eChapters

The research setting provides specific details about the location where a study is conducted. This study area typically encompasses a particular geographical region, such as a state, district, block, or gram panchayat, chosen according to the research requirements. The researcher must have a thorough understanding of the locality, including its communication methods, in order to effectively access all parts of the region for data collection.

In social science research, a clear comprehension of the characteristics, attitudes, and behaviours of the individuals within the study area is essential. Without this understanding, accurately conceptualizing, perceiving, and interpreting data becomes challenging. To obtain a comprehensive understanding of the implications and behavioural intricacies of the local people representing a broader community in the referenced study area, researchers must have a solid grasp of these factors. Therefore, this chapter critically analyses the socio-demographic background of the residents in a rural setting.

The term “research setting” denotes the context in which research inputs and elements are absorbed, interacted with, and mutually contribute to the system’s overall performance.

The research setting is crucial because it shapes and influences the interactions of various factors and components. Therefore, conducting a study on how farmers perceive persuasive issues and other topics requires a local context that takes into account the unique natural environment, demographics, crop ecology, institutional framework, and socio-cultural factors. For example, when writing a paper about the social behaviour of chimpanzees, it is important to include details about the research setting. This may include information such as where the chimpanzees were studied (in the wild or in captivity), the number of chimpanzees that were observed, whether they were part of the same social group, the geographic location, the time of the study, the season/weather conditions, the availability of resources such as food, water, and shelter, and any environmental factors that were present.

In the context of a thesis, theoretical orientation refers to the conceptual or theoretical framework or perspective that informs and shapes the overall approach and analysis of the research (Natalie, 2022). It involves selecting and adopting a specific set of theories, concepts, or models that provide a foundation for understanding and interpreting the research topic. The theoretical orientation helps to guide the methodology, and provide a coherent framework for organizing and analysing the data.

Theoretical orientation in a thesis serves several purposes. It helps to establish a theoretical basis for the study, providing a context for the research and connecting it to existing knowledge and theories in the field. It also helps to guide the selection of appropriate research methods and data analysis techniques. The theoretical orientation shapes the overall structure and content of the thesis, ensuring that the study is grounded in relevant theories and concepts and contributes to the existing body of knowledge. By adopting a specific theoretical orientation, the researcher can provide a clear and systematic framework for understanding and interpreting the findings of the study. This orientation also helps to establish credibility and validity for the research, as it demonstrates the researcher’s awareness of and engagement with the existing theoretical perspectives in the field.

This chapter addresses crucial terminology and concepts essential for effectively communicating the ideas of the current study. It lays the groundwork for empirical investigation and aids in the selection of predictor variables. Additionally, this section involves a scholarly and theoretical exercise that influences the operational definition and content of the research. It combines conceptual inputs, axiomatic inputs, logical discussions, and the pursuit of knowledge to construct a theory that aligns with the research objectives and designs.

Climate change is a complex and dynamic phenomenon that has significant impacts on agriculture, especially in terms of uncertainty and variability. Agricultural dynamics refer to the various factors that affect agricultural production, including climate, soil, water availability, pests, and diseases, as well as market forces and government policies. Climate change has significant impacts on agricultural dynamics. Variations in temperature, patterns of rainfall, and occurrences of extreme weather can influence crop yields and livestock production in both beneficial and detrimental ways (UCAR, 2021). The effects of climate change on farming can differ based on the geographical location and the specific agricultural practices employed (Wikipedia Contributors, 2019). For example, in some areas, increased rainfall may lead to increased crop yields, while in other areas, droughts may lead to crop failures and loss of income for farmers. Additionally, rising temperatures can cause reduced crop yields and decreased quality of some crops.

Uncertainty is a term used to describe a situation where there is a lack of information, knowledge, or predictability about a particular outcome or event. In agricultural dynamics, uncertainty can refer to a range of factors that can affect the production, distribution, and consumption of agricultural products. One of the most significant sources of uncertainty in agriculture is the weather. The productivity of crops can be significantly influenced by weather conditions, including rainfall and temperature and farmers need to effectively adjust their agricultural practices to adapt to these changing weather patterns (Guntukulaand Goyari, 2020). For example, droughts or floods can reduce crop yields, while frost or hail can damage crops(Lamaoui et al., 2018).

Significant Progress and Prospects

It is widely acknowledged that biofortification presents a promising and cost effective agricultural strategy to enhance the nutritional status of malnourished populations globally. Approaches to biofortification, including crop breeding, targeted genetic modification, and mineral fertilizer application, offer significant potential for combatting mineral deficiencies in human diets. The development of biofortified food crops with enhanced nutrient content such as iron, zinc, selenium, and provitamin A has shown promise in addressing micronutrient deficiencies prevalent in both developing and developed nations. Over the past decade, both national and international initiatives have made substantial contributions toward achieving these goals. These efforts have resulted in the release of biofortified varieties across various crops, including rice, maize, wheat, potatoes, vegetables, and millets. The majority of these varieties have been developed through conventional breeding methods without sacrificing crop yield, making them readily accepted by both growers and consumers.

One of the United Nations’ sustainable development goals is the cultivation of nutritionally rich crop varieties with heightened levels of micronutrients such as iron, zinc, calcium, total protein, lysine, tryptophan, anthocyanin, provitamin A, and oleic acid, coupled with reduced levels of anti-nutritional factors. In the past decade, 142 biofortified varieties, spanning rice, wheat, maize, pearl millet, small millet, lentil, chickpea, and other crops, have been developed under the auspices of the Indian Council of Agricultural Research (ICAR). Biofortified varieties typically do not impact ecological conditions, soil, or water requirements differently from traditional varieties. Additionally, they do not incur extra cultivation costs, and their economic output is comparable to traditional produce, leading to their widespread adoption. In India, the scale-up of biofortified varieties has gained momentum, with substantial quantities of breeder seeds being produced and distributed to public and private seed agencies for further multiplication and dissemination to farmers. Over the past six years, approximately 10 million hectares of land have been cultivated with biofortified rice, wheat, pearl millet, mustard, and lentil varieties.

Introduction

The transgenic approach can be an effective alternative for the development of biofortified crops when there is limited genetic variation for the targeted nutrient content among the germplasm (Zhu et al. 2007). Transgenic approaches have been used for the simultaneous integration of genes involved in the enhancement of micronutrient concentration as well as reduction in the concentration of antinutrients, resulting in enhancing the bioavailability of nutrients in plants. Development of biofortified crops employing the transgenic approaches, involves a significant amount of time, effort, and resources during the development stage, but it is a cost-effective and sustainable approach in a long run (Garg et al., 2018). For its wide consumption, rice has been targeted to address the global challenge of malnutrition. Vitamin deficiency can be considered as one of the significant challenges that affect poor section of populations due to low affordability. Development of ‘Golden Rice’ with provitamin A (beta-carotene) was recognized as an important breakthrough in this direction by expressing genes encoding PSY and carotene desaturase (Datta et al. 2003). Folic acid (vitamin B9) is important during pregnancy and reducing anemia. Rice was genetically modified to increase folate content (up to 150-fold) by overexpressing genes encoding Arabidopsis GTP-cyclohydrolase I (GTPCHI) and aminodeoxy-chorismate synthase (ADCS) (Blancquaert et al. 2015). Rice has also been targeted to address the global challenge of iron deficiency anemia. Multiple reports indicated an enhance in iron content by overexpressing a number of genes (Lee et al. 2009). Similarly, zinc content was also raised in rice by overexpressing OsIRT1 and mugineic acid biosynthesis genes from barley (HvNAS1, HvNAS1, HvNAAT-A, HvNAAT-B, IDS3) (Lee and An 2009, Masuda et al. 2008).

Introduction

Rice is the world’s most important staple crop and is a primary source of energy and nutrition for about half of the world’s population. So it is the most important cereal crop with respect to food security of common people. Due to increasing world population and shrinkage of farm land holdings there is an urgent need to increase the grain productivity. Therefore, increasing grain yield has become the primary objective in many rice-breeding programs. India is the second highest rice producer (about 120 million ton/year) in the world and able to meet the demand of rice for the entire Indian population. But along with yield improvement of rice, quality has now become a foremost consideration for rice consumers and millers. Quality is defined as “the totality of features and characteristics of a product or service that bears its ability to satisfy stated or implied needs” (International Standard Organization (ISO) 8402 1986). The concept of grain quality covers many physico-chemical properties such as grain shape and size, milling and cooking properties, amylose content, stickiness, chalkiness, texture, colour, gelatinization characters and various nutritional properties. Thus, rice grain quality generally includes five main classes i.e. (i) milling quality, (ii) physical quality, (iii) cooking and eating quality (iv) sensory quality and (v) nutritional quality. Grain quality and its assessment are very important to consumers, millers and rice breeders who are engaged in varietal improvement programme, related to new features such as high nutritional quality, high yield potential, highly resistant to abiotic or biotic stresses, higher water use efficiency etc.

Introduction

Rice contains essential micronutrients such as iron (Fe), zinc (Zn), copper (Cu), calcium (Ca), manganese (Mn), magnesium (Mg), etc. which are generally lower when compared with other staple crops like wheat, maize, legumes, and tubers (Adeyeye et al. 2000). The most crucial micronutrients are iron and zinc, whose inadequacy is a leading cause of malnutrition. In this chapter we discuss estimation methodologies and diversity of Fe and Zn, its genetic basis, and improvement for micronutrient content through breeding techniques.

Procedure of Estimation of Fe and Zn Content in Rice Grain

Iron and zinc concentrations in rice samples were generally estimated by colorimetric method Atomic Absorption Spectrometry (AAS), X-ray Fluorescence (XRF), and Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). X-Ray Fluorescence (XRF) Spectrometry is extremely helpful in the non-destructive estimation of relative Zn and Fe concentration in rice breeding lines and large germplasm collection (Paltridge et al. 2012). The majority of biofortification programs employ XRF as a metal analysis tool. For estimation of Fe and Zn, panicles of middle row plants of each replication were harvested, sun-dried for 4-5 days to reduce the moisture content to 11-12 %, and then seeds were dehusked. Each brown rice sample of about 5g was subjected to energy dispersive X-ray fluorescent spectrophotometer (ED-XRF) as per standard protocol (Stangoulis and Sison 2008, Rao et al. 2014) and expressed in ppm (µg g-1).

Introduction

Rice is one of the most important staple foods among all cereals. The larger population in Asia and Africa depends on rice for their daily calorie and nutritional requirements. People are found to bank on rice as their main source of nutrition in emerging and underdeveloped nations (Yang et al. 2016). However, it is considered that the milled or polished rice is nutritionally poor as the majority of the essential micronutrients viz. iron (Fe) and zinc (Zn), and important vitamins are lost during the process of milling and polishing (Johnson et al. 2011). So, by the way, the poorer section of the worldwide population mainly depends on rice and is most vulnerable to ‘hidden hunger’ as they are unable to afford other micronutrients-rich non-staple foods for their balanced diet and are often at the maximum risk for micronutrients deficiencies (Bouis and Saltzman 2017). The only possible solution for such malnutrition is to have nutritionally enriched food in the daily foodstuff. However, approximately one third of the world’s population is facing the problem of hidden hunger (White and Broadley 2009). Prolonged utilization of carbohydrate-rich food mainly based on rice, wheat, or maize is contributing to such nutritional deficiency in the poorer section of our society as most of them are unable to supplement nutritionally rich food for their diet. The deficiency of micronutrients can be termed a silent epidemic because it slowly weakens our immune system and hampers physical and intellectual development which may lead to fatality in some severe conditions. In the case of micronutrient deficiencies, deficiencies  of iron or iron deficiency anaemia (IDA), zinc deficiency, and vitamin-A  deficiency (VAD) are common, and have serious consequences.

Introduction

Understanding the variation in grain protein content is the pre-requisite of its improvement in modern rice varieties. The measure of quantitative and qualitative aspects of grain storage protein content includes estimation of soluble and total grain protein, quantifying various fractions, viz. glutelins, prolamins, globulins and albumins and their profiling through SDS-Page and  estimation of amino acid. As traditional chemical methods for protein content determination are destructive in nature. All these estimates comprehensively give insight into the diversity of storage protein in rice germplasm. The standard procedures followed for all these estimates are briefly stated in the  following sections.

Estimation of Total Grain Protein Content in Rice

The total protein is estimated via estimation of total N through the Kjeldahl method whereas soluble protein is estimated through Lowry method, Dumas method and Bradford method. But for estimation of large number of genotypes all these processes are tedious, time-consuming, and costly. Near-infrared spectroscopy (NIRS), as a non-destructive detection technique, can achieve rapid quantitative determination of protein contents and become an important development direction to replace traditional chemical detection methods.

Introduction: N metabolism

Nitrogen is one of the three essential macronutrients for plant growth and yield (Su et al., 2005) and most crucial elements for root growth also (Fageria, 2014). Most macromolecules and a variety of secondary and signalling substances, such as proteins, nucleic acids, cell wall components, hormones, and vitamins, contain nitrogen (N), an important element. In order to assimilate nitrogen, nitrate must be reduced to ammonium, and then ammonium must be converted into amino acids. Perez et al. (1973) pointed out that the rice genotype with high protein yield translocated N from leaf blade to the developing grains more efficiently than the low protein genotype. This was reported due to a high concentration of free amino acids in the sap translocated to the developing grains rather than to differences in translocation rates. Therefore, proper understanding of N metabolism and amino acid translocation are prerequisite to comprehend higher grain protein in high yielding rice genotypes. Use of N by plants involves several steps including uptake, assimilation, translocation and remobilization; and recycling and remobilization when the plant is ageing (Fig. 1). The enzyme nitrate reductase (NR) assimilates nitrate, the main form of nitrogen available to agricultural plants in the field. This enzyme and the nitrogen status of various higher plant systems have a strong positive link, and growth, yield, or protein content can occasionally be connected to this enzyme’s level in seeds or leaves. Nitrate intake occurs at the root level, and it has been demonstrated that plants have two nitrate transport systems that work together to cohabit, absorb, and distribute nitrate from the soil solution throughout the entire plant. (Srivastava 1980) Following NO3- uptake by NO3- transporters and reduction of NO3- to NO2- by nitrate reductase (NR) in the cytoplasm, the process of NO3- assimilation commences (Lea and Miflin, 1974).

Introduction

Malnutrition remains a pervasive global challenge, affecting millions of individuals across the world, particularly in low- and middle-income countries. Despite significant advancements in agriculture and food production, a large segment of the population still lacks access to essential nutrients, leading to severe health consequences and perpetuating cycles of poverty and underdevelopment (Müller and Krawinkel, 2005). Malnutrition, defined as the inadequate intake of essential nutrients required for optimal health and development, encompasses both undernutrition and over-nutrition (WHO, 2023). While undernutrition, characterized by deficiencies in energy, protein, vitamins, and minerals, remains a significant concern, over nutrition, manifesting as obesity and diet-related non-communicable diseases, is also on the rise, particularly in urban settings (Wells et al., 2020). The consequences of malnutrition are far-reaching, impacting physical growth, cognitive development, immune function, and overall well-being, with long term implications for productivity, economic prosperity, and societal stability (Saunders and Smith, 2010).

Rice, a staple food for more than half of the world’s population, plays a central role in global food security and nutrition. However, conventional rice varieties often lack sufficient levels of key nutrients, such as iron, zinc, vitamin A, and certain amino acids, leaving populations reliant on rice-based diets vulnerable to micronutrient deficiencies and associated health risks (Peña-Rosas and Mithra, 2019). Iron deficiency anaemia, zinc deficiency, and vitamin A deficiency, are among the most prevalent forms of malnutrition worldwide, particularly affecting women and children in resource-constrained settings where rice consumption is high (Dipti et al., 2012)

Microbial Resistance Mechanism

Huge use of antibiotics in nosocomical environment has lead to the occurrence of multidrug resistance mechanism by microorganism against particular antibiotics (Munita et al., 2016; Zhao et al., 2020). Main operation includes chemical modification, efflux pump through passivation, modification of drug targeting gene and systemic elimination of antibiotics as many of them can form biofilm (Rajput et al., 2018) which can show extreme resistance. Chemical and enzymatic mechanism can include inactivation, activity loss, degradation and derivatizaton of antibiotics chemical group (Liu et al., 2019). Best idea may include production of enzymes or they can also expel antibiotic to efflux pump. Antibiotics drug efflux resistance can be accomplished by drug efflux pump playing an important role in microbial resistance. A different type of efflux pump system has been identified that include lipophilic and hydrophilic efflux system targeting the drug at different chemical properties (Wasaznik et al., 2009; Kumar et al., 2012). Another strategy adopting in resistance mechanism is modification of drug targeting gene. This mechanism makes the changes in drug to lose its target through drug targeting gene modification. Another important resistance mechanism is effectiveness of antibiotics by interfering with the target site. Therefore, bacteria has evolved different mechanism that include target site protection. A bactericidal role played by beta lactum antibiotics in inhibition of mucopeptide synthase and bacterial penicillin binding protein (PBP) in cell wall transpeptidation reaction that prevents the formation of complete call wall and hence dies (Sauvage et al., 2016). Bacteria also developed its own strategies to cope up with the environmental stress that can also include human body. In course of gaining the advantage bacteria needs to compete for nutrients and to keep away from the molecules produced by other competing organism (Zhao et al., 2019). Recently researchers have found the importance of biofilm resistance in bacteria. Bacterial biofilm resistance produce by complex and systematic drug resistance mechanism.

Introduction

The epidemiological risk and hazards to global health security posed by AMR has been reiterating in several World Health Assembly (WHA) declarations and has been prioritized under the Global Health Security Agenda (GHSA). The Indian Ministry of Health & Family Welfare (MoHFW) has also identified AMR as one of the top priorities for collaborative work with WHO and the first National Action Plan on AMR has been implemented (2017-2022). India ranked fifth in antibiotic consumption in food producing animals (ruminants, pigs, and poultry) in 2010. Even though there has been a gradual reduction of 3.6% in antibiotic consumption during 2011-2019 (Koya et al., 2022), with mounting incomes and shifting in dietary patterns in favour of the consumption of animal protein, especially for poultry, the veterinary antibiotic utilization is projected to further rise by 312%, elevating India to the fourth rank by 2030 (Van Boeckel et al., 2015). FAO has already reported some of the peak resistance rates among common commensal and environmental bacteria against antibiotics like penicillin, cephalosporins, erythromycin and co-trimazoles in India (INFAAR). Resistance to the broad spectrum fluoroquinolones and third generation cephalosporin antibiotics is already more than 70% in Escherichia coli, Klebsiella pneumoniae, and, Acinetobacter baumannii and more than 50% in Pseudomonas aeruginosa. Even the microbial resistance to carbapenems, the last-resort antibiotics, is extremely high among gram-negative microorganisms (Sumanth et al., 2016). To overcome these incidences, it is impulsive to understand the microbe and drug interaction in host system.

Introduction

The study of infectious diseases, alongside other clinical and natural strengths, is going through fast change introduced on by the approach of reasonable next generation sequencing (NGS) advancements (Koser et al., 2012).These technologies become adopted as routine methods easily, and laboratory techniques are transformed throughout the process. The amount of genomic bacterial data generated is huge. As of this writing, for example, over 200,000 Salmonella genomes alone are in the public domain with hundreds being added weekly. A whole genomic DNA sequence characterizes the maximum practicable level of structural detail on the individuating traits of an microbial organism or population. It can therefore be used to provide more accurate microbial genome recognition, evolutionary relations and a detailed catalogue of epidemiologically important characteristics. This has a significant role to play for outbreak research, diagnosis and treatment of infectious diseases, microbiology and epidemiology (Allard et al., 2019). Besides, DNA sequences are also a universal dataset which can theoretically be used to determine any biological function. This means that antimicrobial resistant (AMR) can be detected and to track the development and spread of AMR bacteria in a hospital or the community.

Introduction

Until the 20thcentury, bacterial infections were the number one cause of human death. In the 1940s, antibiotics became the lifelines for treating serious infections that saved millions of lives. Despite the advantages derived from the use of antibiotics, resistance to these drugs emerged. Unfortunately, resistance to most antibiotics emerged in time-course even for the most powerful antibiotics developed.Resistance to antibiotics is a challenge to the scientific community in keeping up the pace of antibiotic discovery.World Economic Forum’s Global Risks Reporthas listed antibiotic resistance as one of the greatest threats (WEF, 2020).United Nations (UN) has warned that drug-resistant diseases could account for 10 million deaths each year by 2050. By 2030, antimicrobial resistance (AMR) could likelylead up to 24 million people into extreme poverty(IACG,2019). Currently, at least 7,00,000 people die each year due to drug-resistant diseases (IACG,2019). The emergence and widespread of antibiotic-resistant organisms is a global challenge and needs a multi-dimensional approach to address the fundamental issues to minimize drug-resistance.The Antibiotic Resistance Genes Database (ARDB) contains a repository of around 23,000 antibiotic resistance gene or protein sequences conferring resistance against over 240 antibiotics (ARDB). Computational Biology (Bioinformatics) has become one of the important tools in studying antimicrobial resistance. It employs a range of computation techniques to make predictions about the biological phenomenon.

Introduction

Resistance to antibiotics in the bacterial world is a genetically determined phenomenon that was first observed within a few years after the introduction of antibiotics for therapeutic purposes. In Nature, ARGs are believed to have originated about three billion years ago as an intrinsic defense mechanism in antibiotic-producing bacteria (Perry et al., 2016; Iskandar et al., 2022), and subsequently, evolved by complex and quantum jump trajectories to mobilize, diversify and interconnect all ecosystems in the micro-biosphere. Bacterial genomes exhibit plasticity and continue to evolve under the selection pressure of antibiotics and other stressors (Patel, 2016). The ARGs in circulation at present are thus a mixture of ancient and modern counterparts. Recently, the interplay between bacterial metabolism and antibiotic resistance has also been revealed (Zampieri, 2021).

The use of antimicrobials in health management, livestock, and food industry is driving the emergence of resistant microbes at a rapid pace (Wall et al., 2016; Adegoke et al., 2016; Hu et al., 2017). As a result, AR pathogens have spread globally to cause loss of lives, production, productivity, and negatively impact economic growth. Recently, AR pathogens in a large study have been found directly responsible for millions of deaths, and the figures are likely to increase in the coming decades (Murray et al., 2022). The pace of the emergence of AR can however be slowed down by improving human interventions. The global and local AR combat plans implemented during the past few years have enhanced the mass awareness of the pandemic problem (WHO, 2015; FAO, 2016; NAP, GOI, 2017; WHO, 2022; WOAH, 2022). These Action Plans on AR containment encourage avoiding of indiscriminate use of antibiotics for the treatment of sick humans and animals, recommend the ban on the use of antibiotics as growth promoters in food animals, promote AR surveillance and monitoring, and support the ‘One-Health’ strategy and application of the biosecurity principles for containment of the resistant microbes.

Introduction

Antibiotic-resistant bacteria are a major cause of health care-associated infections around the world, and resistance has also emerged in infections in the wider community. Infections caused by multi resistant organisms significantly increase morbidity, mortality, and health care costs. Molecular analyses have revealed that widespread multi resistance has commonly been achieved by the acquisition of preexisting determinants followed by amplification in response to selection. The capture, accumulation, and dissemination of resistance genes are largely due to the actions of mobile genetic elements (MGE), a term used to refer to elements that promote intracellular DNA mobility (e.g., from the chromosome to a plasmid or between plasmids) as well as those that enable intercellular DNA mobility.

Insertion sequences (IS) and transposons (Tn) are discrete DNA segments that areable to move themselves (and associated resistance genes) almost randomly to newlocations in the same or different DNA molecules within a single cell. Other elements, such as integrons (In), use site-specific recombination to move resistance genes between defined sites. As these types of MGE are often present in multiple copies indifferent locations in a genome, they can also facilitate homologous recombination(exchange of sequences between identical or related segments). Intercellular mechanisms of genetic exchange include conjugation/mobilization (mediated by plasmidsand integrative conjugative elements [ICE]), transduction (mediated by bacteriophages), and transformation (uptake of extracellular DNA). Interactions between thevarious types of MGE underpin the rapid evolution of diverse multi resistant pathogens in the face of antimicrobial chemotherapy. Primarily the most important and/ or topical elements in Gram-negative and Gram-positive bacterial species of particular concern clinically, namely, Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp. (the so-called ESKAPE group) (Rice LB., 2008) as well as Escherichia coli (giving the ESKAPEE group) (Llaca-Díaz J.M. et al.,2012); nonetheless, many of the MGE types described are of course broadly relevant to many other bacterial taxa.

Antibiotics, often referred to as “magic bullets” in the battle against bacteria, stand out as one of the most remarkable medical breakthroughs of the 20th century. Their advent revolutionized the therapeutic landscape, consistently saving millions of lives from bacterial infections (WHO, 2020). Undoubtedly, antibiotics are a blessing to humanity, not merely for their medicinal applications but also for their diverse uses. They have long been employed in various contexts, including animal husbandry and production, serving as preventive measures in numerous underdeveloped and developing nations for decades (Majumder et al., 2020). A range of antimicrobial agents, including antibiotics, antifungals, antivirals, disinfectants, and food preservatives, function to either inhibit microbial growth or eradicate them altogether. Among these, antibiotics, specifically tailored to combat bacterial infections, are the most widely used class of antimicrobials. With their increasing and often improper use, microorganisms have developed antimicrobial resistance (AMR) (Murray et al., 2022).

Antimicrobial resistance is an inevitable evolutionary process observed in all microorganisms, and is driven by genetic mutations aimed at resisting the lethal pressures of selection. Bacteria, adapt to environmental selection pressures by developing resistance to antibacterial drugs, thereby diminishing the efficacy of these treatments (Murray et al., 2022). The widespread use of antibiotics, particularly in developing nations, further flares up the process, leading to significant repercussions such as increased rates of morbidity and mortality (WHO, 2020). The incidence and prevalence of antimicrobial resistant bacterial infections have reached alarming levels in the 21st century, posing a substantial threat to global public health akin to a silent pandemic. Antibiotic resistance knows no borders and can impact individuals of any age or gender, regardless of their location. In its present state, antimicrobial resistance (AMR) stands as one of the foremost threats, not only to global health but also to food security (Murray et al., 2022).

The response of any living cell to a xenobiotic (including antibacterial agent) is significantly affected by the prevailing local environmental conditions. In case of bacterial infection, it may include the presence of other microbes, no matter commensal or pathogenic, or biochemical alterations at that particular site of bacterial infection in host. All these host and bacterial factors play a critical role in the evolutionary responses of bacteria but usually go unconsidered while determining the microbial sensitivity to a particular antibiotic in a clinical setting. These also include the direct and indirect interspecies interactions that can affect the responses of individual bacterial species and surviving microbial communities to a particular antibiotic therapy. These interactions may significantly alter the qualitative and quantitative responses, potential phenotypic changes and the final trajectory of evolution of antimicrobial resistance. Due acknowledgement and plausible interpretation to these interactions may help to reduce the upsurge in AMR and its associated morbidity and fatality and pave path to more proficient clinical success.

The factors participating in drug- microbe interaction can be classified into two broad groups: host factors and microbial factors. The environmental milieu of the interaction is chiefly regulated by the gut microbiota with stressors causing deflections. The gastrointestinal bacteria amend host mental and physiological cadence via microbial metabolites such as butyrate, polyphenolic antioxidants, vitamins, and amines, affecting the overall ready perception and active rebuke to a stimulus. Lifestyle stressors such as fluctuating sleep and erratic eating patterns (western diet) disturb the host circadian system along with the gut microbiome. The overall impact is impaired detoxification (decreased conjugation of bile acids or increased production of hydrogen sulphide), substrate oxidation and energy regulation (reduced butyrate production) in the host affecting the overall health and productivity.

Globally, antimicrobial resistance (AMR) is an important public health and development threat (WHO, 2020). Being one of the top 10 global public health threats, the ever-increasing rates in the occurrence of drug-resistant bacterial infections have become a grave public health concern for the governments (Laxminarayan et al., 2013). Moreover, such infections would be difficult to treat and therefore can lead to worse clinical outcomes (Laxminarayan et al., 2013). Worldwide, each year about 700,000 people die from antimicrobial resistant infections and the mortality figures are projected to reach 10 million/ year by 2050 (O’Neill, 2016). The crude infectious disease mortality rate in India is more than 400 per 100,000 persons and at least 23,000 deaths in adults and 58,000 neonatal deaths per year are caused by AMR bacteria (Laxminarayan and Chaudhury, 2016). A 2017 estimate puts the cost of developing an antibiotic at around US$1.5 billion (Towse, et al. 2017). Meanwhile, industry analysts estimate that the average revenue generated from an antibiotic’s sale is roughly $46 million per year. “That’s tiny and nowhere near the.