RNA interference (RNAi) is the process of sequence-specific post-transcriptional gene silencing triggered by double-stranded RNAs. In attempts to identify RNAi triggers that effectively function at lower concentrations, we found that synthetic RNA duplexes 25-30 nucleotides in length can be up to 100-fold more potent than corresponding conventional 21-mer small interfering RNAs (siRNAs). Some sites that are refractory to silencing by 21-mer siRNAs can be effectively targeted by 27-mer duplexes, with silencing lasting up to 10 d. Notably, the 27-mers do not induce interferon or activate protein kinase R (PKR). The enhanced potency of the longer duplexes is attributed to the fact that they are substrates of the Dicer endonuclease, directly linking the production of siRNAs to incorporation in the RNA-induced silencing complex. These results provide an alternative strategy for eliciting RNAi-mediated target cleavage using low concentrations of synthetic RNA as substrates for cellular Dicer-mediated cleavage.

We have sequenced and annotated the genome of the filamentous ascomycete Ashbya gossypii. With a size of only 9.2 megabases, encoding 4718 protein-coding genes, it is the smallest genome of a free-living eukaryote yet characterized. More than 90% of A. gossypii genes show both homology and a particular pattern of synteny with Saccharomyces cerevisiae. Analysis of this pattern revealed 300 inversions and translocations that have occurred since divergence of these two species. It also provided compelling evidence that the evolution of S. cerevisiae included a whole genome duplication or fusion of two related species and showed, through inferred ancient gene orders, which of the duplicated genes lost one copy and which retained both copies.

Growing concerns over limited fossil resources and associated environmental problems are motivating the development of sustainable processes for the production of chemicals, fuels and materials from renewable resources. Metabolic engineering is a key enabling technology for transforming microorganisms into efficient cell factories for these compounds. Systems metabolic engineering, which incorporates the concepts and techniques of systems biology, synthetic biology and evolutionary engineering at the systems level, offers a conceptual and technological framework to speed the creation of new metabolic enzymes and pathways or the modification of existing pathways for the optimal production of desired products. Here we discuss the general strategies of systems metabolic engineering and examples of its application and offer insights as to when and how each of the different strategies should be used. Finally, we highlight the limitations and challenges to be overcome for the systems metabolic engineering of microorganisms at more advanced levels.

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Mammalian skeletal muscles are capable of regeneration after injury. Quiescent satellite cells are activated to reenter the cell cycle and to differentiate for repair, recapitulating features of myogenesis during embryonic development. To understand better the molecular mechanism involved in this process in vivo, we employed high density cDNA microarrays for gene expression profiling in mouse tibialis anterior muscles after a cardiotoxin injection. Among 16,267 gene elements surveyed, 3,532 elements showed at least a 2.5-fold change at one or more time points during a 14-day time course. Hierarchical cluster analysis and semiquantitative reverse transcription-PCR showed induction of genes important for cell cycle control and DNA replication during the early phase of muscle regeneration. Subsequently, genes for myogenic regulatory factors, a group of imprinted genes and genes with functions to inhibit cell cycle progression and promote myogenic differentiation, were induced when myogenic stem cells started to differentiate. Induction of a majority of these genes, including E2f1 and E2f2, was abolished in muscles lacking satellite cell activity after gamma radiation. Regeneration was severely compromised in E2f1 null mice but not affected in E2f2 null mice. This study identifies novel genes potentially important for muscle regeneration and reveals highly coordinated myogenic cell proliferation and differentiation programs in adult skeletal muscle regeneration in vivo.Skeletal muscles are damaged and repaired repeatedly throughout life. Muscle regeneration maintains locomotor function during aging and delays the appearance of clinical symptoms in neuromuscular diseases, such as Duchenne muscular dystrophy (1, 2). This capacity for tissue repair is conferred by satellite cells located between the basal lamina and the sarcolemma of mature myofibers (3, 4). Upon injury, satellite cells reenter the cell cycle, proliferate, and then exit the cell cycle either to renew the quiescent satellite cell pool or to differentiate into mature myofibers (5). Understanding the molecular mechanism by which satellite cell activity is regulated could promote development of novel countermeasures to enhance muscle performance that is compromised by diseases or aging.Both the cell proliferation and differentiation programs are essential for myogenesis. Mammalian cells escape from quiescence (G 0 ) and enter the cell cycle by activating the Cdk 1 /Rb/ E2f signaling pathway (6, 7). In general, mitogen stimulation induces expression and assembly of the G 1 cyclin-dependent kinases (Cdks) (8, 9). Activation of Cdks causes phosphorylation of the retinoblastoma protein (Rb) (10, 11), leading to increased activities of a subset of E2f transcription factors (E2fs) (12) and up-regulation of a variety of E2f-responsive genes encoding proteins directly involved in DNA replication and cell cycle progression (13,14). On the other hand, myogenic differentiation is controlled by interactions of a network of myogenic transcription factors (15). Studies ...

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Structure-based drug design is becoming an essential tool for faster and more cost-efficient lead discovery relative to the traditional method. Genomic, proteomic, and structural studies have provided hundreds of new targets and opportunities for future drug discovery. This situation poses a major problem: the necessity to handle the “big data” generated by combinatorial chemistry. Artificial intelligence (AI) and deep learning play a pivotal role in the analysis and systemization of larger data sets by statistical machine learning methods. Advanced AI-based sophisticated machine learning tools have a significant impact on the drug discovery process including medicinal chemistry. In this review, we focus on the currently available methods and algorithms for structure-based drug design including virtual screening and de novo drug design, with a special emphasis on AI- and deep-learning-based methods used for drug discovery.

Platform chemicals composed of 2–6 carbons derived from fossil resources are used as important precursors for making a variety of chemicals and materials, including solvents, fuels, polymers, pharmaceuticals, perfumes, and foods. Due to concerns regarding our environment and the limited nature of fossil resources, however, increasing interest has focused on the development of sustainable technologies for producing these platform chemicals from renewable resources. The techniques and strategies for developing microbial strains for chemicals production have advanced rapidly, and it is becoming feasible to develop microbes for producing additional types of chemicals, including non‐natural molecules. In this study, we review the current status of the bio‐based production of major C2–C6 platform chemicals, focusing on the microbial production of platform chemicals that have been used for the production of chemical intermediates, building block compounds, and polymers. Biotechnol. Bioeng. 2012; 109: 2437–2459. © 2012 Wiley Periodicals, Inc.