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Listeria has been divided into seven species with two distinct groups. Among which the Listeria monocyotgenes and Listeria ivanovii are haemolytic and pathogenic for animals. The Listeria murrayi and Listeria grayi are nonhaemolytic, rarely isolated and considered to be non pathogenic. Among which the genus L. monocytogens, being the cause of septicaemia, abortion and CNS infections in a wide range of animal species including humans.

History
L.monocytogenes first described by Murray (1926) who named it as bacterium monocytogenes because of characteristic monocytosis infection in laboratory animals. It was renamed Listerella hepatolytica by Pirie (1927) and the present name given by him in 1940. The Listeria momnocytogenes was first isolated by Gill (1929) from sheep.
Natural Habitat
Listeria species are widely distributed in the environment and can be isolated from soil, faeces, plants, decaying vegetation and silage (pH 5.5) in which the bacteria can multiply. Silage is commonly implicated in outbreaks of listeriosis in cattle and sheep. In poor quality silage the listerial numbers may reach 107 cfu/kg of silage. Asymptomatic faecal carriers occur in man and many animal species. L.monocytogens can be excreted in bovine milk. Human foods associated with listeriosis in man include soft cheeses, milk and poultry meat.

General Terminologies in Livestock Production

Meat is considered as well balanced diet because it is good source of macro and micro nutrients.

Macronutrients-required in large quantity in body i.e proteins, fat and carbohydrates.

Micronutrients-required in lesser quantity by human body i.e vitamins, minerals and fibers.

Organ meat like liver is a good source of glycogen, viatm-A, B1 and nicotinic acid.

Fresh meat is unprocessed.

Raw meat is a fresh meat undergone chilling and freezing.

Refrigeration and rapid cooling can delay the onset of rigor mortis

Cells Contain 4 Major Types of Giant Molecules (Macromolecules, Polymers)

Carbohydrates

Lipids

Proteins

Nucleic Acids

BIOLOGICAL POLYMERS ARE MADE FROM ABOUT 60 SMALL BUILDING BLOCKS

Cells contain thousands of types of giant molecules (macromolecules, polymers)

Polymers are macromolecules made from a single building block molecule Most of the macromolecules are made from about 60 types of small building block molecules

Most macromolecules are linear: building blocks linked head to tail- a few have branches (some polysaccharides)

This is what you would get if you heated cells in hydrochloric acid overnight at 110 degrees C:

Major Histocompetibility Complex (MHC) is a closely linked cluster of genes which have codes for cell surface proteins known as MHC molecules. MHC molecules were previously called as HLA molecules. Since these molecules were first discovered on the leucocytes, these were called human leukocyte antigen or HLA molecules.

Major Histocompatibility Complex (MHC) is a closely linked cluster of genes which have codes for cell surface proteins known as  MHC molecules. These molecules have very important role in presentation of processed antigens to the T cells in initiation of an immune response as T cells recognize an antigen only when it is presented along with MHC molecule. These are highly polymorphic and are the major barrier to organ/tissue transplantation. All vertebrates have MHC. MHC differs among members of a species and are thus called alloantigens. MHC participates in the development of both humoral and cell-mediated immune responses.

Introduction
The emergence and spread of antimicrobial resistance has changed the landscape of infectious disease treatment, creating an urgent need for new diagnostic and therapeutic approaches4’7. Traditional phenotypic antimicrobial susceptibility testing, while remaining the gold standard, requires 24-72 hours for results and provides limited insights into resistance mechanisms. Limited turnaround time is often a constraint that requires empirical use of antibiotics, potentially driving the propagation of other resistance emergence as well as suboptimal patient outcomes. Thanks to mass spectrometry, clinical microbiology has greatly benefitted through the rapid detection of pathogens. However, the application is far broader than species identification. The integration of multiple omics fields like proteomics, metabolomics, genomics, and transcriptomics through mass spectrometry provides unprecedented means to unravel, predict, and combat antimicrobial resistance (AMR) on a molecular level. The use of a multiomics approach is demonstrated to show that AMR is a complex phenotype that arises from the intersection between genetic mutations, variations in gene expression, metabolic differences, and changes in protein structures that all act in unison to affect bacterial survival in the presence of antibiotics. The conversion of raw mass spectrometry outputs into clinical insights amenable to decision-making is dependent upon bioinformatics. Through the use of sophisticated computational methodologies, such as machine learning and network analysis, bioinformatics provides the means to incorporate heterogeneous omics datasets. Through this approach, resistance-related biomarkers can be identified, predictions for therapeutic efficacy can be made, and new targets for intervention can be identified. The intersection between high-resolution mass spectrometry, broad-based omic profiling, and strictbioinformatics provides a powerful platform for addressing the intractable challenge of antimicrobial resistance.

Introduction

Measurement of pH of a solution and preparation of different types/strength of buffers are common practices in a laboratory, particularly in the Biochemistry and Molecular Biology laboratories. Therefore, in this chapter you will be acquainted with the procedures of measuring pH of a solution as well as preparation of some of the commonly used buffers in a laboratory.

Potential or Power of Hydrogen Ion (pH)

Measurement of pH of a solution is measuring the molar concentration of hydrogen ion [H+] in the solution, which is an indication of the acidity or basicity of the solution. The symbol pH stands for “power of hydrogen” and numerical value for pH is just the negative logarithm of the molar concentration of hydrogen ions [H+]. The ionic product of water (Kw ) is the basis for the pH scale. The total hydrogen ion concentration from all the sources and it can be experimentally measured.

The pH scale designates the concentration of H+ (and thus of OH−) in an aqueous solution, which ranges between 1.0 M H+ and 1.0 M OH−. The term pH is defined by the expression

Thus, the ionic product of water makes it possible to calculate the concentration of H+, with given concentration of OH−, and vice versa. The value of 7 for pH of a neutral solution is not an arbitrarily chosen figure; it is derived from the absolute value of the ionic product of water. A solution having pH greater than 7 is basic, and the concentration of OH− is greater than that of H+. A solution having a pH less than 7 is acidic.

Introduction
• A cell is the most basic structural and functional unit of life. These are of two types:
i) Prokaryotic cells– Prokaryotes are those cells which lack a membrane bound nucleus and other membrane bound cell organelles. These cells are primitive cells. Examples, bacterial cells, archaeal cells.
ii) Eukaryotic cells– Eukaryotes are those cells which have distinct membrane bound organelles. These are advanced cells. Example, animal cells, plant cells, fungi.
• A microorganisms (from the Greek: mikros, “small” and organism’s, “organism”) are those small living organisms which cannot be seen with naked eyes. These are of two types:
i) Single cell– Organism made up of a single cell.
ii) Multi-cellular– Organism made up of multiple cells.
Shape and Arrangement of Bacterial Cells
• Prokaryotes display following shapes
• Spherical cells called Cocci
• Cylinders called rods or Bacilli
• Coma shaped called Vibrio
 

Introduction
The advent of antibiotics, beginning with penicillin in 1941, transformed medicine by rendering bacterial infections treatable [1]. However, antimicrobial resistance (AMR) has emerged as a profound threat, enabling bacteria to survive in the presence of drugs designed to inhibit or kill them and these are rooted in ancient microbial ecosystems evidenced by resistome genes in 30,000-year-old permafrost [2]. AMR has been exacerbated by human practices: approximately 50% of antibiotic prescriptions are inappropriate, 70% of global antibiotics fuel agriculture, and environmental pollution creates resistance hotspots [1]. By 2025, AMR directly causes 1.3 million deaths annually, with economic losses projected at $100 trillion by 2050 [1]. Priority pathogens, including carbapenem-resistant Enterobacteriaceae (CRE), methicillin-resistant Staphylococcus aureus (MRSA), and colistin-resistant strains via mcr-1, challenge last-resort therapies, particularly in low-resource settings [3]. This chapter delivers a technically extraordinary exploration of AMR, structured into genetic, biochemical, and evolutionary mechanisms, each elaborated with molecular precision and step-by-step clarity for learners. Genetic alterations provide the DNA-level foundation, biochemical pathways execute molecular defenses, and evolutionary forces drive adaptation and dissemination. It ensures scientific rigor and broad appeal for students, researchers, clinicians, and policymakers.
Historical Context and Global Burden
AMR emerged shortly after antibiotics’ introduction, with penicillin-resistant S. aureus identified by 1942 due to ß-lactamase production [1]. The 1960s

SEX IS VERY COSTLY

Large amounts of energy required to find a mate and do the mating: specialized structures and behavior required

Intimate contact provides route for infection by parasites (AIDS, syphillis, etc.)

Genetic costs: in sex you pass on only half your genes to your children

Males are an expensive luxury- in most species they contribute little to rearing offspring

But There are Some Advantages

More genetic diversity: more potential for survival of species when environmental conditions change

Shuffling of genes in meiosis (random separation of homologous chromosomes)

Crossing-over in meiosis (see below)

Fertilization (genes from 2 individuals brought together)

ALL MOLECULES MOVE CONTINUOUSLY BY SIMPLE DIFFUSION

Heat energy causes molecules to move randomly (sometimes called Brownian motion)

If the concentration of molecules is different in 2 regions (this produces a concentration gradient), diffusion will cause molecules to move from a region of high concentration to one of low concentration

The higher the concentration gradient the more rapid the net diffusion

Diffusion evens out the concentrations so they are equal everywhere (maximum entropy)

If 2 different substances have the same concentration gradient, usually one will move faster than the other

Differences in speed between molecules with the same concentration gradient are given in terms of diffusion constants

A substance with a high diffusion constant moves faster than one with a low diffusion constant

In general, large molecules move slower than small molecules

Diffusion across a membrane is called permeability, and membrane diffusion constants are called permeability constants

A fair number of practical breeding experiments were done in ancient times

People knew there was a connection between sex and reproduction

The idea had developed that “like begets like”

By selecting certain plants and animals and breeding them many domestic varieties of plants and animals had been developed

Example: corn was developed from a wild grass in Mexico and Central America, probably about 5000 years ago

149 of the top 150 plant crops were domesticated by primitive man

Metabolic fingerprinting and profiling provide powerful approaches for investigating global biochemical changes within biological systems. This chapter explains the principles of metabolic fingerprinting and profiling and distinguishes between broad, untargeted characterization and targeted analysis of selected metabolites. It discusses experimental design, sample preparation, analytical platforms, data preprocessing, normalization, statistical analysis, and multivariate approaches used to identify meaningful metabolic patterns. Techniques such as principal component analysis and related statistical methods help reveal differences between biological conditions. The chapter highlights applications in disease investigation, agricultural research, environmental studies, food analysis, and biotechnology, while emphasizing the importance of reproducible analytical procedures and appropriate interpretation of complex metabolomic datasets.

Metabolism - sum total of all chemical reactions in living cells

Catabolic reactions - degrade macromolecules and other molecules to release energy

Anabolic reactions - used to synthesize macromolecules for cell growth, repair, and reproduction

Can divide metabolism into 4 groups: carbohydrates, lipids, amino acids, nucleotides.

Metabolomic databases provide essential information for identifying metabolites, interpreting experimental results, analyzing pathways, and understanding biochemical relationships. This chapter introduces major databases used in metabolomics and explains their roles in modern biological research. Resources such as KEGG, BRENDA, HMDB, MetaboLights, METLIN, and LIPID MAPS provide information on metabolites, enzymes, pathways, structures, spectra, diseases, and experimental datasets. The chapter discusses their applications in metabolite identification, pathway analysis, biomarker discovery, systems biology, and translational research. It also considers challenges including data volume, database completeness, continuous updating, standardization, and integration with other omics resources.

Metabolomic research depends on analytical technologies capable of detecting and characterizing large numbers of chemically diverse metabolites. This chapter introduces the principal analytical platforms used for metabolite analysis, with emphasis on mass spectrometry and nuclear magnetic resonance spectroscopy. Gas chromatography–mass spectrometry, liquid chromatography–mass spectrometry, capillary electrophoresis–mass spectrometry, and NMR are examined in relation to metabolite separation, identification, and quantification. The chapter also considers sample preparation, analytical workflows, advantages and limitations of different platforms, and complementary approaches for achieving broader metabolome coverage. These techniques provide the analytical foundation for metabolic profiling, biomarker discovery, pathway analysis, and systems-level biological investigations.