Automated design of bacterial genome sequences

Background: Organisms have evolved ways of regulating transcription to better adapt to varying environments. Could the current functional genomics data and models support the possibility of engineering a genome with completely rearranged gene organization while the cell maintains its behavior under environmental challenges? How would we proceed to design a full nucleotide sequence for such genomes? Results: As a first step towards answering such questions, recent work showed that it is possible to design alternative transcriptomic models showing the same behavior under environmental variations than the wild-type model. A second step would require providing evidence that it is possible to provide a nucleotide sequence for a genome encoding such transcriptional model. We used computational design techniques to design a rewired global transcriptional regulation of Escherichia coli, yet showing a similar transcriptomic response than the wild-type. Afterwards, we “compiled” the transcriptional networks into nucleotide sequences to obtain the final genome sequence. Our computational evolution procedure ensures that we can maintain the genotype-phenotype mapping during the rewiring of the regulatory network. We found that it is theoretically possible to reorganize E. coli genome into 86% fewer regulated operons. Such refactored genomes are constituted by operons that contain sets of genes sharing around the 60% of their biological functions and, if evolved under highly variable environmental conditions, have regulatory networks, which turn out to respond more than 20% faster to multiple external perturbations. Conclusions: This work provides the first algorithm for producing a genome sequence encoding a rewired transcriptional regulation with wild-type behavior under alternative environments

The physicist's guide to one of biotechnology's hottest new topics: CRISPR-Cas

Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (Cas) constitute a multi-functional, constantly evolving immune system in bacteria and archaea cells. A heritable, molecular memory is generated of phage, plasmids, or other mobile genetic elements that attempt to attack the cell. This memory is used to recognize and interfere with subsequent invasions from the same genetic elements. This versatile prokaryotic tool has also been used to advance applications in biotechnology. Here we review a large body of CRISPR-Cas research to explore themes of evolution and selection, population dynamics, horizontal gene transfer, specific and cross-reactive interactions, cost and regulation, non-immunological CRISPR functions that boost host cell robustness, as well as applicable mechanisms for efficient and specific genetic engineering. We offer future directions that can be addressed by the physics community. Physical understanding of the CRISPR-Cas system will advance uses in biotechnology, such as developing cell lines and animal models, cell labeling and information storage, combatting antibiotic resistance, and human therapeutics.Comment: 75 pages, 15 figures, Physical Biology (2018

Adaptive evolution of hybrid bacteria by horizontal gene transfer

Horizontal gene transfer is an important factor in bacterial evolution that can act across species boundaries. Yet, we know little about rate and genomic targets of cross-lineage gene transfer, and about its effects on the recipient organism's physiology and fitness. Here, we address these questions in a parallel evolution experiment with two Bacillus subtilis lineages of 7% sequence divergence. We observe rapid evolution of hybrid organisms: gene transfer swaps ~12% of the core genome in just 200 generations, and 60% of core genes are replaced in at least one population. By genomics, transcriptomics, fitness assays, and statistical modeling, we show that transfer generates adaptive evolution and functional alterations in hybrids. Specifically, our experiments reveal a strong, repeatable fitness increase of evolved populations in the stationary growth phase. By genomic analysis of the transfer statistics across replicate populations, we infer that selection on HGT has a broad genetic basis: 40% of the observed transfers are adaptive. At the level of functional gene networks, we find signatures of negative and positive selection, consistent with hybrid incompatibilities and adaptive evolution of network functions. Our results suggest that gene transfer navigates a complex cross-lineage fitness landscape, bridging epistatic barriers along multiple high-fitness paths.Comment: The first three authors are joint first authors. Corresponding authors are Lassig and Maie

At the nexus of three kingdoms: the genome of the mycorrhizal fungus Gigaspora margarita provides insights into plant, endobacterial and fungal interactions.

As members of the plant microbiota, arbuscular mycorrhizal fungi (AMF, Glomeromycotina) symbiotically colonize plant roots. AMF also possess their own microbiota, hosting some uncultivable endobacteria. Ongoing research has revealed the genetics underlying plant responses to colonization by AMF, but the fungal side of the relationship remains in the dark. Here, we sequenced the genome of Gigaspora margarita, a member of the Gigasporaceae in an early diverging group of the Glomeromycotina. In contrast to other AMF, G. margarita may host distinct endobacterial populations and possesses the largest fungal genome so far annotated (773.104 Mbp), with more than 64% transposable elements. Other unique traits of the G. margarita genome include the expansion of genes for inorganic phosphate metabolism, the presence of genes for production of secondary metabolites and a considerable number of potential horizontal gene transfer events. The sequencing of G. margarita genome reveals the importance of its immune system, shedding light on the evolutionary pathways that allowed early diverging fungi to interact with both plants and bacteria

Adaptive laboratory evolution of a genome-reduced Escherichia coli.

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

Contextualizing context for synthetic biology--identifying causes of failure of synthetic biological systems.

Despite the efforts that bioengineers have exerted in designing and constructing biological processes that function according to a predetermined set of rules, their operation remains fundamentally circumstantial. The contextual situation in which molecules and single-celled or multi-cellular organisms find themselves shapes the way they interact, respond to the environment and process external information. Since the birth of the field, synthetic biologists have had to grapple with contextual issues, particularly when the molecular and genetic devices inexplicably fail to function as designed when tested in vivo. In this review, we set out to identify and classify the sources of the unexpected divergences between design and actual function of synthetic systems and analyze possible methodologies aimed at controlling, if not preventing, unwanted contextual issues

Evolution, metabolism, and virulence of the oral microbiome

textThe human microbiome has important roles in maintaining health, but dysbiosis of the microbiota can lead to disease. Polymicrobial interactions can result in synergy, producing disease that is worse than the sum of the respective single species infections. Despite this significant impact, synergy is understudied due to the complexity of polymicrobial interactions. Periodontitis is a microbiome-associated disease, and is one of the most common infectious diseases worldwide. Therefore, we have used periodontal disease as a model to study polymicrobial synergy. I have used two complementary approaches to study polymicrobial infections. The opportunistic periodontal pathogen Aggregatibacter actinomycetemcomitans exhibits synergy with streptococci in model murine infections. Because polymicrobial interactions are dependent on organisms’ abilities to sense their environments, I have examined the genetic regulatory mechanisms used by A. actinomycetemcomitans to interact with its environment. Through Northern blot analyses and biochemical approaches, I show that A. actinomycetemcomitans uses non-coding RNAs to regulate amino acid transport. Taking a comparative genomics approach, I demonstrate that A. actinomycetemcomitans DNA uptake systems are evolutionarily linked to genome defense. To describe host-influenced changes in gene expression, I develop a new technique to transcriptionally profile A. actinomycetemcomitans in a murine abscess infection, thereby revealing the importance of specific fermentative and anaerobic respiratory genes for in vivo survival. The long-term goal is to use these studies as a basis to characterize genetic regulatory mechanisms mediating synergy in polymicrobial A. actinomycetemcomitans infections with streptococci and other oral microbes. As a second approach to study polymicrobial infections, I analyze gene expression of healthy and diseased human plaque communities from aggressive periodontitis patients. Profiling ribosome content of healthy and diseased communities, I show that disease communities adopt similar less diverse population structures distinct from healthy populations. In addition to changes in population composition, using community transcriptional profiling I show that a keystone species within diseased communities up-regulates expression of genes involved in making the oral inflammatory molecule butyrate. These studies demonstrate for the first time that microbiome based diseases are marked by gene expression changes in addition to compositional changes.Microbiolog

Fitness of Isogenic Colony Morphology Variants of Pseudomonas aeruginosa in Murine Airway Infection

Chronic lung infections with Pseudomonas aeruginosa are associated with the diversification of the persisting clone into niche specialists and morphotypes, a phenomenon called ‘dissociative behaviour’. To explore the potential of P. aeruginosa to change its morphotype by single step loss-of–function mutagenesis, a signature-tagged mini-Tn5 plasposon library of the cystic fibrosis airway isolate TBCF10839 was screened for colony morphology variants under nine different conditions in vitro. Transposon insertion into 1% of the genome changed colony morphology into eight discernable morphotypes. Half of the 55 targets encode features of primary or secondary metabolism whereby quinolone production was frequently affected. In the other half the transposon had inserted into genes of the functional categories transport, regulation or motility/chemotaxis. To mimic dissociative behaviour of isogenic strains in lungs, pools of 25 colony morphology variants were tested for competitive fitness in an acute murine airway infection model. Six of the 55 mutants either grew better or worse in vivo than in vitro, respectively. Metabolic proficiency of the colony morphology variant was a key determinant for survival in murine airways. The most common morphotype of self-destructive autolysis did unexpectedly not impair fitness. Transposon insertions into homologous genes of strain PAO1 did not reproduce the TBCF10839 mutant morphotypes for 16 of 19 examined loci pointing to an important role of the genetic background on colony morphology. Depending on the chosen P. aeruginosa strain, functional genome scans will explore other areas of the evolutionary landscape. Based on our discordant findings of mutant phenotypes in P. aeruginosa strains PAO1, PA14 and TBCF10839, we conclude that the current focus on few reference strains may miss modes of niche adaptation and dissociative behaviour that are relevant for the microevolution of complex traits in the wild