigantica was confirmed and then identifies the prevalence of single or multiple haplotypes

per infection (multiplicity of infection) and demonstrating the spread of F.. gigantica alleles by

using high throughput deep amplicon sequencing of metabarcoded DNA.

Fasciola spp. are cosmopolitan parasites that are widely distributed throughout the world

(Mas-Coma. 2004). F hepatica is more common temperate (moderate) regions, while the

prevalence of F. gigantica is the highest in subtropical and tropical zones where cattle and sheep

are raised (Mas-Coma et al. 2014). Livestock plays an important role in agrarian based economy

of Pakistan. There are several reports of Fasciola infections in Pakistan, frequently F. hepatica

exists commonly in large and small ruminants (Ashraf et al. 2014; Ijaz et al. 2009; Shahzad et al.

2012). A few reports indicate the presence of both F. gigantica, F. hepatica and hybrid (Akhtar

et al. 2012; Iqbal et al. 2007). On the other hand, all previous reports are based on adult and egg

morphology with inadequate molecular justification of species identity. In the present study of

the dynamics of Fasciola spp. in Pakistan, ITS-2 rDNA sequence data confirmed the existence of

F. hepatica, F. .gigantica and hybrid types with F. gigantica being the predominant species

(Table 1) concurring with a earlier study (Chaudhry et al. 2016).

DISCUSSION

52

In the final host from which the parasites were derived, the predominance of single mt-

ND-1 haplotypes in 17 out of 20 (85%) populations, F. gigantica suggests a single genetic

emergence of infections. In contrast, the presence of high proportions of multiple mt-ND-1

haplotypes in just 3 of 20 (15%) populations suggests multiple infections. The clonal lineage of

the haplotypes in most of the F. gigantica populations is similar to the situation that has been

described in F. hepatica (Beesley et al. 2017; Vilas et al. 2012), implying similar importance of

asexual reproduction of the intermediate snail hosts to the population genetics of the two species.

The clonal lineage might arise because the life cycle of F. gigantica involves uneven disease

transmission intensity and, or, abundance of intermediate hosts; as has been described for F.

hepatica, where single miracidia infects the G. truncatula mud snails giving rise to multiple,

genetically identical cercariae (Beesley et al. 2017). These may aggregate with little mixing on

the pasture before being ingested by the definitive host. These conditions would be more likely if

the prevalence of infection in the intermediate hosts is low, and snail habitats are small and

isolated, as is likely the case in Pakistan, where long-term muddy regions tend to be found in

association with irrigation pumps or ponds. An alternative explanation for the clonal lineage of

the F. gigantica could be a little population bottlenecking arising due to the influences of the

wide range of climatic conditions throughout the year on intermediate snail host infection (Rana

et al. 2014).

The present study confirms a high level of genetic diversity in F. gigantica in the region,

even higher in Balochistan (Table 2), implying the capacity for reproduction in the definitive

host through meiosis during cross-breeding. A similar situation has been described in F. hepatica

infection (Beesley et al. 2017; Vilas et al. 2012; Zintl et al. 2015). However, a low level of

infection (Dar et al. 2011; Rondelaud et al. 2011). And clonal lineage in snails could give rise to

a potential low population bottlenecking effect, raising questions about how genetic diversity

might be maintained in F. gigantica.

The movement of livestock is frequent in Pakistan and contributes to the high levels of

parasitic gene flow (Ali et al. 2018). In the present study, ten haplotypes were spread between

populations. Three of those haplotypes predominated in the Punjab and three in the Balochistan

provinces. In contrast, four haplotypes were equally shared between the populations from both

provinces. This suggests that animal movement play a significant role in maintaining a high level

DISCUSSION

53

of gene flow in F. gigantica, for example translocating animals to a new region could introduce

new parasites as well as exposing the definitive hosts to different residents’ parasite populations.

In summary, we used an mt-ND-1 marker to provide first insights into the genetic

diversity and multiplicity of F. gigantica infection in Pakistan. Our findings suggest that most of

the hosts were predominantly infected with parasites of identical mt-ND-1 haplotypes, consistent

with clonal multiplication within the snails. A high level of genetic diversity was seen in F.

gigantica isolated from naturally infected small and large ruminants, showing that sexual

reproduction with cross-fertilization occurs within the definitive host. At range of geographic

locations, mt ND-1 haplotypes were identified highlighting the role of animals movements in the

spread of infectious disease. With reference to development of sustainable parasite control

strategies to investigate host parasite relationships and to examine influences of intermediate

hosts, co-infections and climate change on the epidemiology of F. gigantica, our study provides

proof of concept for method that could be used.

Historically, it has been suggested that F. gigantica might originate and spread by water

buffalo (Bubalus bubalis) and zabu cattle (bos indicus) in the Indian subcontinent (Peng et al.

2009) around 5000-6000 BC. Zabu cattle and water buffaloes were domesticated in the

Northwestern region of subcontinent (Pakistan) (Bradley et al. 1996; Loftus et al. 1994; Tanaka

et al. 1996), the spread of F. gigantica might play a significant role due to the free movement of

Zabu cattle and water buffaloes before the creation of Pakistan. Over the past few decades, high

levels of the animal movement have been reported in domestic ruminants in the Indian

subcontinent (Kelley et al. 2016; Vilas et al. 2012). The animal movement patterns differ

between farms and F. gigantica infects domestic animals, wild animals and humans potentially

enables the spread of this parasite (Rojo-Vázquez et al. 2012). In contrast, the farmers rear

multiple species of animals to meet their livelihood in the Indian subcontinent (Devendra. 2007).

The mixed farming system might perform a significant role in the spread of F. gigantica. Hence

genetic analyses are needed to understand the corresponding origin and spread of F. gigantica

infections, aid in the development of parasite control strategies (Hayashi et al. 2016).

The current study revealed that at least two origins of F. gigantica in Pakistan with

reference to the neighboring countries. Seventeen nad1haplotypes derived from 53 F. gigantica

flukes. In haplotype group A, four F. gigantica haplotypes of the present study had a close

relationship with the haplotypes from India, Bangladesh, Nepal and Myanmar. The most likely

DISCUSSION

54

explanation of these haplotypes maybe expanded in Pakistan from India, suggests the spread of

the F. gigantica (Hayashi et al. 2016; Hayashi et al. 2015). The MJ network indicates that the

haplotypes detected in India were more diverse than Pakistan supports the hypothesis of the

expansion of these haplotypes from India to Pakistan. In contrast, fourteen Pakistani haplotypes

were not shared with any neighboring countries suggest independent origin, or possibly come

from neighboring Middle East countries where genetic analysis of F. gigantica has never been

conducted. Further studies from different areas of Pakistan, as well as neighboring Middle East

countries, will be required to reveal the origin and dispersal direction of these haplotypes.

In the present study, we have assessed the diversity between buffaloes and goats derived F.

gigantica in the Punjab province of Pakistan. Seventeen nad1 and cox1 haplotypes derived from

53 F. gigantica flukes. The MJ network data suggest that there was significant difference

between F. gigantica of buffalo and goat might be the difference due to host immunity (Haroun

et al. 1986; Piedrafita et al. 2004; Roberts et al. 1997) or due to the variances in the geographical

position of these two hosts in the province of Punjab (Pakistan). Generally, the lowlands of

Punjab are more prone to flooding and reported to be highly populated with buffalo, in

comparison, goats are resided in higher areas or keep moving in different areas due to human

travelling (Afshan et al. 2014).

In summary, this study provides preliminary perceptions into the origin and spread of F.

gigantica in Pakistan and the neighboring countries of the Indian subcontinent. We have also

described the genetic diversity of buffalo and goat derived F. gigantica suggests significant

difference between two host.

Overall, the study provides a benchmark and opens new avenues for more detail analysis in this

region. It might be helpful to involve higher samples size, more host species from different areas

to get more conclusive results of the genetic diversity of F. gigantica between buffaloes, goats,

sheep and cattle as well as their possible spread patterns in the country and the subcontinent.

CONCLSUSIONS

Stop animal movement from one area to another area for the control of spread disease.

To prevent hybridization/ co-infection to stop co-grazing of large and small ruminants.

Quarantine must be followed.

DISCUSSION

55

Early diagnose may prevent the spread and emergence of disease by the use of deep

amplicon sequencing technique.

56

CHAPTER 6

SUMMARY

Fasciolosis is an important neglected worldwide disease of ruminant livestock and

humans. Fasciola spp. not only causes billion of dollar production losses annually in farm

animals. According to WHO, liver fluke is also an emerging food-borne zoonotic parasite in

humans with 180 million at risk and 2.4 million people infected. The genus Fasciola comprises

of two important species; Fasciola gigantica and Fasciola hepatica that are found in different

zones where F. hepatica resides in temperate region, while F. gigantica is found in tropical

region. In addition, with the presence of hybrid of the two species has been seen in subtropical

area. The ingestion of contaminated herbage with infective metacercariae, animals become

infected with liver flukes, where parasite need snail species of Galba truncatula of Lymnaeidae

family as intermediate hosts to complete their life cycle.

In farm animals, F. gigantica are responsible for more than 3 billion US$ losses of

production annually and a wide-extent zoonotic disease, even though, the emergence and spread

of the trematodal species are poor. The multiplicity of F. gigantica infection and it’s spread is

potentially influenced by multiple factors including abundance of suitable intermediate hosts,

atmospheric environments favoring to complete the life cycle, and translocation of infected

animals or free-living parasite stages between regions. By explaining the development of

tremabiome, metabarcoding sequencing approach to interpret the numbers of F. gigantica

genotypes per infection and parasite spread patterns rely on genetic characteristics of the

mitochondrial NADH dehydrogenase 1 (mt-ND-1) locus. We collected F. gigantica from three

slaughter houses in the Balochistan and Punjab, provinces of Pakistan, and the present study

showed high level of genetic diversity in 20 F. gigantica population resultant from small and

large ruminants consigned to slaughter in both provinces. This implies that F. gigantica can

reproduce in its definitive hosts through meiosis involving cross- and self-breeding, as described

in the closely related species, F. hepatica. The genetic diversity between the 20 populations

which was derived from different locations also illustrated its impact in animal movements on

gene flow. Our results demonstrated that 85 % of the hosts from which the parasite populations

were derived, showed single haplotypes predominance of F. gigantica. This is consistent with

clonal reproduction in the intermediate snail hosts.

SUMMARY

57

In identification of two species; F. gigantica and F. hepatica, an expert analysis is

required due to the same structural characteristics of egg or adult or intermediate or hybrid

flukes. Therefore, PCR for the two nuclear DNA markers; DNA polymerase delta (pold),

phosphoenol pyruvate carboxykinase (pepck), were employed for accurate diagnosis of hybrid

forms from F. gigantica and F. hepatica. For phylogenetic studies of fasciola flukes, the

nucleotide sequence of cytochrome C oxidase sub unit 1 (Cox1) and mitochondrial NADH

dehydrogenase sub unit 1(nad1) were analyzed. Fifty three flukes were collected from goats and

buffaloes from the slaughterhouse (PAMCO, Lahore, Punjab, Pakistan). Our results of pold and

pepck genotyping displayed that the samples were of F. gigantica. Further studies are needed to

analyze the flukes from other Provinces of Pakistan to estimate the prevalence of fasciolosis in

bovine and caprine.

58

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PHYLOGENETIC ANALYSIS, DRUG RESISTENCE PATTERN AND