Mycobacterium smegmatis (M.sm) is frequently used as an alternative model organism in Mycobacterium tuberculosis (M.tb) studies. While containing high sequence homology with M.tb, it is considered non-pathogenic in humans. As such it has been used to study M.tb and other infections in vivo and more recently been explored for potential therapeutic applications. A body of previous research has highlighted the potential of using genetically modified M.sm displaying rapid growth and unique immunostimulatory characteristics as an effective vaccine vector. Novel systems biology techniques can further serve to optimize these delivery constructs. In this article, we review recent advancements in vaccinomics tools that support the efficacy of a M.sm-based vaccine vector. Moreover, the integration of systems biology and molecular omics techniques in these pioneering studies heralds a potential accelerated pipeline for the development of next-generation recombinant vaccines against rapidly developing diseases.

Metabolomics is emerging as a promising tool to understand the effect of immunometabolism for the development of novel host-directed alternative therapies. Immunometabolism can modulate both innate and adaptive immunity in response to pathogens and vaccinations. For instance, infections can affect lipid and amino acid metabolism while vaccines can trigger bile acid and carbohydrate pathways. Metabolomics as a vaccinomics tool, can provide a broader picture of vaccine-induced biochemical changes and pave a path to potentiate the vaccine efficacy. Its integration with other systems biology tools or treatment modes can enhance the cure, response rate, and control over the emergence of drug-resistant strains. Mycobacterium tuberculosis (Mtb) infection can remodel the host metabolism for its survival, while there are many biochemical pathways that the host adjusts to combat the infection. Similarly, the anti-TB vaccine, Bacillus Calmette-Guerin (BCG), was also found to affect the host metabolic pathways thus modulating immune responses. In this review, we highlight the metabolomic schema of the anti-TB vaccine and its therapeutic applications. Rewiring of immune metabolism upon BCG vaccination induces different signaling pathways which lead to epigenetic modifications underlying trained immunity. Metabolic pathways such as glycolysis, central carbon metabolism, and cholesterol synthesis play an important role in these aspects of immunity. Trained immunity and its applications are increasing day by day and it can be used to develop the next generation of vaccines to treat various other infections and orphan diseases. Our goal is to provide fresh insight into this direction and connect various dots to develop a conceptual framework.

Intracellular bacterial pathogens have evolved sophisticated metabolic strategies to persist and replicate within the hostile intracellular environments of their hosts. By leveraging their metabolic plasticity, these pathogens dynamically modulate host metabolic processes in response to immunological, environmental, and pharmacological stressors. This review examines the diverse metabolic adaptations employed by intracellular pathogens, including nutrient acquisition, modulation of host metabolism, and stress-induced metabolic shifts that contribute to persistence and virulence. Emphasis is placed on how distinct intracellular niches- such as vacuoles and the cytosol- shape pathogen metabolism, and how bipartite metabolic strategies enable pathogens to balance energy production with biosynthetic demands. Species-specific adaptations in representative pathogens, including Listeria monocytogenes , Legionella pneumophila , Shigella flexneri , and Chlamydia trachomatis , are analyzed, with a focus on mechanisms of metabolic reprogramming (the alteration of cellular metabolic pathways in response to environmental cues, such as infection or stress, which allows the pathogen to adapt its metabolic state to support survival, replication, and virulence within the host), stress tolerance (refers to a pathogen’s ability to survive and function under harsh environmental conditions, such as oxidative stress, nutrient scarcity, and antimicrobial exposure), and lifecycle transitions (refer to the changes in a pathogen’s developmental or replication stages, such as switching from active growth to a dormant or persistent state during infection). Finally, the review considers how these metabolic strategies intersect with antimicrobial resistance and highlights the potential of targeting host-pathogen metabolic interactions for the development of novel interventions, including host-directed therapies (HDTs).

Several decades after the discovery of the first antibiotic (penicillin) microbes have evolved novel mechanisms of resistance; endangering not only our abilities to combat future bacterial pandemics but many other clinical challenges such as acquired infections during surgeries. Antimicrobial resistance (AMR) is attributed to the mismanagement and overuse of these medications and is complicated by a slower rate of the discovery of novel drugs and targets. Bacterial peptidoglycan (PG), a three-dimensional mesh of glycan units, is the foundation of the cell wall that protects bacteria against environmental insults. A significant percentage of drugs target PG, however, these have been rendered ineffective due to growing drug resistance. Identifying novel druggable targets is, therefore, imperative. Uridine diphosphate N-acetylglucosamine (UDP-GlcNAc) is one of the key building blocks in PG production, biosynthesized by the bifunctional enzyme N-acetyl-glucosamine-1-phosphate uridyltransferase (GlmU). UDP-GlcNAc metabolism has been studied in many organisms, but it holds some distinctive features in bacteria, especially regarding the bacterial GlmU enzyme. In this review, we provide an overview of different steps in PG biogenesis, discuss the biochemistry of GlmU, and summarize the characteristic structural elements of bacterial GlmU vital to its catalytic function. Finally, we will discuss various studies on the development of GlmU inhibitors and their significance in aiding future drug discoveries.

Alzheimer's disease (AD) affects 50 million people worldwide, an increase of 35 million since 2015, and it is known for memory loss and cognitive decline. Considering the morbidity associated with AD, it is important to explore lifestyle elements influencing the chances of developing AD, with special emphasis on nutritional aspects. This review will first discuss how dietary factors have an impact in AD development and the possible role of Artificial Intelligence (AI) and Machine Learning (ML) in preventative care of AD patients through nutrition. The Mediterranean‐DASH diets provide individuals with many nutrient benefits which assists the prevention of neurodegeneration by having neuroprotective roles. Lack of micronutrients, protein‐energy, and polyunsaturated fatty acids increase the chance of cognitive decline, loss of memory, and synaptic dysfunction among others.ML software has the ability to design models of algorithms from data introduced to present practical solutions that are accessible and easy to use. It can give predictions for a precise medicine approach to evaluate individuals as a whole. There is no doubt the future of nutritional science lies on customizing diets for individuals to reduce dementia risk factors, maintain overall health and brain function.