Molecular Modeling the Proteins from the exo-xis Region of Lambda and Shigatoxigenic Bacteriophages

Despite decades of intensive research on bacteriophage lambda, a relatively uncharacterized region remains between the exo and xis genes. Collectively, exo-xis region genes are expressed during the earliest stages of the lytic developmental cycle and are capable of affecting the molecular events associated with the lysogenic-lytic developmental decision. In Shiga toxin-producing E. coli (STEC) and enterohemorragic E. coli (EHEC) that are responsible for food- and water-borne outbreaks throughout the world, there are distinct differences of exo-xis region genes from their counterparts in lambda phage. Together, these differences may help EHEC-specific phage and their bacterial hosts adapt to the complex environment within the human intestine. Only one exo-xis region protein, Ea8.5, has been solved to date. Here, I have used the AlphaFold and RoseTTAFold machine learning algorithms to predict the structures of six exo-xis region proteins from lambda and STEC/EHEC phages. Together, the models suggest possible roles for exo-xis region proteins in transcription and the regulation of RNA polymerase.

The Binding of Monoclonal and Polyclonal Anti-Z-DNA Antibodies to DNA of Various Species Origin

DNA is a polymeric macromolecule that can display a variety of backbone conformations. While the classical B-DNA is a right-handed double helix, Z-DNA is a left-handed helix with a zig-zag orientation. The Z conformation depends upon the base sequence, base modification and supercoiling and is considered to be transient. To determine whether the presence of Z-DNA can be detected immunochemically, the binding of monoclonal and polyclonal anti-Z-DNA antibodies to a panel of natural DNA antigens was assessed by an ELISA using brominated poly(dG-dC) as a control for Z-DNA. As these studies showed, among natural DNA tested (Micrococcus luteus, calf thymus, Escherichiacoli, salmon sperm, lambda phage), micrococcal (MC) DNA showed the highest binding with both anti-Z-DNA preparations, and E. coli DNA showed binding with the monoclonal anti-DNA preparation. The specificity for Z-DNA conformation in MC DNA was demonstrated by an inhibition binding assay. An algorithm to identify propensity to form Z-DNA indicated that DNA from Mycobacterium tuberculosis could form Z-DNA, a prediction confirmed by immunoassay. Together, these findings indicate that anti-Z-DNA antibodies can serve as probes for the presence of Z-DNA in DNA of various species origin and that the content of Z-DNA varies significantly among DNA sources.

Swarm-mediated phage transport disrupts a biofilm inherently protected from phage penetration

Phage therapy is the treatment of chronic bacterial infections by virus that kill bacteria and it has shown promise in combating antimicrobial resistance (AMR). A typical phage particle is around 100 times bigger than a typical antibiotic molecule. Due to larger size, a phage particle diffuses slower than an antibiotic molecule, and can get trapped in the polymeric mesh of biofilm matrix. We report that a swarm of Capnocytophaga gingivalis, a bacterium abundant in the human oral microbiota, can actively transport phages over long distances. By tracking fluorescently labeled lambda phage particles that do not infect C. gingivalis, we demonstrate active predator transport by a C. gingivalis swarm. As a result, the rate of disruption of the prey i.e., an Escherichia coli colony increases 10 times. Production of curli fiber by a mature E. coli biofilm blocks the intercellular space and is known to inhibit the diffusion of phages within a biofilm. We find that C. gingivalis forms tunnels within the prey biofilm. When phages are actively delivered, curli fiber containing E. coli biofilms are no longer protected against phage infection. Our results demonstrate that active delivery of the predator by a self-propelled swarm might improve the pharmacokinetics of phage therapy. This can lead to the development of a tool to combat chronic AMR biofilms.

Biophysical ambiguities prevent accurate genetic prediction

A goal of biology is to predict how mutations combine to alter phenotypes, fitness and disease. It is often assumed that mutations combine additively or with interactions that can be predicted. Here, we show using simulations that, even for the simple example of the lambda phage transcription factor CI repressing a gene, this assumption is incorrect and that perfect measurements of the effects of mutations on a trait and mechanistic understanding can be insufficient to predict what happens when two mutations are combined. This apparent paradox arises because mutations can have different biophysical effects to cause the same change in a phenotype and the outcome in a double mutant depends upon what these hidden biophysical changes actually are. Pleiotropy and non-monotonic functions further confound prediction of how mutations interact. Accurate prediction of phenotypes and disease will sometimes not be possible unless these biophysical ambiguities can be resolved using additional measurements.

The Protein Hourglass: Exact First Passage Time Distributions for Protein Thresholds

Protein thresholds have been shown to act as an ancient timekeeping device, such as in the time to lysis of E. coli infected with bacteriophage lambda. The time taken for protein levels to reach a particular threshold for the first time is defined as the first passage time of the protein synthesis system, which is a stochastic quantity. The first few moments of the distribution of first passage times were known earlier, but an analytical expression for the full distribution was not available. In this work, we derive an analytical expression for the first passage times for a long-lived protein. This expression allows us to calculate the full distribution not only for cases of no self-regulation, but also for both positive and negative self-regulation of the threshold protein. We show that the shape of the distribution matches previous experimental data on lambda-phage lysis time distributions. We also provide analytical expressions for the FPT distribution with non-zero degradation in Laplace space. Furthermore, we study the noise in the precision of the first passage times described by coefficient of variation (CV) of the distribution as a function of the protein threshold value. We show that under conditions of positive self-regulation, the CV declines monotonically with increasing protein threshold, while under conditions of linear negative self-regulation, there is an optimal protein threshold that minimizes the noise in the first passage times.

Quantification of lysogeny caused by phage coinfections in microbial communities from biophysical principles

Temperate phages can integrate in their bacterial host genome to form a lysogen, often modifying the phenotype of the host. Lysogens are dominant in the microbial-dense environment of the mammalian-gut. This observation contrasts with the long-standing hypothesis of lysogeny being favored in microbial communities with low densities. Here we hypothesized that phage coinfections—the most studied molecular mechanism of lysogeny in lambda phage—increases at high microbial abundances. To test this hypothesis, we developed a biophysical model of coinfection and stochastically sampled ranges of phage and bacterial concentrations, adsorption rates, lysogenic commitment times, and community diversity from marine and gut microbiomes. Based on lambda experiments, a Poisson process assessed the probability of lysogeny via coinfection in these ecosystems. In 90% of the sampled marine ecosystems, lysogeny stayed below 10% of the bacterial community. In contrast, 25% of the sampled gut communities stayed above 25% of lysogeny, representing an estimated nine trillion lysogens formed via phage coinfection in the human gut every day. The prevalence of lysogeny in the gut was a consequence of the higher densities and faster adsorption rates. In marine communities, which were characterized by lower densities and phage adsorption rates, lysogeny via coinfection was still possible for communities with long lysogenic commitments times. Our study suggests that physical mechanisms can favor coinfection and cause lysogeny at poor growth conditions (long commitment times) and in rich environments (high densities and adsorption rates).ImportancePhage integration in bacterial genomes manipulate microbial dynamics from the oceans to the human gut. This phage-bacteria interaction, called lysogeny, is well-studied in laboratory models, but its environmental drivers remain unclear. Here we quantified the frequency of lysogeny via phage coinfection—the most studied mechanism of lysogeny—by developing a biophysical model that incorporated a meta-analysis of the properties of marine and gut microbiomes. Lysogeny was found to be more frequent in high-productive environments like the gut, due to higher phage and bacterial densities and faster phage adsorption rates. At low cell densities, lysogeny via coinfection was possible for hosts with long duplication times. Our research bridges the molecular understanding of lysogeny with the ecology of complex microbial communities.

I-Block: a simple Escherichia coli-based assay for studying sequence-specific DNA binding of proteins

We have developed a simple method called I-Block assay, which can detect sequence-specific binding of proteins to DNA in Escherichia coli. The method works by detecting competition between the protein of interest and RNA polymerase for binding to overlapping target sites in a plasmid-borne lacI promoter variant. The assay utilizes two plasmids and an E. coli host strain, from which the gene of the Lac repressor (lacI) has been deleted. One of the plasmids carries the lacI gene with a unique NheI restriction site created in the lacI promoter. The potential recognition sequences of the tested protein are inserted into the NheI site. Introduction of the plasmids into the E. coliΔlacI host represses the constitutive β-galactosidase synthesis of the host bacterium. If the studied protein expressed from a compatible plasmid binds to its target site in the lacI promoter, it will interfere with lacI transcription and lead to increased β-galactosidase activity. The method was tested with two zinc finger proteins, with the lambda phage cI857 repressor, and with CRISPR-dCas9 targeted to the lacI promoter. The I-Block assay was shown to work with standard liquid cultures, with cultures grown in microplate and with colonies on X-gal indicator plates.