| 1. |
- Repecka, Donatas, et al.
(författare)
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Expanding functional protein sequence spaces using generative adversarial networks
- 2021
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Ingår i: Nature Machine Intelligence. - : Springer Science and Business Media LLC. - 2522-5839. ; 3:4, s. 324-333
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Tidskriftsartikel (refereegranskat)abstract
- De novo protein design for catalysis of any desired chemical reaction is a long-standing goal in protein engineering because of the broad spectrum of technological, scientific and medical applications. However, mapping protein sequence to protein function is currently neither computationally nor experimentally tangible. Here, we develop ProteinGAN, a self-attention-based variant of the generative adversarial network that is able to ‘learn’ natural protein sequence diversity and enables the generation of functional protein sequences. ProteinGAN learns the evolutionary relationships of protein sequences directly from the complex multidimensional amino-acid sequence space and creates new, highly diverse sequence variants with natural-like physical properties. Using malate dehydrogenase (MDH) as a template enzyme, we show that 24% (13 out of 55 tested) of the ProteinGAN-generated and experimentally tested sequences are soluble and display MDH catalytic activity in the tested conditions in vitro, including a highly mutated variant of 106 amino-acid substitutions. ProteinGAN therefore demonstrates the potential of artificial intelligence to rapidly generate highly diverse functional proteins within the allowed biological constraints of the sequence space.
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| 2. |
- Sulcius, Sigitas, et al.
(författare)
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Genomic Characterization of Cyanophage vB_AphaS-CL131 Infecting Filamentous Diazotrophic Cyanobacterium Aphanizomenon flos-aquae Reveals Novel Insights into Virus-Bacterium Interactions
- 2019
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Ingår i: Applied and Environmental Microbiology. - : American Society of Microbiology. - 0099-2240 .- 1098-5336. ; 85:1
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Tidskriftsartikel (refereegranskat)abstract
- While filamentous cyanobacteria play a crucial role in food web dynamics and biogeochemical cycling of many aquatic ecosystems around the globe, the knowledge regarding the phages infecting them is limited. Here, we describe the complete genome of the virulent cyanophage vB_AphaS-CL131 (here, CL 131), a Siphoviridae phage that infects the filamentous diazotrophic bloom-forming cyanobacterium Aphanizomenon flos-aquae in the brackish Baltic Sea. CL 131 features a 112,793-bp double-stranded DNA (dsDNA) genome encompassing 149 putative open reading frames (ORFs), of which the majority (86%) lack sequence homology to genes with known functions in other bacteriophages or bacteria. Phylogenetic analysis revealed that CL 131 possibly represents a new evolutionary lineage within the group of cyanophages infecting filamentous cyanobacteria, which form a separate cluster from phages infecting unicellular cyanobacteria. CL 131 encodes a putative type V-U2 CRISPR-Cas system with one spacer (out of 10) targeting a DNA primase pseudogene in a cyanobacterium and a putative type II toxin-antitoxin system, consisting of a GNAT family N-acetyltransferase and a protein of unknown function containing the PRK09726 domain (characteristic of HipB antitoxins). Comparison of CL 131 proteins to reads from Baltic Sea and other available fresh- and brackish-water metagenomes and analysis of CRISPR-Cas arrays in publicly available A. flos-aquae genomes demonstrated that phages similar to CL 131 are present and dynamic in the Baltic Sea and share a common history with their hosts dating back at least several decades. In addition, different CRISPR-Cas systems within individual A. flos-aquae genomes targeted several sequences in the CL 131 genome, including genes related to virion structure and morphogenesis. Altogether, these findings revealed new genomic information for exploring viral diversity and provide a model system for investigation of virus-host interactions in filamentous cyanobacteria. IMPORTANCE The genomic characterization of novel cyanophage vB_AphaS-CL131 and the analysis of its genomic features in the context of other viruses, metagenomic data, and host CRISPR-Cas systems contribute toward a better understanding of aquatic viral diversity and distribution in general and of brackish-water cyanophages infecting filamentous diazotrophic cyanobacteria in the Baltic Sea in particular. The results of this study revealed previously undescribed features of cyanophage genomes (e.g., self-excising intein-containing putative dCTP deaminase and putative cyanophage-encoded CRISPR-Cas and toxin-antitoxin systems) and can therefore be used to predict potential interactions between bloom-forming cyanobacteria and their cyanophages.
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| 3. |
- Zrimec, Jan, 1981, et al.
(författare)
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Controlling gene expression with deep generative design of regulatory DNA
- 2022
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 13:1, s. 5099-
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Tidskriftsartikel (refereegranskat)abstract
- Design of de novo synthetic regulatory DNA is a promising avenue to control gene expression in biotechnology and medicine. Using mutagenesis typically requires screening sizable random DNA libraries, which limits the designs to span merely a short section of the promoter and restricts their control of gene expression. Here, we prototype a deep learning strategy based on generative adversarial networks (GAN) by learning directly from genomic and transcriptomic data. Our ExpressionGAN can traverse the entire regulatory sequence-expression landscape in a gene-specific manner, generating regulatory DNA with prespecified target mRNA levels spanning the whole gene regulatory structure including coding and adjacent non-coding regions. Despite high sequence divergence from natural DNA, in vivo measurements show that 57% of the highly-expressed synthetic sequences surpass the expression levels of highly-expressed natural controls. This demonstrates the applicability and relevance of deep generative design to expand our knowledge and control of gene expression regulation in any desired organism, condition or tissue.
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