Growth-dependent Gene Expression Variation Influences the Strength of Codon Usage Biases.

The most highly expressed genes in microbial genomes tend to use a limited set of synonymous codons, often referred to as "preferred codons." The existence of preferred codons is commonly attributed to selection pressures on various aspects of protein translation including accuracy and/or speed. However, gene expression is condition-dependent and even within single-celled organisms transcript and protein abundances can vary depending on a variety of environmental and other factors. Here, we show that growth rate-dependent expression variation is an important constraint that significantly influences the evolution of gene sequences. Using large-scale transcriptomic and proteomic data sets in Escherichia coli and Saccharomyces cerevisiae, we confirm that codon usage biases are strongly associated with gene expression but highlight that this relationship is most pronounced when gene expression measurements are taken during rapid growth conditions. Specifically, genes whose relative expression increases during periods of rapid growth have stronger codon usage biases than comparably expressed genes whose expression decreases during rapid growth conditions. These findings highlight that gene expression measured in any particular condition tells only part of the story regarding the forces shaping the evolution of microbial gene sequences. More generally, our results imply that microbial physiology during rapid growth is critical for explaining long-term translational constraints.

pLannotate: engineered plasmid annotation.

Engineered plasmids are widely used in the biological sciences. Since many plasmids contain DNA sequences that have been reused and remixed by researchers for decades, annotation of their functional elements is often incomplete. Missing information about the presence, location, or precise identity of a plasmid feature can lead to unintended consequences or failed experiments. Many engineered plasmids contain sequences-such as recombinant DNA from all domains of life, wholly synthetic DNA sequences, and engineered gene expression elements-that are not predicted by microbial genome annotation pipelines. Existing plasmid annotation tools have limited feature libraries and do not detect incomplete fragments of features that are present in many plasmids for historical reasons and may impact their newly designed functions. We created the open source pLannotate web server so users can quickly and comprehensively annotate plasmid features. pLannotate is powered by large databases of genetic parts and proteins. It employs a filtering algorithm to display only the most relevant feature matches and also reports feature fragments. Finally, pLannotate displays a graphical map of the annotated plasmid, explains the provenance of each feature prediction, and allows results to be downloaded in a variety of formats. The webserver for pLannotate is accessible at: http://plannotate.barricklab.org/.

Functional Analysis of Bacteriophage Immunity through a Type I-E CRISPR-Cas System in Vibrio cholerae and Its Application in Bacteriophage Genome Engineering.

UNLABELLED: The classical and El Tor biotypes of Vibrio cholerae serogroup O1, the etiological agent of cholera, are responsible for the sixth and seventh (current) pandemics, respectively. A genomic island (GI), GI-24, previously identified in a classical biotype strain of V. cholerae, is predicted to encode clustered regularly interspaced short palindromic repeat (CRISPR)-associated proteins (Cas proteins); however, experimental evidence in support of CRISPR activity in V. cholerae has not been documented. Here, we show that CRISPR-Cas is ubiquitous in strains of the classical biotype but excluded from strains of the El Tor biotype. We also provide in silico evidence to suggest that CRISPR-Cas actively contributes to phage resistance in classical strains. We demonstrate that transfer of GI-24 to V. cholerae El Tor via natural transformation enables CRISPR-Cas-mediated resistance to bacteriophage CP-T1 under laboratory conditions. To elucidate the sequence requirements of this type I-E CRISPR-Cas system, we engineered a plasmid-based system allowing the directed targeting of a region of interest. Through screening for phage mutants that escape CRISPR-Cas-mediated resistance, we show that CRISPR targets must be accompanied by a 3' TT protospacer-adjacent motif (PAM) for efficient interference. Finally, we demonstrate that efficient editing of V. cholerae lytic phage genomes can be performed by simultaneously introducing an editing template that allows homologous recombination and escape from CRISPR-Cas targeting. IMPORTANCE: Cholera, caused by the facultative pathogen Vibrio cholerae, remains a serious public health threat. Clustered regularly interspaced short palindromic repeats and CRISPR-associated proteins (CRISPR-Cas) provide prokaryotes with sequence-specific protection from invading nucleic acids, including bacteriophages. In this work, we show that one genomic feature differentiating sixth pandemic (classical biotype) strains from seventh pandemic (El Tor biotype) strains is the presence of a CRISPR-Cas system in the classical biotype. We demonstrate that the CRISPR-Cas system from a classical biotype strain can be transferred to a V. cholerae El Tor biotype strain and that it is functional in providing resistance to phage infection. Finally, we show that this CRISPR-Cas system can be used as an efficient tool for the editing of V. cholerae lytic phage genomes.

Zinc oxide nanoparticle suspensions and layer-by-layer coatings inhibit staphylococcal growth.

Despite a decade of engineering and process improvements, bacterial infection remains the primary threat to implanted medical devices. Zinc oxide nanoparticles (ZnO-NPs) have demonstrated antimicrobial properties. Their microbial selectivity, stability, ease of production, and low cost make them attractive alternatives to silver NPs or antimicrobial peptides. Here we sought to (1) determine the relative efficacy of ZnO-NPs on planktonic growth of medically relevant pathogens; (2) establish the role of bacterial surface chemistry on ZnO-NP effectiveness; (3) evaluate NP shape as a factor in the dose-response; and (4) evaluate layer-by-layer (LBL) ZnO-NP surface coatings on biofilm growth. ZnO-NPs inhibited bacterial growth in a shape-dependent manner not previously seen or predicted. Pyramid shaped particles were the most effective and contrary to previous work, larger particles were more effective than smaller particles. Differential susceptibility of pathogens may be related to their surface hydrophobicity. LBL ZnO-NO coatings reduced staphylococcal biofilm burden by >95%. From the Clinical Editor: The use of medical implants is widespread. However, bacterial colonization remains a major concern. In this article, the authors investigated the use of zinc oxide nanoparticles (ZnO-NPs) to prevent bacterial infection. They showed in their experiments that ZnO-NPs significantly inhibited bacterial growth. This work may present a new alternative in using ZnO-NPs in medical devices.

Identifying widespread and recurrent variants of genetic parts to improve annotation of engineered DNA sequences.

Engineered plasmids have been workhorses of recombinant DNA technology for nearly half a century. Plasmids are used to clone DNA sequences encoding new genetic parts and to reprogram cells by combining these parts in new ways. Historically, many genetic parts on plasmids were copied and reused without routinely checking their DNA sequences. With the widespread use of high-throughput DNA sequencing technologies, we now know that plasmids often contain variants of common genetic parts that differ slightly from their canonical sequences. Because the exact provenance of a genetic part on a particular plasmid is usually unknown, it is difficult to determine whether these differences arose due to mutations during plasmid construction and propagation or due to intentional editing by researchers. In either case, it is important to understand how the sequence changes alter the properties of the genetic part. We analyzed the sequences of over 50,000 engineered plasmids using depositor metadata and a metric inspired by the natural language processing field. We detected 217 uncatalogued genetic part variants that were especially widespread or were likely the result of convergent evolution or engineering. Several of these uncatalogued variants are known mutants of plasmid origins of replication or antibiotic resistance genes that are missing from current annotation databases. However, most are uncharacterized, and 3/5 of the plasmids we analyzed contained at least one of the uncatalogued variants. Our results include a list of genetic parts to prioritize for refining engineered plasmid annotation pipelines, highlight widespread variants of parts that warrant further investigation to see whether they have altered characteristics, and suggest cases where unintentional evolution of plasmid parts may be affecting the reliability and reproducibility of science.

Measuring the burden of hundreds of BioBricks defines an evolutionary limit on constructability in synthetic biology.

Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Escape mutants that alleviate this burden can rapidly evolve and take over cell populations, making genetic engineering less reliable and predictable. Synthetic biologists often use genetic parts encoded on plasmids, but their burden is rarely characterized. We measured how 301 BioBrick plasmids affected Escherichia coli growth and found that 59 (19.6%) were burdensome, primarily because they depleted the limited gene expression resources of host cells. Overall, no BioBricks reduced the growth rate of E. coli by >45%, which agreed with a population genetic model that predicts such plasmids should be unclonable. We made this model available online for education ( https://barricklab.org/burden-model ) and added our burden measurements to the iGEM Registry. Our results establish a fundamental limit on what DNA constructs and genetic modifications can be successfully engineered into cells.

Measuring the burden of hundreds of BioBricks defines an evolutionary limit on constructability in synthetic biology.

Engineered DNA will slow the growth of a host cell if it redirects limiting resources or otherwise interferes with homeostasis. Populations of engineered cells can rapidly become dominated by "escape mutants" that evolve to alleviate this burden by inactivating the intended function. Synthetic biologists working with bacteria rely on genetic parts and devices encoded on plasmids, but the burden of different engineered DNA sequences is rarely characterized. We measured how 301 BioBricks on high-copy plasmids affected the growth rate of Escherichia coli. Of these, 59 (19.6%) negatively impacted growth. The burden imposed by engineered DNA is commonly associated with diverting ribosomes or other gene expression factors away from producing endogenous genes that are essential for cellular replication. In line with this expectation, BioBricks exhibiting burden were more likely to contain highly active constitutive promoters and strong ribosome binding sites. By monitoring how much each BioBrick reduced expression of a chromosomal GFP reporter, we found that the burden of most, but not all, BioBricks could be wholly explained by diversion of gene expression resources. Overall, no BioBricks reduced the growth rate of E. coli by >45%, which agreed with a population genetic model that predicts such plasmids should be "unclonable" because escape mutants will take over during growth of a bacterial colony or small laboratory culture from a transformed cell. We made this model available as an interactive web tool for synthetic biology education and added our burden measurements to the iGEM Registry descriptions of each BioBrick.

Identifying widespread and recurrent variants of genetic parts to improve annotation of engineered DNA sequences.

Engineered plasmids have been workhorses of recombinant DNA technology for nearly half a century. Plasmids are used to clone DNA sequences encoding new genetic parts and to reprogram cells by combining these parts in new ways. Historically, many genetic parts on plasmids were copied and reused without routinely checking their DNA sequences. With the widespread use of high-throughput DNA sequencing technologies, we now know that plasmids often contain variants of common genetic parts that differ slightly from their canonical sequences. Because the exact provenance of a genetic part on a particular plasmid is usually unknown, it is difficult to determine whether these differences arose due to mutations during plasmid construction and propagation or due to intentional editing by researchers. In either case, it is important to understand how the sequence changes alter the properties of the genetic part. We analyzed the sequences of over 50,000 engineered plasmids using depositor metadata and a metric inspired by the natural language processing field. We detected 217 uncatalogued genetic part variants that were especially widespread or were likely the result of convergent evolution or engineering. Several of these uncatalogued variants are known mutants of plasmid origins of replication or antibiotic resistance genes that are missing from current annotation databases. However, most are uncharacterized, and 3/5 of the plasmids we analyzed contained at least one of the uncatalogued variants. Our results include a list of genetic parts to prioritize for refining engineered plasmid annotation pipelines, highlight widespread variants of parts that warrant further investigation to see whether they have altered characteristics, and suggest cases where unintentional evolution of plasmid parts may be affecting the reliability and reproducibility of science.

Growth-dependent gene expression variation influences the strength of codon usage biases.

The most highly expressed genes in microbial genomes tend to use a limited set of synonymous codons, often referred to as "preferred codons." The existence of preferred codons is commonly attributed to selection pressures on various aspects of protein translation including accuracy and/or speed. However, gene expression is condition-dependent and even within single-celled organisms transcript and protein abundances can vary depending on a variety of environmental and other factors. Here, we show that growth rate-dependent expression variation is an important constraint that significantly influences the evolution of gene sequences. Using large-scale transcriptomic and proteomic data sets in Escherichia coli and Saccharomyces cerevisiae, we confirm that codon usage biases are strongly associated with gene expression but highlight that this relationship is most pronounced when gene expression measurements are taken during rapid growth conditions. Specifically, genes whose relative expression increases during periods of rapid growth have stronger codon usage biases than comparably expressed genes whose expression decreases during rapid growth conditions. These findings highlight that gene expression measured in any particular condition tells only part of the story regarding the forces shaping the evolution of microbial gene sequences. More generally, our results imply that microbial physiology during rapid growth is critical for explaining long-term translational constraints.