Understanding key features of bacterial restriction-modification systems through quantitative modeling

Construction of prophage-free and highly-transformable Limosilactobacillus reuteri strains and their use for production of 1,3-propanediol

The lactic acid bacterium Limosilactobacillus reuteri (formerly Lactobacillus reuteri) is a desirable host for the production of 1,3-propanediol (1,3-PDO) from glycerol when 1,3-PDO is used in the food or cosmetic industry. However, the production is hindered by strain instability, causing cell lysis, and difficult gene manipulation. This study reveals that the stability of L. reuteri DSM 20016 and its 1,3-PDO production, especially in the alcohol dehydrogenases (ADHs)-deletion mutants, are greatly enhanced after the deletion of two prophages (Φ3 and Φ4) present in the L. reuteri's chromosome. The resulting phage-free and ADHs-deletion mutant could produce >825 mM 1,3-PDO in 48 h without cell lysis at the theoretical maximum yield on glucose of ~2 mol/mol. Compared to the wild-type strain, the mutant exhibited a 45.2% increase in 1,3-PDO production titer and a 2.1-fold increase in yield. In addition, this study reports that the transformation efficiency of L. reuteri Δadh2Δadh6 mutant strains were greatly enhanced by >300-fold after the deletion of prophage Φ3, probably due to the removal of a restriction-modification (RM) system which resides in the phage genome. With improved stability and higher transformation efficiency, recombinant L. reuteri DSM 20016 Δadh2Δadh6ΔΦ3ΔΦ4 can be a more reliable and amenable host for industrial applications.

Species Delineation and Comparative Genomics within the Campylobacter ureolyticus Complex

Campylobacter ureolyticus is an emerging pathogen increasingly appreciated as a common cause of gastroenteritis and extra-intestinal infections in humans. Outside the setting of gastroenteritis, little work has been done to describe the genomic content and relatedness of the species, especially regarding clinical isolates. We reviewed the epidemiology of clinical C. ureolyticus cultured by our institution over the past 10 years. Fifty-one unique C. ureolyticus isolates were identified between January 2010 and August 2022, mostly originating from abscesses and blood cultures. To clarify the taxonomic relationships between isolates and to attribute specific genes with different clinical manifestations, we sequenced 19 available isolates from a variety of clinical specimen types and conducted a pangenomic analysis with publicly available C. ureolyticus genomes. Digital DNA:DNA hybridization suggested that these C. ureolyticus comprised a species complex of 10 species clusters (SCs) and several subspecies clusters. Although some orthologous genes or gene functions were enriched in isolates found in different SCs and clinical specimens, no association was significant. Nearly a third of the isolates possessed antimicrobial resistance genes, including the ermA resistance gene, potentially conferring resistance to macrolides, the treatment of choice for severe human campylobacteriosis. This work effectively doubles the number of publicly available C. ureolyticus genomes, provides further clarification of taxonomic relationships within this bacterial complex, and identifies target SCs for future analysis.

New Insights for Biosensing: Lessons from Microbial Defense Systems

Microorganisms have gained defense systems during the lengthy process of evolution over millions of years. Such defense systems can protect them from being attacked by invading species (e.g., CRISPR-Cas for establishing adaptive immune systems and nanopore-forming toxins as virulence factors) or enable them to adapt to different conditions (e.g., gas vesicles for achieving buoyancy control). These microorganism defense systems (MDS) have inspired the development of biosensors that have received much attention in a wide range of fields including life science research, food safety, and medical diagnosis. This Review comprehensively analyzes biosensing platforms originating from MDS for sensing and imaging biological analytes. We first describe a basic overview of MDS and MDS-inspired biosensing platforms (e.g., CRISPR-Cas systems, nanopore-forming proteins, and gas vesicles), followed by a critical discussion of their functions and properties. We then discuss several transduction mechanisms (optical, acoustic, magnetic, and electrical) involved in MDS-inspired biosensing. We further detail the applications of the MDS-inspired biosensors to detect a variety of analytes (nucleic acids, peptides, proteins, pathogens, cells, small molecules, and metal ions). In the end, we propose the key challenges and future perspectives in seeking new and improved MDS tools that can potentially lead to breakthrough discoveries in developing a new generation of biosensors with a combination of low cost; high sensitivity, accuracy, and precision; and fast detection. Overall, this Review gives a historical review of MDS, elucidates the principles of emulating MDS to develop biosensors, and analyzes the recent advancements, current challenges, and future trends in this field. It provides a unique critical analysis of emulating MDS to develop robust biosensors and discusses the design of such biosensors using elements found in MDS, showing that emulating MDS is a promising approach to conceptually advancing the design of biosensors.

Genome-wide high-throughput signal peptide screening via plasmid pUC256E improves protease secretion in Lactiplantibacillus plantarum and Pediococcus acidilactici

BACKGROUND

Proteases catalyze the hydrolysis of peptide bonds of proteins, thereby improving dietary protein digestibility, nutrient availability, as well as flavor and texture of fermented food and feed products. The lactobacilli Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) and Pediococcus acidilactici are widely used in food and feed fermentations due to their broad metabolic capabilities and safe use. However, extracellular protease activity in these two species is low. Here, we optimized protease expression and secretion in L. plantarum and P. acidilactici via a genetic engineering strategy.

RESULTS

To this end, we first developed a versatile and stable plasmid, pUC256E, which can propagate in both L. plantarum and P. acidilactici. We then confirmed expression and secretion of protease PepG1 as a functional enzyme in both strains with the aid of the previously described L. plantarum-derived signal peptide LP_0373. To further increase secretion of PepG1, we carried out a genome-wide experimental screening of signal peptide functionality. A total of 155 predicted signal peptides originating from L. plantarum and 110 predicted signal peptides from P. acidilactici were expressed and screened for extracellular proteolytic activity in the two different strains, respectively. We identified 12 L. plantarum signal peptides and eight P. acidilactici signal peptides that resulted in improved yield of secreted PepG1. No significant correlation was found between signal peptide sequence properties and its performance with PepG1.

CONCLUSION

The vector developed here provides a powerful tool for rapid experimental screening of signal peptides in both L. plantarum and P. acidilactici. Moreover, the set of novel signal peptides identified was widely distributed across strains of the same species and even across some closely related species. This indicates their potential applicability also for the secretion of other proteins of interest in other L. plantarum or P. acidilactici host strains. Our findings demonstrate that screening a library of homologous signal peptides is an attractive strategy to identify the optimal signal peptide for the target protein, resulting in improved protein export.

Genomic Signatures of Honey Bee Association in an Acetic Acid Symbiont

Recent declines in the health of the honey bee have startled researchers and lay people alike as honey bees are agriculture's most important pollinator. Honey bees are important pollinators of many major crops and add billions of dollars annually to the US economy through their services. One factor that may influence colony health is the microbial community. Indeed, the honey bee worker digestive tract harbors a characteristic community of bee-specific microbes, and the composition of this community is known to impact honey bee health. However, the honey bee is a superorganism, a colony of eusocial insects with overlapping generations where nestmates cooperate, building a hive, gathering and storing food, and raising brood. In contrast to what is known regarding the honey bee worker gut microbiome, less is known of the microbes associated with developing brood, with food stores, and with the rest of the built hive environment. More recently, the microbe Bombella apis was identified as associated with nectar, with developing larvae, and with honey bee queens. This bacterium is related to flower-associated microbes such as Saccharibacter floricola and other species in the genus Saccharibacter, and initial phylogenetic analyses placed it as sister to these environmental bacteria. Here, we used comparative genomics of multiple honey bee-associated strains and the nectar-associated Saccharibacter to identify genomic changes that may be associated with the ecological transition to honey bee association. We identified several genomic differences in the honey bee-associated strains, including a complete CRISPR/Cas system. Many of the changes we note here are predicted to confer upon Bombella the ability to survive in royal jelly and defend themselves against mobile elements, including phages. Our results are a first step toward identifying potential function of this microbe in the honey bee superorganism.

From biophysics to 'omics and systems biology

Recent decades brought a revolution to biology, driven mainly by exponentially increasing amounts of data coming from "'omics" sciences. To handle these data, bioinformatics often has to combine biologically heterogeneous signals, for which methods from statistics and engineering (e.g. machine learning) are often used. While such an approach is sometimes necessary, it effectively treats the underlying biological processes as a black box. Similarly, systems biology deals with inherently complex systems, characterized by a large number of degrees of freedom, and interactions that are highly non-linear. To deal with this complexity, the underlying physical interactions are often (over)simplified, such as in Boolean modelling of network dynamics. In this review, we argue for the utility of applying a biophysical approach in bioinformatics and systems biology, including discussion of two examples from our research which address sequence analysis and understanding intracellular gene expression dynamics.

Endogenous Gene Regulation as a Predicted Main Function of Type I-E CRISPR/Cas System in E. coli

CRISPR/Cas is an adaptive bacterial immune system, whose CRISPR array can actively change in response to viral infections. However, Type I-E CRISPR/Cas in E. coli (an established model system), appears not to exhibit such active adaptation, which suggests that it might have functions other than immune response. Through computational analysis, we address the involvement of the system in non-canonical functions. To assess targets of CRISPR spacers, we align them against both E. coli genome and an exhaustive (~230) set of E. coli viruses. We systematically investigate the obtained alignments, such as hit distribution with respect to genome annotation, propensity to target mRNA, the target functional enrichment, conservation of CRISPR spacers and putative targets in related bacterial genomes. We find that CRISPR spacers have a statistically highly significant tendency to target i) host compared to phage genomes, ii) one of the two DNA strands, iii) genomic dsDNA rather than mRNA, iv) transcriptionally active regions, and v) sequences (cis-regulatory elements) with slower turn-over rate compared to CRISPR spacers (trans-factors). The results suggest that the Type I-E CRISPR/Cas system has a major role in transcription regulation of endogenous genes, with a potential to rapidly rewire these regulatory interactions, with targets being selected through naïve adaptation.

Effects of Population Dynamics on Establishment of a Restriction-Modification System in a Bacterial Host

In vivo dynamics of protein levels in bacterial cells depend on both intracellular regulation and relevant population dynamics. Such population dynamics effects, e.g., interplay between cell and plasmid division rates, are, however, often neglected in modeling gene expression regulation. Including them in a model introduces additional parameters shared by the dynamical equations, which can significantly increase dimensionality of the parameter inference. We here analyse the importance of these effects, on a case of bacterial restriction-modification (R-M) system. We redevelop our earlier minimal model of this system gene expression regulation, based on a thermodynamic and dynamic system modeling framework, to include the population dynamics effects. To resolve the problem of effective coupling of the dynamical equations, we propose a “mean-field-like” procedure, which allows determining only part of the parameters at a time, by separately fitting them to expression dynamics data of individual molecular species. We show that including the interplay between kinetics of cell division and plasmid replication is necessary to explain the experimental measurements. Moreover, neglecting population dynamics effects can lead to falsely identifying non-existent regulatory mechanisms. Our results call for advanced methods to reverse-engineer intracellular regulation from dynamical data, which would also take into account the population dynamics effects.

Controller protein of restriction-modification system Kpn2I affects transcription of its gene by acting as a transcription elongation roadblock

C-proteins control restriction-modification (R-M) systems' genes transcription to ensure sufficient levels of restriction endonuclease to allow protection from foreign DNA while avoiding its modification by excess methyltransferase. Here, we characterize transcription regulation in C-protein dependent R-M system Kpn2I. The Kpn2I restriction endonuclease gene is transcribed from a constitutive, weak promoter, which, atypically, is C-protein independent. Kpn2I C-protein (C.Kpn2I) binds upstream of the strong methyltransferase gene promoter and inhibits it, likely by preventing the interaction of the RNA polymerase sigma subunit with the -35 consensus element. Diminished transcription from the methyltransferase promoter increases transcription from overlapping divergent C-protein gene promoters. All known C-proteins affect transcription initiation from R-M genes promoters. Uniquely, the C.Kpn2I binding site is located within the coding region of its gene. C.Kpn2I acts as a roadblock stalling elongating RNA polymerase and decreasing production of full-length C.Kpn2I mRNA. Mathematical modeling shows that this unusual mode of regulation leads to the same dynamics of accumulation of R-M gene transcripts as observed in systems where C-proteins act at transcription initiation stage only. Bioinformatics analyses suggest that transcription regulation through binding of C.Kpn2I-like proteins within the coding regions of their genes may be widespread.

Features of CRISPR-Cas Regulation Key to Highly Efficient and Temporally-Specific crRNA Production

Bacterial immune systems, such as CRISPR-Cas or restriction-modification (R-M) systems, affect bacterial pathogenicity and antibiotic resistance by modulating horizontal gene flow. A model system for CRISPR-Cas regulation, the Type I-E system from Escherichia coli, is silent under standard laboratory conditions and experimentally observing the dynamics of CRISPR-Cas activation is challenging. Two characteristic features of CRISPR-Cas regulation in E. coli are cooperative transcription repression of cas gene and CRISPR array promoters, and fast non-specific degradation of full length CRISPR transcripts (pre-crRNA). In this work, we use computational modeling to understand how these features affect the system expression dynamics. Signaling which leads to CRISPR-Cas activation is currently unknown, so to bypass this step, we here propose a conceptual setup for cas expression activation, where cas genes are put under transcription control typical for a restriction-modification (R-M) system and then introduced into a cell. Known transcription regulation of an R-M system is used as a proxy for currently unknown CRISPR-Cas transcription control, as both systems are characterized by high cooperativity, which is likely related to similar dynamical constraints of their function. We find that the two characteristic CRISPR-Cas control features are responsible for its temporally-specific dynamical response, so that the system makes a steep (switch-like) transition from OFF to ON state with a time-delay controlled by pre-crRNA degradation rate. We furthermore find that cooperative transcription regulation qualitatively leads to a cross-over to a regime where, at higher pre-crRNA processing rates, crRNA generation approaches the limit of an infinitely abrupt system induction. We propose that these dynamical properties are associated with rapid expression of CRISPR-Cas components and efficient protection of bacterial cells against foreign DNA. In terms of synthetic applications, the setup proposed here should allow highly efficient expression of small RNAs in a narrow time interval, with a specified time-delay with respect to the signal onset.