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The rise of antibiotic resistance has created an urgent need for the discovery of new antibiotic compounds. Streptomycin, the first antibiotic isolated from Streptomyces sp., paved the way for discovering other antibiotics for combating bacterial infections. By exploring the genome-based biosynthetic potential of various Streptomyces species, a vast array of secondary metabolites with potential therapeutic applications can be identified, contributing a transformative impact on the field of medicine. However, conventional screening approaches on novel natural products (NPs) from Streptomyces sp. have entered a bottleneck due to inefficiency. Fortunately, artificial intelligence (AI) and machine learning (ML) models enable rapid exploration and prediction of potential antibiotic compounds, increasing the probability of discovering new antibacterial compounds. AI-driven drug discovery in Streptomyces sp. represents a paradigm shift in the future quest for novel pharmaceutical agents. Various ML models have been developed and applied in different practical applications. Overall, the ML model is trained using input data and generates outcomes based on prediction output. This review discusses the continued potential of Streptomyces sp. as a source of novel NPs, along with the application of ML throughout the NP drug discovery pipeline involving genome mining, biological activities prediction, and optimization compound production in Streptomyces microbial systems. [ABSTRACT FROM AUTHOR]

Aquaculture is gaining prominence in meeting the increasing global food demand. However, persistent episodes of pathogenic infections have greatly affected production and incurred substantial financial losses to the industry. Regrettably, there is a lack of effective contemporary therapeutic measures to control infectious diseases in aquaculture. The repercussions of antimicrobial resistance have underscored the drawbacks of the contemporary practice of relying solely on antibiotics in disease control. The aquaculture industry needs a safer, environmentally viable, and economically efficient means for disease management. In this regard, this study aims to investigate the effectiveness of mangrove-derived Streptomyces sp. probiotics in controlling Vibrio parahaemolyticus infections. In vitro screenings were undertaken to evaluate the inhibitory activity of five Streptomyces sp. isolates. Subsequently, a series of in vivo trials was conducted, with the Malaysian giant freshwater prawn, Macrobrachium rosenbergii larvae as the animal model. Following that, molecular analyses were employed to examine the changes in gene expression. In essence, Streptomyces sp. MUM 195J emerges as a promising probiotic strain that demonstrates a strong inhibitory effect against V. parahaemolyticus. Its application as a feed additive elevates the survival rate of M. rosenbergii threefold, thus demonstrating efficacy at par with florfenicol antibiotic when challenged with the V. parahaemolyticus pathogen. Besides, Streptomyces sp. MUM 195J elevated the growth rate of M. rosenbergii by 17%. Real-time quantitative polymerase chain reaction (RT-qPCR) analysis revealed that probiotic supplementation elevated the immune function of the animal. Additionally, Streptomyces sp. MUM 195J demonstrates the potential to ameliorate the quality of the rearing water. [ABSTRACT FROM AUTHOR]

Streptomyces sp. is a group of filamentous, Gram-positive bacteria well known for their capabilities in producing bioactive compounds that have been used as novel drugs and lead in drug development. The Streptomyces sp. MUM 178J was isolated from a mangrove forest in Malaysia. This isolate was found to harbor anti-Vibrio properties as its crude extract inhibited the growth of multidrug-resistant Vibrio parahaemolyticus. Therefore, the strain was subjected to whole genome sequencing to unearth its genomic potential. The genome of Streptomyces sp. MUM 178J consists of 6,699,249 bp with a G+C content of 71.3%. 66 tRNA genes and 18 rRNA genes were also predicted to be present within the genome. Further analysis with the bioinformatics tool, antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), detected nine biosynthetic gene clusters displaying more than 70% similarity to known gene clusters, including one associated with melanin production. Melanin has demonstrated antagonistic activity against the growth of members of the Vibrio family, including V. parahaemolyticus. This indicates the potential correlation between the production of melanin and the anti-Vibrio properties of MUM 178J. The availability of the whole genome sequence of Streptomyces sp. MUM 178J allows for future in-depth investigation and potential exploitation of MUM 178J to harvest useful bioactive compounds. [ABSTRACT FROM AUTHOR]

The incidence of foodborne diseases has increased over the years and resulted in major public health problem globally. Foodborne pathogens can be found in various foods and it is important to detect foodborne pathogens to provide safe food supply and to prevent foodborne diseases. The conventional methods used to detect foodborne pathogen are time consuming and laborious. Hence, a variety of methods have been developed for rapid detection of foodborne pathogens as it is required in many food analyses. Rapid detection methods can be categorized into nucleic acid-based, biosensor-based and immunological-based methods. This review emphasizes on the principles and application of recent rapid methods for the detection of foodborne bacterial pathogens. Detection methods included are simple polymerase chain reaction (PCR), multiplex PCR, real-time PCR, nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP) and oligonucleotide DNA microarray which classified as nucleic acid-based methods; optical, electrochemical and mass-based biosensors which classified as biosensor-based methods; enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassay which classified as immunological-based methods. In general, rapid detection methods are generally time-efficient, sensitive, specific and labor-saving. The developments of rapid detection methods are vital in prevention and treatment of foodborne diseases. [ABSTRACT FROM AUTHOR]