Synthetic biology aims to design and construct bacterial genomes harboring the minimum number of genes required for self-replicable life. However, the genome-reduced bacteria often show impaired growth under laboratory conditions that cannot be understood based on the removed genes. The unexpected phenotypes highlight our limited understanding of bacterial genomes. Here, we deploy adaptive laboratory evolution (ALE) to re-optimize growth performance of a genome-reduced strain. The basis for suboptimal growth is the imbalanced metabolism that is rewired during ALE. The metabolic rewiring is globally orchestrated by mutations in
rpoD
altering promoter binding of RNA polymerase. Lastly, the evolved strain has no translational buffering capacity, enabling effective translation of abundant mRNAs. Multi-omic analysis of the evolved strain reveals transcriptome- and translatome-wide remodeling that orchestrate metabolism and growth. These results reveal that failure of prediction may not be associated with understanding individual genes, but rather from insufficient understanding of the strain’s systems biology.
Determining transcriptional and translational regulatory elements in GC-rich Streptomyces genomes is essential to elucidating the complex regulatory networks that govern secondary metabolite biosynthetic gene cluster (BGC) expression. However, information about such regulatory elements has been limited for Streptomyces genomes. To address this limitation, a high-quality genome sequence of β-lactam antibiotic-producing Streptomyces clavuligerus ATCC 27 064 is completed, which contains 7163 newly annotated genes. This provides a fundamental reference genome sequence to integrate multiple genome-scale data types, including dRNA-Seq, RNA-Seq and ribosome profiling. Data integration results in the precise determination of 2659 transcription start sites which reveal transcriptional and translational regulatory elements, including −10 and −35 promoter components specific to sigma (σ) factors, and 5′-untranslated region as a determinant for translation efficiency regulation. Particularly, sequence analysis of a wide diversity of the −35 components enables us to predict potential σ-factor regulons, along with various spacer lengths between the −10 and −35 elements. At last, the primary transcriptome landscape of the β-lactam biosynthetic pathway is analyzed, suggesting temporal changes in metabolism for the synthesis of secondary metabolites driven by transcriptional regulation. This comprehensive genetic information provides a versatile genetic resource for rational engineering of secondary metabolite BGCs in Streptomyces.
Streptomyces are Gram-positive bacteria of significant industrial importance due to their ability to produce a wide range of antibiotics and bioactive secondary metabolites. Recent advances in genome mining have revealed that Streptomyces genomes possess a large number of unexplored silent secondary metabolite biosynthetic gene clusters (smBGCs). this indicates that Streptomyces genomes continue to be an invaluable source for new drug discovery. Here, we present high-quality genome sequences of 22 Streptomyces species and eight different Streptomyces venezuelae strains assembled by a hybrid strategy exploiting both long-read and short-read genome sequencing methods. the assembled genomes have more than 97.4% gene space completeness and total lengths ranging from 6.7 to 10.1 Mbp. Their annotation identified 7,000 protein coding genes, 20 rRNAs, and 68 tRNAs on average. In silico prediction of smBGCs identified a total of 922 clusters, including many clusters whose products are unknown. We anticipate that the availability of these genomes will accelerate discovery of novel secondary metabolites from Streptomyces and elucidate complex smBGC regulation.
An integrated finite element-based model is presented for the prediction of the steady-state thermomechanical behavior of the roll-strip system and of roll life in hot strip rolling. The model is comprised of basic finite-element models, which are incorporated into an iterative-solution procedure to deal with the interdependence between the thermomechanical behavior of the strip and that of the work roll, which arises from roll-strip contact, as well as with the interdependence between the thermal and mechanical behavior. Comparison is made between the predictions and the measurements to assess solution accuracy. Then, the effect of various process parameters on the detailed aspects of thermomechanical behavior of the work roll and on roll life is investigated via a series of process simulations.
Streptomyces lividans is an attractive host for production of heterologous proteins and secondary metabolites of other Streptomyces species. To fully harness the industrial potential of S. lividans, understanding its metabolism and genetic regulatory elements is essential. This study aimed to determine its transcription unit (TU) architecture and elucidate its diverse regulatory elements, including promoters, ribosome binding sites, 5′-untranslated regions, and transcription terminators. Total 1,978 transcription start sites and 1,640 transcript 3′-end positions were identified, which were integrated to determine 1,300 TUs, consistent with transcriptomic profiles. The conserved promoter sequences were found as 5′-TANNNT and 5′-TGAC, representing the −10 and −35 elements, respectively. Analysis of transcript 3′-end positions revealed the presence of distinctive terminator sequences and the RNA stem structure responsible for the determination of the 3′-boundary of a transcript. Functionally related genes are likely to be regulated simultaneously by using similar promoters and being transcribed as a poly-cistronic TU. Poly-cistronic TUs were further processed or alternatively transcribed into multiple TUs to fine-regulate individual genes in response to environmental conditions. The TU information and regulatory elements identified will serve as invaluable resources for understanding the complex regulatory mechanisms of S. lividans and to elevate its industrial potential.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.