Benjamin A. Blount

Transcriptomics experiments are often conducted to capture changes in gene expression over time. However, time annotations may be missing, imprecise, or not reflect the same physiological state of the bacterial culture between different experiments. Assigning accurate time points to these experiments using a reference time course is therefore crucial for identifying differentially expressed genes, and understanding gene regulatory networks for elucidating the studied organism’s physiology and life cycle. This important task, which could enhance the biological interpretation of the transcriptomics experiments, has not been previously addressed. In this work, we propose a novel method to solve the challenge of realigning transcriptomics experiments based on a reference time course. Our method is based on a Bayesian approach that uses Gaussian process regression modeling. We show a use case of applying our method for assigning time annotations in legacy microarray samples of the bacterium Clostridium botulinum, which were solely annotated based on the growth phase at the time when the culture aliquots were sampled, utilizing recently collected RNA-Seq time series data comprising multiple replicates as a reference. The method significantly improved the description of the growth phases of the microarray data compared to the original annotations by clearly delineating the microarray samples belonging to different growth phases, as demonstrated by principal component analysis. Consequently, a larger number of differentially expressed genes was detected when comparing experiments belonging to successive growth phases. We compare this innovative approach with a baseline method that uses k-nearest neighbor algorithm and show that our method offers a higher resolution in the description of the data by exposing smaller time changes between samples. We also test the performance of the method on sparse RNA-Seq time series (i.e. sampled every second hour). All the predictions for the samples were within a 30-min margin of their true time.

Naturally evolved organisms typically have large genomes that enable their survival and growth under various conditions. However, the complexity of genomes often precludes our complete understanding of them, and limits the success of biotechnological designs. In contrast, minimal genomes have reduced complexity and therefore improved engineerability, increased biosynthetic capacity through the removal of unnecessary genetic elements, and less recalcitrance to complete characterisation. Here, we review the past and current genome minimisation and re-functionalisation efforts, with an emphasis on the latest advances facilitated by synthetic genomics, and provide a critical appraisal of their potential for industrial applications.

Here we report the design, construction and characterization of a tRNA neochromosome, a designer chromosome that functions as an additional, de novo counterpart to the native complement of Saccharomyces cerevisiae . Intending to address one of the central design principles of the Sc2.0 project, the ∼190 kb tRNA neochromosome houses all 275 relocated nuclear tRNA genes. To maximize stability, the design incorporated orthogonal genetic elements from non- S. cerevisiae yeast species. Furthermore, the presence of 283 rox recombination sites enable an orthogonal SCRaMbLE system capable of adjusting tRNA abundance. Following construction, we obtained evidence of a potent selective force once the neochromosome was introduced into yeast cells, manifesting as a spontaneous doubling in cell ploidy. Furthermore, tRNA sequencing, transcriptomics, proteomics, nucleosome mapping, replication profiling, FISH and Hi-C were undertaken to investigate questions of tRNA neochromosome behavior and function. Its construction demonstrates the remarkable tractability of the yeast model and opens up new opportunities to directly test hypotheses surrounding these essential non-coding RNAs. Highlights: De novo design, construction and functional characterization of a neochromosome containing all 275 nuclear tRNA genes of Saccharomyces cerevisiae . Increasing the copy number of the 275 highly expressed tRNA genes causes cellular burden, which the host cell likely buffers either by selecting for partial tRNA neochromosome deletions or by increasing its ploidy. The tRNA neochromosome can be chemically extracted and transformed into new strain backgrounds, enabling its transplantation into multi-synthetic chromosome strains to finalize the Sc2.0 strain. Comprehensive functional characterization does not pinpoint a singular cause for the cellular burden caused by the tRNA neochromosome, but does reveal novel insights into its tRNA and structural chromosome biology.

Summary: We describe construction of the 660 kilobase synthetic yeast chromosome XI ( synXI ) and reveal how synthetic redesign of non-coding DNA elements impact the cell. To aid construction from synthesized 5 to 10 kilobase DNA fragments, we implemented CRISPR-based methods for synthetic crossovers in vivo and used these methods in an extensive process of bug discovery, redesign and chromosome repair, including for the precise removal of 200 kilobases of unexpected repeated sequence. In synXI , the underlying causes of several fitness defects were identified as modifications to non-coding DNA, including defects related to centromere function and mitochondrial activity that were subsequently corrected. As part of synthetic yeast chromosome design, loxPsym sequences for Cre-mediated recombination are inserted between most genes. Using the GAP1 locus from chromosome XI , we show here that targeted insertion of these sites can be used to create extrachromosomal circular DNA on demand, allowing direct study of the effects and propagation of these important molecules. Construction and characterization of synXI has uncovered effects of non-coding and extrachromosomal circular DNA, contributing to better understanding of these elements and informing future synthetic genome design.

Synthetic biology tools, such as modular parts and combinatorial DNA assembly, are routinely used to optimise the productivity of heterologous metabolic pathways for biosynthesis or substrate utilisation, yet it is well established that host strain background is just as important for determining productivity. Here we report that in vivo combinatorial genomic rearrangement of Saccharomyces cerevisiae yeast with a synthetic chromosome V can rapidly generate new, improved host strains with genetic backgrounds favourable to diverse heterologous pathways, including those for violacein and penicillin biosynthesis and for xylose utilisation. We show how the modular rearrangement of synthetic chromosomes by SCRaMbLE can be easily determined using long-read nanopore sequencing and we explore experimental conditions that optimise diversification and screening. This synthetic genome approach to metabolic engineering provides productivity improvements in a fast, simple and accessible way, making it a valuable addition to existing strain improvement techniques.

The Synthetic Genome Summer Course was convened with the aim of teaching a wide range of researchers the theory and practical skills behind recent advances in synthetic biology and synthetic genome science, with a focus on Sc2.0, the synthetic yeast genome project. Through software workshops, tutorials and research talks from leading members of the field, the 30 attendees learnt about relevant principles and techniques that they were then able to implement first-hand in laboratory-based practical sessions. Participants SCRaMbLEd semi-synthetic yeast strains to diversify heterologous pathways, used automation to build combinatorial pathway libraries and used CRISPR to debug fitness defects caused by synthetic chromosome design changes. Societal implications of synthetic chromosomes were explored and industrial stakeholders discussed synthetic biology from a commercial standpoint. Over the 5 days, participants gained valuable insight and acquired skills to aid them in future synthetic genome research.

Fungi are a valuable source of enzymatic diversity and therapeutic natural products including antibiotics. Here we engineer the baker’s yeast Saccharomyces cerevisiae to produce and secrete the antibiotic penicillin, a beta-lactam nonribosomal peptide, by taking genes from a filamentous fungus and directing their efficient expression and subcellular localization. Using synthetic biology tools combined with long-read DNA sequencing, we optimize productivity by 50-fold to produce bioactive yields that allow spent S. cerevisiae growth media to have antibacterial action against Streptococcus bacteria. This work demonstrates that S. cerevisiae can be engineered to perform the complex biosynthesis of multicellular fungi, opening up the possibility of using yeast to accelerate rational engineering of nonribosomal peptide antibiotics.