## 8 Conclusions and Future Perspectives  
In this review, we summarized several versatile methods that are used to activate silent natural product BGCs by the manipulation of regulatory genes, ribosomal engineering, co-cultivation, or precise genome engineering mediated by CRISPR-Cas9. However, there are advantages and disadvantages to each method. For example, although the particular biosynthetic pathway-specific manipulation can link the product and the gene cluster directly, it can only activate one specific gene cluster at a time. The manipulation of the global regulatory genes, ribosomal engineering, and cultivation in varied conditions may activate several BGCs at a time, but it is difficult to link the specific metabolites with the BGCs. For those methods toward multiple BGC activation, if an easy way can be found to link the particular BGCs to their specific products, respectively, then the high-throughput activation of cryptic biosynthetic pathways can become feasible. In other instances, the revolutionary technology for precise genome engineering like CRISPR-Cas9 has disadvantages, such as the non-specificity of DSBs, the toxicity of Cas nuclease, and poor expression levels of _cas9_ gene or _sgRNAs_, which have been major bottlenecks for their application in multiplexed fashion [100]. However, there have been attempts to improvise the application of CRISPR-Cas9 by employing conjugating with base-editing enzymes [101] and in the future, many breakthroughs can update the application of these approaches. The application of CRISPR interference (CRISPRi) [102] and CRISPR activation (CRISPRRa) [103] in addition to gene deletions in multiplexed fashion, can bring forth rational metabolic engineering approaches for activating cryptic BGCs mediated by multi-repurposing of precursor pathways, regulators, and biosynthetic enzymes. The ease of availability of the genome sequence of diverse _Streptomyces_ has unfolded the genomic context of all the BGCs, including cryptic BGCs, that can be analyzed by versatile in silico based BGC prediction software (ActinoBase) [104]. Nevertheless, these tools provide an effective prediction of diverse NPs belonging to different compound classes as PKS, NRPS, RiPPs, or hybrids, but still much greater robustness and higher precision can be expected. In addition, the availability of web-based tools, such as MASST [105], have enabled high-throughput screening of NPs based on their mass fragmentation patterns, which can enable the precise prediction of the metabolite from the culture broth, independent of the purification and structural elucidation steps. Furthermore, the available knowledge resources from genomics and metabolomics can be employed for strain engineering, biosynthetic pathway engineering, synthetic biology, systems biology, and media optimization technology for the production of such cryptic/known biomolecules in significant titers [106]. Such burgeoning development in both genetic studies, as well as metabolic profiling, can be further harnessed in metabolic engineering strategies by the application of computational approaches, such as artificial intelligence (AI). These approaches can be effective in simulating the connection between the genomics and metabolomics to generate intelligence in these production hosts, so that they can sense the environmental condition, and respond rationally [107]. Therefore, the next dimension for the activation of cryptic BGCs can be based on computational optimization of genomics, proteomics, and metabolomics, based on machine learning and AI. Such information can be utilized for the reincarnation of a particular production host by robust synthetic biological tools, or genome engineering approaches based on the predicted mathematical models and simulations. Conceptualization, C.T.N., D.D. and J.-K.S. ; writing--original draft preparation, C.T.N. and D.D. ; writing--review and editing, C.T.N., D.D., V.T.T.P. and H.T.N. ; supervision, J.-K.S. ; funding acquisition, J.-K.S.