Gene Marker Identification Targeting Toll-Like Receptor 4 (TLR4), Breast Cancer 1 (BRCA1), and Adenosine Triphosphatase 1 Alpha 1 (ATP1A1) Genes:
Assessing Their Association With Subclinical Mastitis Cases in Dairy Water Buffaloes, Bubalus bubalis

Thesis Proposal

Cyndi Candelaria Biendima
Patricia Malapit Cabatit

Submitted to the
Department of Biology
College of Arts and Sciences
University of the Philippines Manila
Padre Faura, Ermita, Manila

In partial fulfilment of the requirements for
Undergraduate Thesis (BIO 200)

TABLE OF CONTENTS

Title Page1
Table of Contents2
Introduction3
Review of Related Literature6
Proposed Methodology14
Presentation of Results20
Literature Cited22
Line Item Budget26
Project Timeline27

1.0 INTRODUCTION

1.1 Background of the Study

Cases of intramammary infections such as mastitis in water buffaloes contribute to large annual losses in milk production and net profit for smallholder farmers in the Philippines. Social and economic factors might prevent households from diagnosing, treating, and eliminating from circulation those animals or animal products, such as milk, that are afflicted with mastitis or which came from individuals afflicted with mastitis; this is especially true in the case of the asymptomatic subclinical mastitis, which tends to become chronic and difficult to eradicate by conventional antimicrobial therapies (Brouillette & Malouin, 2005; Ng et al., 2010).

With the advent of technology comes new techniques in identifying and treating diseases such as mastitis through more rapid, accurate, and efficient means, such as fluorescent dye staining or the utilization of electrical fields (Dohoo & Meek, 1982). By far, genetic approaches to the treatment of this disease have been of great interest, primarily because of the lack of information regarding their application in the field of clinical and subclinical mastitis.

A prospective application of this genetic approach is the identification of molecular markers in the genome of the water buffalo, Bubalus bubalis. Previous studies suggest that an assessment of gene polymorphisms in afflicted animals could lead to the implication of such genes in the detection of the disease (Liu et al., 2012). Such a diagnostic technique could prove invaluable in reducing the incidence of subclinical cases of disease and infection in livestock herds. The mitigation of net profit losses by herders of dairy water buffaloes may be economically significant if screening individual animals for mastitis can be backed with conclusive genetic evidence, particularly in subclinical cases wherein the effects of the disease are not translated in the phenotype, making the disease harder to recognize without first analyzing the milk product.

The aim of this research is to provide new information regarding the association of three genes in the water buffalo (the toll-like receptor 4 gene, the breast cancer 1 gene, and the adenosine triphosphatase 1 alpha 1 gene) with the occurrence of subclinical mastitis in water buffaloes. Further studies may aim to innovate techniques for the rapid and accurate detection of subclinical mastitis in water buffalo herds based on the new genetic correlations that this study aims to elucidate.

1.2 Statement of the Problem

Can the toll-like receptor 4 gene (TLR4), the breast cancer 1 gene (BRCA1), and the adenosine triphosphatase 1 alpha 1 gene (ATP1A1) serve as genetic markers for subclinical mastitis in dairy water buffaloes (Bubalus bubalis)?

1.3 Research Objectives

General Objective:
To determine if the toll-like receptor 4 gene (TLR4), the breast cancer 1 gene (BRCA1), and the adenosine triphosphatase 1 alpha 1 gene (ATP1A1) can serve as genetic markers for subclinical mastitis in dairy water buffaloes (Bubalus bubalis)

Specific Objectives:
To measure the frequency of gene polymorphisms in the toll-like receptor 4 gene (TLR4) gene, the breast cancer 1 gene (BRCA1), and the adenosine triphosphatase 1 alpha 1 gene (ATP1A1) in healthy and mastitic dairy water buffaloes
To test the significance of gene polymorphisms in the toll-like receptor 4 gene (TLR4) gene, the breast cancer 1 gene (BRCA1), and the adenosine triphosphatase 1 alpha 1 gene (ATP1A1) in subclinical mastitis cases in dairy water buffaloes

1.4 Significance of the Study

Technological advances continue to allow us to improve on diagnostic and preventative techniques, among others. Subclinical diseases are especially important because of their asymptomatic and chronic nature. New information on the association of gene markers with subclinical mastitis can provide a foundation for future research on innovative disease prevention or treatment programs. A reduction in the occurrence of mastitis in dairy water buffaloes can have a great impact on smallholder Filipino farmers who rely on buffaloes and their milk products for their livelihood.

1.6 Scope and Limitations

The proposed study will focus on the measurement of single nucleotide polymorphism frequencies in three genes of Bubalus bubalis: the toll-like receptor 4 gene (TLR4), the breast cancer 1 gene (BRCA1), and the adenosine triphosphatase 1 alpha 1 (ATP1A1) gene. The statistical measures taken to test the significance of gene polymorphism frequencies and related values in association with mastitis will be the sole determinant in assessing whether each of the three genes is a suitable genetic marker for subclinical mastitis. The various extrinsic causes of mastitis and the degree of infection of each subject will not be considered in the discussion of the results. The significance of TLR4, BRCA1, and ATP1A1 relative to one another regarding their association with mastitis will not be assessed. Neither will the effects of other markers – whether morphological, chromosomal, biochemical, or molecular – aside from the aforementioned three be investigated. The source of test DNA will be from buffalo’s milk; the resulting effects of extracting DNA from buffalo’s blood will not be considered, and their differences waived. The subjects under study shall all be lactating female dairy water buffaloes of the subspecies Bubalus bubalis bubalis, born and raised in confinement at the Philippine Carabao Center, Nueva Ecija, Philippines, under authorization granted by the same institution.

2.0 REVIEW OF RELATED LITERATURE

2.1 The Water Buffalo, Bubalus bubalis

Water buffalo (Bubalus bubalis) is the biggest member of the Bovidae family, which comprises all artiodactyl ungulates possessing non-deciduous horn cores and sheaths and includes antelopes, cattle, sheep and goats (Gatesy et al., 1992; Jesser et al., 2008). Water buffalo are massive and barrel-chested, however with short legs that are usually dirty white in color up to knees with thin body hair that is ashy gray or black, adults almost hairless and their skin varies with weather condition that ranges from slate-gray to black. They have relatively long tail which is bushy at its tip (Jesser et al., 2008; Macdonald, 2001). They are actively feeding in late afternoons and evening. They eat wider range of forage than cattle and also chew the bark of trees to obtain minerals. It usually spends time in pools or bodies of water to wallow to prevent intolerable high body temperature due to midday heat because of their fewer sweat glands. Wallowing cakes the animal with mud, thus protecting them from insect bites. Usually it uses its horn as a shovel to increase the mud coverage (Jesser et al., 2008; Macdonald, 2001). Usually, males are larger than females. Also, males are very much darker than females and the male horns are thicker, but female horns are longer. Water buffalos are very protective of their young and females will form a protective line on front of the calves when they sense threat. Females also tend to stay in the herd in which they are born while males disperse in their third year (Jesser et al., 2008; Macdonald, 2001). Female water buffalos have the longest gestation period among the bovids. It is usually 10 to 11 months, and in line with this, a female can only produce one calf every two years. Typically a female can bear one calf, but it can also bear twins. Nursing period lasts from 6 to 9 months (Macdonald, 2001). There are two types of water buffalo recognized: riverine-type and swamp-type buffalo. The riverine-type buffalo has 50 chromosomes with curled horn whereas the swamp-type buffalo has 48 chromosomes with swept-back horn. The two subspecies can interbreed and have a fertile progeny (Jesser et al., 2008). The present study will deal with riverine-type buffalos. This type is usually found in Indian continent, and is mostly used for dairy and meat (Hufana-Duran et al., 2003).

2.2 Economic Importance of the Water Buffalo

Locally known as the carabao or kalabaw, water buffalos are utilized by Filipino farmers for their milk and meat, as well as for mechanical power such as in ploughing. The importance of this species in the Philippine setting is indeed notable in smallholder mixed-farming systems in many agriculturally-invested towns (Gundran & More, 1999). They provide a critical source of meat and milk for household consumption as well as profit, and their hide can be treated for domestic or industrial use (Mingala & Gundran, 2008; Ng et al., 2010).

According to Gundran & More (1999), the importance of this species was recognised by the Philippine government in 1981 with the establishment of the Philippine Carabao Center (PCC), which was then known as the Philippine Carabao Research and Development Center (PCRDC). The national water buffalo development program and the PCC were institutionalised in 1992. Despite substantial development efforts, the total Philippine water buffalo population declined by an estimated 7.1% from 2.8 million animals in 1981 to 2.6 million animals in 1994 (Gundran & More, 1999). “In contrast, the water-buffalo population in the world is reported to have grown by 22.3% during this same period to 148.5 million animals in 1994. This negative growth rate in the Philippines has been attributed to the relatively low productivity of these animals, to high slaughter rates and to high mortality rates due to disease among neonates and adult animals”, report Gundran & More (1999) in their observational study of the health and growth of water buffalo calves in Nueva Ecija, Philippines.

2.3 Mastitis: Its Causes and Effects

Mastitis is a bacterial disease that induces inflammation of the mammary gland which, together with physical, chemical and microbiological changes, is characterized by an increase in the number of somatic cells in the milk and pathological changes in the mammary tissue (Brouillette & Malouin, 2005; Gianneechini et al., 2002). This can lead to tissue necrosis in regions where milk-secreting alveolar cells are damaged. In addition, milk production by the infected animal is reduced and is of a lower quality, containing less casein and more serum proteins as well as host cells (Brouillette & Malouin, 2005). Many factors such as pathogens, genetic factors, poor management practice and health of the dairy cattle cause mastitis (Yuan et al., 2012).

Mastitis can be classified based on the symptoms. Clinical mastitis is observable and causes flakes, clots or clumps in the milk and the infected animal is often off feed, running a temperature or acting lethargic (Yuan et al., 2012). On the other hand, subclinical mastitis, often called as hidden mastitis, shows no physical symptoms and can only be diagnosed via specialized tests; however it can still affect the yield of milk. Also, it infects greater number than clinical mastitis. It is estimated that in every 1 clinical mastitis case in a herd, 15-40 subclinical cases are present (Ogorevc et al., 2009). It should also be noted that subclinical mastitis should be treated immediately because it can develop into clinical mastitis (Sharma et al., 2011).

Subclinical mastitis increases the economic loss by suppressing the milk yield and milk quality. It is always related to low milk production, altered milk consistency, low protein content and high risk of contamination since it may have pathogenic organisms. The low quality of milk is due to the decrease of lactose, α-lactalbumin, and fat in milk due to the decreased synthetic activity in the mammary tissue. High level of SCC is also related to shorter shelf-life and undesirable final product due to the enzymatic activities of the somatic cells.

2.4 Somatic Cell Score

Somatic cell count (SCC) is one of the techniques used to determine the level of occurrence of subclinical mastitis in bovines. There are some indirect ways to determine SCC like California Mastitis Test (CMT) and Wisconsin Mastitis Test (WMT), however, recently, automated devices are used for rapidly determining the SCC of milk samples like the Coulter Milk Cell Counter and the Fossomatic 2, the former of which accomplishes its task by counting particles as they flow through an electric field, whereas the latter utilizes a fluorescent dye stain to count the number of particles. The current technological advances have paved the way for routine screening of cattle milk samples (Dohoo & Meek, 1982).

Somatic cells present in the samples are mainly the milk-secreting lining epithelial cells that have been regularly shed from the lining of the gland and leukocytes that have entered the mammary gland in response to injury of infection. During the inflammation, majority of the somatic cells present are neutrophils due to its influx in response to the infection. The normal SCC in milk would be lower than 1x105 cells/mL while bacterial infection can cause it to increase to above 1x106 cell/mL (Sharma et al, 2011).

The amount of neutrophil polymorphonuclear (PMN) leukocytes increases due to its nature being the second line of defense against mammary gland infection. However, in bovine, the phagocytic ability of PMN of milk can consume milk fat globules and casein which may lead to decomposition of milk. Also, blood monocytes which became macrophages and lymphocytes play an important role in immune response against invading bacteria, and also they add to the number of SCC (Sharma et al, 2011).

Apart from mastitis, there are other factors that affect the SCC. It is important to correctly interpret the SCC because it might just mean that other factors are actually contributing to its number. One of the factors is the stage of lactation, wherein SCC increases with the progressing lactation regardless of whether the bovine is infected of not. This said elevation is linked to the animal’s innate immune response in preparation for calving and to enhance the mammary gland defense mechanism at critical calving time. Another factor is age and breed. Various studies showed that SCC increases as the age increases due to an increase in prevalence of infection in older bovines. It is also noted that high-producing breeds has higher presence of SCC/mL in milk. Also, season and stress affect the number of SCC. During winter, SCC is generally lower compared to SCC in summer. This is due to the favorable temperature in summer for bacterial growth as well as the humidity. Meanwhile, stress due to milking techniques, environmental and injury affects the SCC by producing free radicals that are known to damage cells, causing attraction of leukocytes to the said damages cells, thus increasing the SCC (Sharma et al, 2011).

In line with this, somatic cell score (SCS) is used to interpret the SCC more accurately because it eliminates the effect of lactation days and period of sampling on SCS. From SCC, SCS can be computed with the use of equation SCS = log2[SCC/100,000)+3 (Wang et al., 2007). SCS conforms to the normal bell-shaped frequency distribution while SCC is strongly skewed. SCS is thus more reliable to use in statistical analysis because mean SCS can be interpreted as a median while mean SCC is higher than median and there is no consistent relationship between the mean and median. Likewise, SCS has greater power to distinguish between diseased and healthy cows than SCC (Shook, 2001). Studies have shown that mastitis is the most important cause of an elevated SCS, making the latter an excellent quantitative substitute trait for mastitis. The relationship between SCS and SCC is given in Table 1 below.

Table 1. The relationship between somatic cell score (SCS and somatic cell count (SCC) (Sharma et al., 2011) SCS Category | SCC (cells/mL) | | Midpoint | Range | 0 | 12,500 | 0 – 17,000 | 1 | 25,000 | 18,000 – 34,000 | 2 | 50,000 | 35,000 – 70,000 | 3 | 100,000 | 71,000 – 140,000 | 4 | 200,000 | 141,000 – 282,000 | 5 | 400,000 | 283,000 – 565,000 | 6 | 800,000 | 566,000 – 1,130,000 | 7 | 1,600,000 | 1,131,000 – 2,263,000 | 8 | 3,200,000 | 2,263,000 – 4,525,000 |

2.5 Microbial Causes of Mastitis

Reporters have cited coliforms and coagulase-negative staphylococci as the bacterial agents predominantly associated with cases of clinical and subclinical mastitis in Nepal (Ng et al., 2010; Dhakal et al., 2007). Mastitis-inducing organisms are classified into two groups: contagious and environmental pathogens. Contagious pathogens include Staphylococcus aureus and Streptococcus agalactiae which generally causes a great increase in SCC. On the other hand, environmental pathogens, which include Streptococcus dysgalactiae, Streptococcus uberis, Corynebacterium bovis and Coagulas-negative Staphylococcus, cause relatively low elevation in SCC. With ampicillin and tetracyclines proving to be marginally effective against these pathogenic bacteria, enrofloxacin is now the antibiotic of first choice for mastitis treatment in Nepal (Dhakal et al., 2007). In Egypt, maternal mastitis has been recognized as the major problem in buffalo productivity due to the high mortality rate of the calves in the first 3 months of life (Akhtar and Ali, 1994), even though the buffalo has been traditionally considered less susceptible to mastitis than cattle (Bansal et al., 1995; Sayed-Ahmed, 2010; Wanasinghe, 1985).

Brouillette & Malouin (2005) have reported that Staphylococcus aureus can provoke clinical mastitis but more frequently causes subclinical mastitis, which tend to be more difficult to eradicate by conventional antimicrobial therapies. This explains why mastitis constitutes a major challenge to dairy producers. More research needs to be performed in order to develop new prophylactic and therapeutic approaches that counteract S. aureus pathogenesis leading to intramammary gland infections (Brouillette & Malouin, 2005).

2.6 Prevalence and Risk Factors of Subclinical Mastitis

A recent study by Salvador et al. (2012) on the prevalence and risk factors of subclinical mastitis (SCM) in B. bubalis from Nueva Ecija revealed that SCM prevalence was 42.76%, recurrence was 75.03%, and susceptibility was higher in buffaloes younger than 6 years old. Dams younger than 3 years old have a 76% probability of having SCM, whereas those aged 3 years old have an 82% probability. Both age and lactation length were recognized as factors in the occurrence of SCM (Salvador et al., 2012), but Dohoo & Meek (1982) pointed out that the most important factor affecting SCC is the infection status of the entire population, and that in comparison, other factors have only a minor effect. Bovine SCC of uninfected individuals range from 113,000 to 251,000 cells/mL depending on the cow’s age (Dohoo & Meek, 1982). Cows harbouring commensals have SCCs at an average of 227,000 cells/mL, and cows harbouring major pathogens produce, on average, cell counts over 600,000 cells/mL. The California Mastitis Test (CMT) is a commonly used rapid test for subclinical mastitis that detects somatic cell nuclear material or SCNM, relying on a threshold of 300,000 cells/mL (Ng et al., 2010 and Radostitis et al., 1994).

2.7 Gene Marker Method of Studying Subclinical Mastitis

Bovine mastitis caused by Staphylococcus aureus has been studied in mice using histopathological methods (Brouillette & Malouin, 2005). Another method of assessing mastitis cases is by identifying gene markers. Gene markers are “tags” that can be part of the gene, a primer, or introns. These markers have been used widely in different bovines to identify and associate them with different diseases. Polymorphisms in the gene of interest can be used to predict susceptibility to subclinical mastitis. Gene products might be impaired by single nucleotide polymorphisms, or SNP) (Banerjee et al., 2012). Gene markers are also used to assist in the selection of the potentially quality breeds because it increases the rate of the yields as an important trait. By using statistical methods, gene markers can be identified whether it is significantly associated with a trait or not (Hogeveen, 2005).

2.8 Toll-Like Receptor 4 Gene (TLR4)

Toll-like receptors (TLRs) are a family of at least 11 proteins that function as pathogen-recognition receptors that initiate an inflammatory response upon ligation by conserved motifs on invading pathogens (Hyakkoku et al., 2010; White et al., 2003). TLRs are highly conserved from Drosophila to humans and share structural and functional similarities. TLR4, the first TLR to be discovered, is located at chromosome 8 and is estimated to be 13,309 bases long. It is specifically implicated in signal transduction events induced by lipopolysaccharide (LPS) found in most gram-negative bacteria. A study conducted by Goldammer et al. (2004) revealed that mastitis only increases the amount of mammary mRNA of TLR4 in affected areas, which indicates a localized induction of TLR4 mRNA depending on the site of infection. An association may therefore be inferred between TLR4 and subclinical mastitis, with TLR4 as a potential gene marker for the disease (White et al., 2003).

2.9 Breast Cancer 1 Gene (BRCA1)

BRCA1 is involved in the processes of DNA damage repair, cell cycle regulation, transcriptional regulation, and other pathways implicated in the maintenance of genome stability. The bovine BRCA1 gene has been mapped at chromosome 19 (BTA19) and estimated to be 68,894 bases long. It was located within or nearby the genomic region of SCS quantitative trait loci. Studies indicate that mutations in the gene encoding BRCA1 were associated with high risk of breast cancer in humans, but studies in bovine subjects are not as extensive. The BRCA1 sequence is also a better predictor of disease alleles (compared to polymorphism) than either the murine or the canine sequences (Yuan et al, 2012).

2.10 Adenosine Triphosphatase 1 Alpha 1 Gene (ATP1A1)

ATP1A1 is a gene that is located at chromosome 3 and estimated to be 22,768 bases long. It encodes for transmembrane proteins in the Na+/K+-ATPase family, in particular, the large catalytic subunit (alpha 1). Polymorphisms in the ATP1A1 gene have been associated with mastitis in dairy cattle (Liu, et al., 2012). It also a potential gene marker by virtue of the differences in the composition of the milk produced by mastitic buffaloes in comparison to that produced by healthy subjects. The most common effect reported is the dramatically increased Na+ and decreased K+ concentrations. To some extent, variations in the concentration of ions might be correlated with the inhibition of ATPase activity of the iron-transporting system. Na+/K+-ATPase is a transmembrane enzyme that utilizes ATP to transport 3 Na+ out and 2 K+ into a mammalian cell via the plasma membrane. This helps in establishing and maintaining ionic homeostasis in the cytoplasm, which is required for normal resting membrane potentials, various cellular activities, osmotic balance, and cell volume regulation. In addition, this enzyme plays a role in the mechanism of cell death and apoptosis, which is associated with a wide range of disease states. Therefore, the bovine Na+/K+-ATPase gene may be a potential gene marker for mastitis (Liu et al., 2012).

3.0 PROPOSED METHODOLOGY 3.1 Selection of Test Subjects and Sample Collection One hundred apparently healthy water buffaloes (Bubalus bubalis), all approximately at the same stage of lactation (second to third month post calving), will be selected from the herd of the Philippine Carabao Center (PCC) in Nueva Ecija, Philippines. The buffaloes will be managed as per the practices followed in the institute’s herd, and under supervision and authorization by representatives of the PCC. About 100 mL of pooled milk, equally collected from all four quarters of an individual water buffalo, will be stored in two clean 50 mL conical tubes. Samples will be immediately placed in an insulated ice chest containing crushed ice deter the deterioration of DNA. The milk samples will then be taken to the laboratory under insulation, with one tube from each subject containing fresh milk samples to be immediately processed for somatic cell count, and the other tube from the same subject to be stored at 20°C until time for DNA extraction and PCR (Murphy et al., 2002 and Sharif et al., 2007). Immediately after sample collection, 10 mL of each sample will be used to determine somatic cell count (SCC) using the Fossomatic™ FC Cell Counter. The somatic cell score (SCS) for each sample will then be determined using the following formula, SCS=log2(SCC100000+3) where SCC is somatic cells per millilitre. All SCS values will be recorded in Table 3. 3.2 Extraction of DNA from Milk Samples Total cellular DNA will be extracted from milk samples accordingly, based on the method of Murphy et al. (2002). Frozen milk samples will be thawed at room temperature prior to the execution of the following procedure. Fifty mL of each milk sample will be placed in a 50 mL conical tube and centrifuged at 2200 x g at room temperature for 5 minutes. After centrifugation, the fat layer and the supernatant will be aspirated and discarded, retaining only the bottom 1 mL of the supernatant as well as the pellet, composed of somatic cells and casein. These will be pipetted into a 1.5-mL microfuge tube. To this, 300 μL of 0.5 M EDTA at pH 8.0 and 200 μL of TE solution (10 mM Tris-HCl and 1 mM EDTA at pH 7.6) will be added, in order to dissolve casein. The solution will be subjected to vortex mixing to resuspend the pellet, after which it will be incubated at room temperature for 10 minutes, or until the tube contents have stopped changing from an opaque milky white to a slightly clear appearance as the casein micelles dissolve. Then, the solution will be centrifuged at 16000 x g at room temperature for 20 seconds. The supernatant will be aspirated and discarded, retaining only the bottom 100 μL, which contains somatic cells. The cells will be washed twice by refilling to 1.5 mL with TE buffer solution, vortexing, incubating, centrifuging, and removal of its supernatant as per the method described above. One hundred μL of digestion solution (40 mM Tris-HCl at pH 8.3, 50 mM KCl, 3 mM MgCl2, 1 μL of Tween 20, and 20 μL of Proteinase K at 20 mg/mL) will be added to the washed cells. The solution will then be incubated in a pre-heated incubator at 55°C for 3 hours. Two hundred µL of chloroform will be added to the DNA sample and will be mixed by gently inverting the tube several times. The DNA sample will be centrifuged again at 2500 to 4700 x g for 5 minutes. The upper aqueous layer will be aspirated and transferred to a new tube. Ice-cold 95% ethanol will be added to this solution until it is approximately thrice its original volume. The sample will then be inverted gently several times, and then incubated at -20°C for 10 minutes to allow the DNA to precipitate. The sample will then be centrifuged at 8000 x g or top speed in a microcentrifuge. The ethanol will be discarded by decantation and the resulting pellet will be resuspended in 0.5 mL TE buffer solution. Three hundred µL of 5 M ammonium acetate and 1 mL 95% ethanol will be added to resuspend the DNA for a second precipitation. It will be again incubated, centrifuged, decanted, and resuspended as per the method described above. The extracted genomic DNA will then be quantified using the NanoDrop UV-Vis Spectrophotometer. Samples will be diluted with TE buffer, as needed, to obtain the required concentrations for PCR described below. 3.3 Amplification of Target Gene Sequences Using Polymerase Chain Reaction Table 2. PCR primers for TLR4, BRCA1, and ATP1A1. (Liu et al., 2012; Wang et al., 2007; Yuan et al., 2012) Gene | Primers | Annealing Temperature (⁰C) | Product Size (bp) | Region | | Forward Primer | Reverse Primer | | | | TLR4 | 5′-AGG TTG ACT GGT CTC TTT G-3′ | 5′-ACA GTG GTA GAA CTC ATG C-3′ | 61.5 | 316 | Partial intron 1, exon 2, partial intron 2 | TLR4 | 5'-AGA CAG CAT TTC ACT CCC TC-3′ | 5′-ACC ACC GAC ACA CTG ATG AT-3′ | 62 | 382 | Partial exon 3 | BRCA1 | 5`-TGC AGT GGA AAT TCC AAA TAA ACT-3` | 5`-GAA TTA GAT CTT CAG CTA TGT GGC-3` | 60 | 209 | Exon 9 | BRCA1 | 5`-AGA GGA AAT CAT CTG GGT GTC C-3` | 5`-CCT TGT GCT TTT TAC CTG AGT GC-3` | 61 | 217 | Exon 10 | BRCA1 | 5`-CTT CAG AAC CTG TAC TTG TAA CC-3` | 5`-CAA GGA ATA TTT ACT GAG CAC C-3` | 54.5 | 321 | Intron 6 | ATP1A1 | 5ꞌ-ACA AAC AAA AGG GTC ACA ACA T-3ꞌ | 5ꞌ-CTT ACC CTA GAT CCT GGC TCA T-3ꞌ | 54 | 301 | Exon 3 |

The forward and reverse primers to be used as well as their annealing temperatures are recorded in Table 2 above. Polymerase chain reaction (PCR) using primers designed for TLR4 will be done after the method of Wang et al. (2007), BRCA1 primers after the method of Yuan et al. (2012), and ATP1A1 primers after the method of Liu et al. (2012). After DNA extraction, PCR will be performed in a total volume of 20 μL reaction mixture per primer, containing 50 ng genomic DNA, 1X buffer (100 mM Tris-HCl at pH 8.3, and 500 mM KCl), 0.25 μM primers, 2.0 mM MgCl2, 0.25 mM dNTPs, and 0.5 U Taq DNA polymerase. The thermal cycling process will vary per primer. The initial denaturation step for BRCA1 and ATP1A1 primers will be at 94°C for 5 minutes, whereas for TLR4 primers it will be at 95°C for 5 minutes. For TLR4 primers, this will be followed by 35 cycles of denaturation at 94°C for 30 seconds, annealing at either 61.5°C or 62°C (depending on which of the two primers are used; refer to Table 2) for 30 seconds, and extension at 72°C for 50 seconds. For BRCA1 primers, there will be 35 cycles of denaturation at 94°C for 30 seconds, annealing at either 60°C or 61°C (depending on which of the two primers are used; refer to Table 2) for 30 seconds, and extension at 72°C for 30 seconds. For ATP1A1 primers, there will be 34 cycles of denaturation at 94°C for 30 seconds, annealing at 54°C for 30 seconds, and extension at 72°C for 45 seconds. The terminal extension step for BRCA1 and ATP1A1 primers will be done at 72°C for 8 minutes, whereas for TLR4 primers it will be at 72°C for 10 minutes. After PCR amplification, 5 μL of the PCR products will be electrophorezed in 1.5% agarose gel containing 0.5X TBE as running buffer at 70 volts for 60 minutes and visualized under ultraviolet light. To ensure that amplification products are of the expected size, a 100-bp DNA ladder will be run simultaneously as a marker (Darwish et al., 2009). Presence of 321-, 209- and 217-bp DNA fragments indicate the presence of BRCA1 (Yuan et al., 2012), presence of 301-bp DNA fragments indicate the presence of ATP1A1 (Liu et al., 2012), and presence of 316- and 382-bp DNA fragments indicate the presence of TLR4 (Wang et al., 2007). This step verifies the successful amplification of the target genes.

3.4 Detection of Candidate Single Nucleotide Polymorphisms (SNPs) Using Restriction Fragment Length Polymorphism (RFLP) Analysis After the method used by Mitra et al. (2012), PCR-RFLP analysis of each PCR product for all three genes (TLR4, BRCA1, ATP1A1) will be carried out using the restriction enzymes (REs) appropriate. Twenty μL of the reaction mixture for each enzyme will be incubated at 37°C for 4 hours. The restriction fragments will then be resolved on a horizontal electrophoresis chamber by loading on 2% agarose gel with 1X TBE as running buffer. The ethidium bromide will be added to the agarose gel at 1 μL/100mL of gel. The gel will be run at 100 volts for 90 minutes. DNA fragments will then be visualized on an ultraviolet transilluminator, using either ethidium bromide staining or FastBlast DNA Stain, and then photographed. The differences in fragment lengths that will be yielded by the various restriction enzymes will indicate polymorphisms in a particular gene. The DNA bands of different patterns will then be sent to a separate institution for nucleotide sequencing. The genotypic and allelic frequencies of the polymorphisms can then be calculated for use in the proceeding statistical analyses of data. 3.5 Detection of Candidate SNPs Using Low Ionic Strength Single-Stranded Conformation Polymorphism (LIS-SSCP) Analysis Additional screening for polymorphisms for each of the three genes will be done using LIS-SSCP analysis, after the method of Liu et al. (2012). To 10 μL LIS loading solution (10% sucrose, 0.01% bromophenol blue, and 0.01% xylene cyanol FF), 2 μL PCR product will be added. The mixture will then be incubated at 98°C for 5 minutes, cooled on ice, and loaded onto a 12% polyacrylamide gel (acrylamide/bisacrylamide 29:1, v/v). Electrophoresis will be carried out using 1X TBE (45 mM Tris-borate, 1 mM EDTA) at 160 V for 15 hours. The resulting bands on the gel will be detected using silver staining. The DNA bands of different LIS-SSCP patterns will then be purified using an agarose gel DNA purification kit, cloned into a plasmid vector, and then sequenced. The genotypic and allelic frequencies of the polymorphisms can then be calculated for use in the proceeding statistical analyses of data. 3.6 Statistical Analyses As in the study of Liu et al. (2012), the frequency of alleles and genotypes, homozygosities (Ho), heterozygosities (He), polymorphism information content (PIC), effective number of alleles (Ne), and Hardy-Weinberg equilibrium at the mutation sites will be calculated using the POPGENE software, and the corresponding values for each gene locus will be recorded in Table 4. According to Yuan et al. (2012), PIC values less than 0.25 indicate low polymorphism, values between 0.25 and 0.5 indicate intermediate polymorphism, and values greater than 0.5 indicate high polymorphism. Allelic and genotypic frequencies corresponding to TLR4, BRCA1, and ATP1A1 will be recorded in Table 5 as well. One-way analysis of variance (ANOVA) will be used to test the differences between each of the determined genotypes and the somatic cell scores. If a genotype is found to be significantly associated with SCS, then the gene to which it corresponds may be implicated as a potential marker for the identification of subclinical mastitis in water buffaloes. Data will be presented as least squares means with associated standard error in Table 6. Statistical significance will be set at p < 0.05.

4.0 PRESENTATION OF RESULTS Table 3. Calculated somatic cell score (SCS) Sample Number | SCS | 1 | | 2 | | ... | | 100 | |

Figure 1. Results of agarose gel electrophoresis following PCR amplification

Figure 2. Results of agarose gel electrophoresis following RFLP analysis

Figure 3. Results of agarose gel electrophoresis following LIS-SSCP analysis

Table 4. Genetic diversity of SNPs in TLR4, BRCA1, and ATP1A1 Gene | SNP Loci | Ho | He | PIC | Ne | χ2 | TLR4 | Locus 1 | | | | | | | Locus 2 | | | | | | | … | | | | | | | Locus n | | | | | | BRCA1 | Locus 1 | | | | | | | Locus 2 | | | | | | | … | | | | | | | Locus n | | | | | | ATP1A1 | Locus 1 | | | | | | | Locus 2 | | | | | | | … | | | | | | | Locus n | | | | | | Table 5. Allelic and genotypic frequencies Gene | SNP Loci | Allelic Frequency | Genotypic Frequency | | | A | B | AA | AB | BB | TLR4 | | | | | | | | | | | | | | BRCA1 | | | | | | | | | | | | | | | | | | | | | ATP1A1 | | | | | | | Table 6. Effects of different genotypes on somatic cell score Locus | Genotype | Frequency | SCS (mean + SE) | | AA | | | | AB | | | | BB | | | | CC | | | | CD | | | | DD | | | | EE | | | | EF | | | | FF | | |

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6.0 LINE ITEM BUDGET

Transportation to Nueva Ecija | 4,000.00 PHP | California Mastitis Test (CMT) kits (30 pcs.) | 5,000.00 PHP * | Plastic bottles (120 pcs.) | 1,500.00 PHP * | Glass slides | 300.00 PHP * | Reagents for somatic cell count (xylene, methylene blue) | 1,000.00 PHP * | Eppendorf tubes (150 pcs.) | 3,000.00 PHP * | Reagents for DNA extraction (Triton X-100, EDTA, Tris, HCl, PBS, MgCl2, proteinase K) | 6,000.00 PHP * | Reagents and equipment for PCR | 4,000.00 PHP * | Reagents and equipment for agarose gel electrophoresis | 8,000.00 PHP * | Reagents and equipment for RFLP analysis | 5,000.00 PHP * | Miscellaneous | 5,000.00 PHP | | | TOTAL | 42,800.00 PHP |

* to be subsidized by the Philippine Carabao Center

7.0 PROJECT TIMELINE

Activities | Aug. 2013 | Sept. 2013 | Oct. 2013 | Nov. 2013 | Dec. 2013 | Jan. 2014 | Feb. 2014 | Mar. 2014 | Proposal Defense | X | | | | | | | | Ordering Reagents | | X | X | | | | | | Testing for SCM (CMT) | | | X | | | | | | Identifying Gene Markers | | | X | X | X | | | | Statistical Analysis | | | | | X | X | | | First Draft Writing | | | | | | X | | | Final Paper Writing | | | | | | | X | | Publishable Form and Poster Preparation | | | | | | | | X | Defense | | | | | | | | X |