Urinary tract infections (UTIs) represent a prevalent health concern among the female population, with anatomical and physiological determinants such as a shorter urethra and its proximity to the rectum augmenting vulnerability. The presence of Escherichia coli and various other pathogens plays a significant role in the etiology of these infections, which can be aggravated by sexual intercourse and disturbances to the vaginal microbiome. The physiological alterations associated with pregnancy further elevate the likelihood of UTIs, with untreated cases potentially leading to severe complications such as pyelonephritis, preterm labor, and stillbirth. Furthermore, postmenopausal women encounter an augmented risk of UTIs attributable to estrogen deficiency and vaginal atrophy, as well as conditions including pelvic organ prolapse (POP) and urinary incontinence (UI), which hinder optimal bladder functionality. The aforementioned factors, in conjunction with the rising prevalence of cesarean deliveries and catheterization, complicate the management of UTIs. While precise diagnosis is paramount, it remains a formidable challenge, notwithstanding advancements in molecular diagnostic techniques. Management strategies encompass antibiotic-sparing therapies; however, the increasing incidence of multidrug resistance represents an alarming trend. Diverse guidelines from various medical specialties endeavor to standardize treatment approaches, yet significant inconsistencies continue to exist. This study systematically appraises the extant guidelines, evaluating the quality of evidence while identifying areas of agreement and discord to supply practitioners with effective strategies for UTI management.

Microbial engineering has made a significant breakthrough in pharmaceutical biotechnology, greatly expanding the production of biologically active compounds, therapeutic proteins, and novel drug candidates. Recent advancements in genetic engineering, synthetic biology, and adaptive evolution have contributed to the optimization of microbial strains for pharmaceutical applications, playing a crucial role in enhancing their productivity and stability. The CRISPR-Cas system is widely utilized as a precise genome modification tool, enabling the enhancement of metabolite biosynthesis and the activation of synthetic biological pathways. Additionally, synthetic biology approaches allow for the targeted design of microorganisms with improved metabolic efficiency and therapeutic potential, thereby accelerating the development of new pharmaceutical products. The integration of artificial intelligence (AI) and machine learning (ML) plays a vital role in further advancing microbial engineering by predicting metabolic network interactions, optimizing bioprocesses, and accelerating the drug discovery process. However, challenges such as the efficient optimization of metabolic pathways, ensuring sustainable industrial-scale production, and meeting international regulatory requirements remain critical barriers in the field. Furthermore, to mitigate potential risks, it is essential to develop stringent biocontainment strategies and implement appropriate regulatory oversight. This review comprehensively examines recent innovations in microbial engineering, analyzing key technological advancements, regulatory challenges, and future development perspectives.

Using free microorganisms for industrial processes has some limitations, such as the extensive consumption of substrates for growth, significant sensitivity to the microenvironment, and the necessity of separation from the product and, therefore, the cyclic process. It is widely acknowledged that confining or immobilizing cells in a matrix or support structure enhances enzyme stability, facilitates recycling, enhances rheological resilience, lowers bioprocess costs, and serves as a fundamental prerequisite for large-scale applications. This report summarizes the various cell immobilization methods, including several synthetic (polyvinylalcohol, polyethylenimine, polyacrylates, and Eudragit) and natural (gelatin, chitosan, alginate, cellulose, agar–agar, carboxymethylcellulose, and other polysaccharides) polymeric materials in the form of thin films, hydrogels, and cryogels. Advancements in the production of well-known antibiotics like penicillin and cephalosporin by various strains were discussed. Additionally, we highlighted cutting-edge research related to strain producers of peptide-based antibiotics (polymyxin B, Subtilin, Tyrothricin, varigomycin, gramicidin S, friulimicin, and bacteriocin), glusoseamines, and polyene derivatives. Crosslinking agents, especially covalent linkers, significantly affect the activity and stability of biocatalysts (penicillin G acylase, penicillinase, deacetoxycephalosporinase, L-asparaginase, β-glucosidase, Xylanase, and urease). The molecular weight of polymers is an important parameter influencing oxygen and nutrient diffusion, the kinetics of hydrogel formation, rigidity, rheology, elastic moduli, and other mechanical properties crucial for long-term utilization. A comparison of stability and enzymatic activity between immobilized enzymes and their free native counterparts was explored. The discussion was not limited to recent advancements in the biopharmaceutical field, such as microorganism or enzyme immobilization, but also extended to methods used in sensor and biosensor applications. In this study, we present data on the advantages of cell and enzyme immobilization over microorganism (bacteria and fungi) suspension states to produce various bioproducts and metabolites—such as antibiotics, enzymes, and precursors—and determine the efficiency of immobilization processes and the optimal conditions and process parameters to maximize the yield of the target products.

Background/Objectives: Urinary tract infections (UTIs) represent a considerable challenge within the field of clinical medicine, as they are responsible for significant morbidity and intensify the operational pressures encountered by healthcare systems. Conventional diagnostic approaches, which include symptom evaluation, dipstick urinalysis, and standard urine culture, often demonstrate inadequacies in identifying atypical clinical manifestations, infections with low bacterial counts, or pathogens that show growth difficulties under typical laboratory conditions. These limitations undermine diagnostic accuracy and hinder timely therapeutic measures. Methods: The present manuscript is a systematic review conducted in accordance with PRISMA guidelines. A structured search was performed in PubMed, Scopus, and Google Scholar, yielding 573 records, of which 107 studies were included for qualitative synthesis. The primary aim of this systematic review is to evaluate both conventional and emerging diagnostic methods for UTIs, with specific objectives of assessing their clinical applicability, limitations, and potential to improve patient outcomes. Results: Recent progress in diagnostic technologies offers promising alternatives. Molecular-based assays, such as multiplex polymerase chain reaction, matrix-assisted laser desorption ionization mass spectrometry, and next-generation sequencing, have substantially improved both the precision and efficiency of pathogen identification. Furthermore, contemporary techniques for evaluating antimicrobial susceptibility, including microfluidic systems and real-time phenotypic resistance assays, enable clinicians to execute targeted therapeutic strategies with enhanced efficacy. Results of this synthesis indicate that while conventional diagnostics remain the cornerstone for uncomplicated cases, innovative molecular and phenotypic approaches demonstrate superior performance in detecting low-count bacteriuria, atypical pathogens, and resistance determinants, particularly in complicated and recurrent infections. These innovations support antimicrobial stewardship by reducing dependence on empirical antibiotic treatment and lessening the risk of resistance emergence. Conclusions: Nonetheless, the incorporation of these technologies into clinical practice requires careful consideration of implementation costs, standardization protocols, and the necessary training of healthcare professionals. In conclusion, this systematic review highlights that emerging molecular diagnostics and resistance-profiling tools offer substantial promise in complementing or enhancing traditional methods, but their widespread adoption will depend on robust validation, cost-effectiveness, and integration into clinical workflows.

Recent advances in computational biology have provided powerful tools for analyzing, modeling, and optimizing probiotic microorganisms, thereby supporting their development as promising agents for improving human health. The essential role of the microbiota in regulating physiological processes and preventing disease has driven interest in the rational design of next-generation probiotics. This review highlights progress in in silico approaches for enhancing the functionality of probiotic strains. Particular attention is given to genome-scale metabolic models, advanced simulation algorithms, and AI-driven tools that provide deeper insight into microbial metabolism and enable precise probiotic optimization. The integration of these methods with multi-omics data has greatly improved our ability to predict strain behavior and design probiotics with specific health benefits. Special focus is placed on modeling probiotic–prebiotic interactions and host–microbiome dynamics, which are essential for the development of functional food products. Despite these achievements, key challenges remain, including limited model accuracy, difficulties in simulating complex host–microbe systems, and the absence of unified standards for validating in silico-optimized strains. Addressing these gaps requires the development of integrative modeling platforms and clear regulatory frameworks. This review provides a critical overview of current advances, identifies existing barriers, and outlines future directions for the application of computational strategies in probiotic research.

Plant growth-promoting microorganisms (PGPMs) and microbial biocontrol agents have emerged as key tools for improving crop productivity while maintaining environmental sustainability. However, central questions remain regarding which factors determine their consistent field performance and how these factors interact under real agronomic conditions. Previous research has demonstrated that PGPMs enhance nutrient acquisition, regulate phytohormone balance, improve stress tolerance, and suppress plant pathogens through diverse biochemical and ecological mechanisms. Advances in omics technologies, genome mining, and synthetic microbial communities have further expanded understanding of their functional potential. Nevertheless, many studies rely on laboratory-scale experiments or short-term trials, with limited multi-season and cross-regional validation. This gap contributes to inconsistent field outcomes and restricts large-scale agricultural adoption. Long-term multi-season validation and reproducibility assessment remain essential priorities for improving reliability of microbial agricultural products. This review synthesizes recent advances in PGPM-based biofertilizers and microbial biocontrol technologies, critically examining their mechanisms of action, scalability constraints, formulation challenges, and regulatory limitations. It identifies major translational barriers, including context dependency, mechanistic uncertainties, reproducibility gaps, and insufficient systems-level integration.