Microarray technology has enabled us to study thousands of genes simultaneously and this has become beneficial to understand the infectious process of pathogens, diagnostics, and host-pathogen interactions. Using microarray technology, studies were done to understand pathogenesis, the host-pathogen interaction. Bovine species were the ones most frequently used that focused on normal physiology, pregnancy, lactation, and parturition. The response of bovine tissues to various pathogens using bovine microarray found that 182 differentially expressed (DE) genes were identified between normal and Bovine Spongiform Encephalopathy (BSE) infected tissues (Benna, 2016).
Majority of those had ontology functions, some were involved in 26 different Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, five were associated with synapse function, and three with calcium iron regulation (Benna, 2016).
Protein microarray has paved a way for veterinarians to use in diagnosing patients as they are able to capture molecules on a microarray chip and target them, the most common protein microarray used is the antibody microarray. Antibody microarray detects antigens and antibodies in blood samples to discover new disease biomarkers, monitor disease states, and monitor response therapy (Benna, 2016).
Protein microarray was used on Brucella melitensis proteins that found eighteen antigens differentially recognized in infected and non-infected goats and ten antigens differently expressed in humans and out of that only two were found to be common for both in naturally infected goats and humans (Benna, 2016).
This indicated different immune response were shown in goats and humans for Brucella melitensis. Antibody microarray technology is not the only microarray to be used in disease diagnostics, there is also the use of tissue microarray that involves the removal a small amount of tissue with a hollow needle, on multiple tissues constructed in the same place.
There is also the use of tissue microarray with disease diagnosis that involves the removal a small amount of tissue with a hollow needle, on multiple tissues constructed in the same place, but it is mostly used to validate diagnosis and prognostic markers.
Foodborne Salmonella spp continues to infect the US human population with poultry and chicken being identified as the leading source. The primary variations of salmonella that come from poultry are salmonella enterica, salmonella Kentucky, salmonella typhimurium, and salmonella Heidelberg. Not much is known about their physiological and metabolic responses to the environment they had during the poultry production cycle (Ricke, 2013). Using a Salmonella Typhimurium DNA microarray to compare hybridizations with serovars and strains of Salmonella enterica and Salmonella bongeri. They found that there was variability in pathogenicity genes among serovars that aligned with their corresponding host (Ricke, 2013).
Within any production, but in this case poultry production feeds and food matrices we need to remember that there are chemicals involve that may allow Salmonella spp to grow and metabolize. Comparing transcriptome responses of Salmonella Typhimurium growing in the presence of glucose-lysine-based Maillard reaction products (MRP), reaction between amino acids and reducing sugars when heat is applied to foods or feeds, generated under low water activity, conditions that are similar in food or feed production (Ricke, 2013). Concluded that there was limitation to MRP activating genes that are part of the glyoxylate carbon pathway that is used by Salmonella under carbon limitation conditions, this was viewed in over 15-fold increases in starvation-induced genes. Using Salmonella microarrays, we discovered their response to a combination of thermal with acid intervention steps as well as alternative carbon pathways when it grows on MRP.
Microarray technology is not only useful with diagnosing and detecting diseases in animals but there is a benefit within the animal production for both the consumer and the owner. Microarray technology has been mostly used to study growth and the development of skeletal muscle in pigs but there have been studies done on transcriptomic profiles associated with meat quality attributes such as water-holding, tenderness, and intramuscular fat (IMF). Pigs that were given a restricted protein diet showed accumulation of IMF in both red and white muscles with increasing gene expressions of genes involved in substrate turnover raising glycolytic and oxidative capacity in those muscles (Pena, 2014).
The tenderness in commercial pigs was shown to be connected with 63 genes connected to cell cycle regulation, energy metabolism, muscle development and 151 differentially expressed genes overrepresented in processes related to growth and development, myofibrillar and proteolytic genes (Pena, 2014). These results suggesting that there is a correlation between slow oxidative fiber with an increase lipid oxidation capacity with meat tenderness. IMF adipocytes that are different from other fat deposits, exhibit a more immature metabolic phenotype compared with subcutaneous, under the skin, and perirenal, adjacent to the kidney, adipocytes. They demonstrate lower mRNA levels and activities of enzymes involved in lipogenesis, lipolysis, and transcriptional regulation of lipid metabolism (Pena, 2014).
The regulation of mRNA levels is done by non-coding RNAs known as microRNAs (miR) and are important to regulating functions in muscles. Studies were conducted to assess the role of miR in regulating pig muscle development and function using several approaches and one of those was miR microarrays (Pena, 2014). They discovered that the four or five most abundant miRs are muscle specific that include miR-1, miR-206, and miR-133. The studies done show that expression patterns of each physiological stage are unique. With all these studies conducted there are limitation with microarray technologies such as muscle tissue being a mixture of muscle, adipose, nervous cells, etc. that their different proportions may alter gene expression. Another limitation is how much comparison is required to limit the number of false positive results (Pena, 2014).
Within cattle production the most important thing is cattle’s fertility rate and how to improve it, and to do this we need to understand the relationship between the expressions of genes in tissues and their sequences for fertility. Studies using different types of microarray technology during ovarian follicle development, oocyte maturation, and embryo development
During ovarian follicle development the follicles grow and in later stages are susceptible to manipulation which is the area of focus. Microarrays were utilized to study the progression of ovarian follicle development and show the changes in gene expression associated with a decrease in Follicle-stimulation hormone (FSH) dependence and an increase in luteinizing hormone (LH) dependence as dominant follicles continue to develop after selection (Evans, 2008). The study concluded that mRNA expression for genes known to be induced by FSH in granulosa cells increased mRNA expression for LH granulosa cells are associated with the increase of dominant follicle cells (Evans, 2008).
During embryo development precise control of gene expression is important as there are several critical developmental events occurring. The use of cDNA microarray is increasing so that global gene expression change in cattle embryos are examined. Using cDNA microarrays comparing mRNA expression across a wide range of biological processed in vivo or in vitro that suggest in vitro embryos are inferior to developmental competence compared to in vivo cultured because of deficiency of transcription and translation (Evans,2008).