Late-Arriving Signals Contribute Less to Cell-Fate Decisions

Liver X Receptor-Inducible Host E3 Ligase IDOL Targets a Human Cytomegalovirus Reactivation Determinant

Liver X receptor (LXR) signaling broadly restricts virus replication; however, the mechanisms of restriction are poorly defined. Here, we demonstrate that the cellular E3 ligase LXR-inducible degrader of low-density lipoprotein receptor (IDOL) targets the human cytomegalovirus (HMCV) UL136p33 protein for turnover. UL136 encodes multiple proteins that differentially impact latency and reactivation. UL136p33 is a determinant of reactivation. UL136p33 is targeted for rapid turnover by the proteasome, and its stabilization by mutation of lysine residues to arginine results in a failure to quiet replication for latency. We show that IDOL targets UL136p33 for turnover but not the stabilized variant. IDOL is highly expressed in undifferentiated hematopoietic cells where HCMV establishes latency but is sharply downregulated upon differentiation, a stimulus for reactivation. We hypothesize that IDOL maintains low levels of UL136p33 for the establishment of latency. Consistent with this hypothesis, knockdown of IDOL impacts viral gene expression in wild-type (WT) HCMV infection but not in infection where UL136p33 has been stabilized. Furthermore, the induction of LXR signaling restricts WT HCMV reactivation from latency but does not affect the replication of a recombinant virus expressing a stabilized variant of UL136p33. This work establishes the UL136p33-IDOL interaction as a key regulator of the bistable switch between latency and reactivation. It further suggests a model whereby a key viral determinant of HCMV reactivation is regulated by a host E3 ligase and acts as a sensor at the tipping point between the decision to maintain the latent state or exit latency for reactivation. IMPORTANCE Herpesviruses establish lifelong latent infections, which pose an important risk for disease particularly in the immunocompromised. Our work is focused on the betaherpesvirus human cytomegalovirus (HCMV) that latently infects the majority of the population worldwide. Defining the mechanisms by which HCMV establishes latency or reactivates from latency is important for controlling viral disease. Here, we demonstrate that the cellular inducible degrader of low-density lipoprotein receptor (IDOL) targets a HCMV determinant of reactivation for degradation. The instability of this determinant is important for the establishment of latency. This work defines a pivotal virus-host interaction that allows HCMV to sense changes in host biology to navigate decisions to establish latency or to replicate.

CO-INFECTING PHAGES IMPEDE EACH OTHER'S ENTRY INTO THE CELL

Bacteriophage lambda tunes its propensity to lysogenize based on the number of viral genome copies inside the infected cell. Viral self-counting is believed to serve as a way of inferring the abundance of available hosts in the environment. This interpretation is premised on an accurate mapping between the extracellular phage-to-bacteria ratio and the intracellular multiplicity of infection (MOI). However, here we show this premise to be untrue. By simultaneously labeling phage capsids and genomes, we find that, while the number of phages landing on each cell reliably samples the population ratio, the number of phages entering the cell does not. Single-cell infections, followed in a microfluidic device and interpreted using a stochastic model, reveal that the probability and rate of individual phage entries decrease with MOI. This decrease reflects an MOI-dependent perturbation to host physiology caused by phage landing, evidenced by compromised membrane integrity and loss of membrane potential. The dependence of phage entry dynamics on the surrounding medium is found to result in a strong impact of environmental conditions on the infection outcome, while the protracted entry of co-infecting phages increases the cell-to-cell variability in infection outcome at a given MOI. Our findings demonstrate the previously unappreciated role played by entry dynamics in determining the outcome of bacteriophage infection.

The complex biology of human cytomegalovirus latency

While many viral infections are limited and eventually resolved by the host immune response or by death of the host, other viruses establish long-term relationships with the host by way of a persistent infection, that range from chronic viruses that may be eventually cleared to those that establish life-long persistent or latent infection. Viruses infecting hosts from bacteria to humans establish quiescent infections that must be reactivated to produce progeny. For mammalian viruses, most notably herpesviruses, this quiescent maintenance of viral genomes in the absence of virus replication is referred to as latency. The latent strategy allows the virus to persist quiescently within a single host until conditions indicate a need to reactivate to reach a new host or, to re-seed a reservoir within the host. Here, I review common themes in viral strategies to regulate the latent cycle and reactivate from it ranging from bacteriophage to herpesviruses with a focus on human cytomegalovirus (HCMV). Themes central to herpesvirus latency include, epigenetic repression of viral gene expression and mechanisms to regulate host signaling and survival. Critical to the success of a latent program are mechanisms by which the virus can "sense" fluctuations in host biology (within the host) or environment (outside the host) and make appropriate "decisions" to maintain latency or re-initiate the replicative program. The signals or environments that indicate the establishment of a latent state, the very nature of the latent state, as well as the signals driving reactivation have been topics of intense study from bacteriophage to human viruses, as these questions encompass the height of complexity in virus-host interactions-where the host and the virus coexist.

Exact Distribution of Threshold Crossing Times for Protein Concentrations: Implication for Biological Timekeeping

Stochastic protein accumulation up to some concentration threshold sets the timing of many cellular physiological processes. Here we obtain the exact distribution of first threshold crossing times of protein concentration, in either Laplace or time domain, and its associated cumulants: mean, variance, and skewness. The distribution is asymmetric, and its skewness nonmonotonically varies with the threshold. We study lysis times of E. coli cells for holin gene mutants of bacteriophage-λ and find a good match with theory. Mutants requiring higher holin thresholds show more skewed lysis time distributions as predicted. The theory also predicts a linear relationship between infection delay time and host doubling time for lytic viruses, that has recently been experimentally observed.

Conjugative plasmid transfer is limited by prophages but can be overcome by high conjugation rates

Antibiotic resistance spread via plasmids is a serious threat to successfully fight infections and makes understanding plasmid transfer in nature crucial to prevent the rise of antibiotic resistance. Studies addressing the dynamics of plasmid conjugation have yet neglected one omnipresent factor: prophages (viruses integrated into bacterial genomes), whose activation can kill host and surrounding bacterial cells. To investigate the impact of prophages on conjugation, we combined experiments and mathematical modelling. Using Escherichia coli, prophage λ and the multidrug-resistant plasmid RP4 we find that prophages can substantially limit the spread of conjugative plasmids. This inhibitory effect was strongly dependent on environmental conditions and bacterial genetic background. Our empirically parameterized model reproduced experimental dynamics of cells acquiring either the prophage or the plasmid well but could only reproduce the number of cells acquiring both elements by assuming complex interactions between conjugative plasmids and prophages in sequential infections. Varying phage and plasmid infection parameters over empirically realistic ranges revealed that plasmids can overcome the negative impact of prophages through high conjugation rates. Overall, the presence of prophages introduces an additional death rate for plasmid carriers, the magnitude of which is determined in non-trivial ways by the environment, the phage and the plasmid. This article is part of the theme issue 'The secret lives of microbial mobile genetic elements'.

Bacteriophage self-counting in the presence of viral replication

When host cells are in low abundance, temperate bacteriophages opt for dormant (lysogenic) infection. Phage lambda implements this strategy by increasing the frequency of lysogeny at higher multiplicity of infection (MOI). However, it remains unclear how the phage reliably counts infecting viral genomes even as their intracellular number increases because of replication. By combining theoretical modeling with single-cell measurements of viral copy number and gene expression, we find that instead of hindering lambda's decision, replication facilitates it. In a nonreplicating mutant, viral gene expression simply scales with MOI rather than diverging into lytic (virulent) and lysogenic trajectories. A similar pattern is followed during early infection by wild-type phage. However, later in the infection, the modulation of viral replication by the decision genes amplifies the initially modest gene expression differences into divergent trajectories. Replication thus ensures the optimal decision-lysis upon single-phage infection and lysogeny at higher MOI.

The landscape of lysogeny across microbial community density, diversity and energetics

Lysogens are common at high bacterial densities, an observation that contrasts with the prevailing view of lysogeny as a low-density refugium strategy. Here, we review the mechanisms regulating lysogeny in complex communities and show that the additive effects of coinfections, diversity and host energic status yield a bimodal distribution of lysogeny as a function of microbial densities. At high cell densities (above 10⁶  cells ml^-1 or g^-1 ) and low diversity, coinfections by two or more phages are frequent and excess energy availability stimulates inefficient metabolism. Both mechanisms favour phage integration and characterize the Piggyback-the-Winner dynamic. At low densities (below 10⁵  cells ml^-1 or g^-1 ), starvation represses lytic genes and extends the time window for lysogenic commitment, resulting in a higher frequency of coinfections that cause integration. This pattern follows the predictions of the refugium hypothesis. At intermediary densities (between 10⁵ and 10⁶  cells ml^-1 or g^-1 ), encounter rates and efficient energy metabolism favour lysis. This may involve Kill-the-Winner lytic dynamics and induction. Based on these three regimes, we propose a framework wherein phage integration occurs more frequently at both ends of the host density gradient, with distinct underlying molecular mechanisms (coinfections and host metabolism) dominating at each extreme.

From Bench to Keyboard and Back Again: A Brief History of Lambda Phage Modeling

Cellular decision making is the process whereby cells choose one developmental pathway from multiple possible ones, either spontaneously or due to environmental stimuli. Examples in various cell types suggest an almost inexhaustible plethora of underlying molecular mechanisms. In general, cellular decisions rely on the gene regulatory network, which integrates external signals to drive cell fate choice. The search for general principles of such a process benefits from appropriate biological model systems that reveal how and why certain gene regulatory mechanisms drive specific cellular decisions according to ecological context and evolutionary outcomes. In this article, we review the historical and ongoing development of the phage lambda lysis-lysogeny decision as a model system to investigate all aspects of cellular decision making. The unique generality, simplicity, and richness of phage lambda decision making render it a constant source ofmathematical modeling-aided inspiration across all of biology. We discuss the origins and progress of quantitative phage lambda modeling from the 1950s until today, as well as its possible future directions. We provide examples of how modeling enabled methods and theory development, leading to new biological insights by revealing gaps in the theory and pinpointing areas requiring further experimental investigation. Overall, we highlight the utility of theoretical approaches both as predictive tools, to forecast the outcome of novel experiments, and as explanatory tools, to elucidate the natural processes underlying experimental data.

Quantification of Lysogeny Caused by Phage Coinfections in Microbial Communities from Biophysical Principles

The association of temperate phages and bacterial hosts during lysogeny manipulates microbial dynamics from the oceans to the human gut. Lysogeny is well studied in laboratory models, but its environmental drivers remain unclear. Here, we quantified the probability of lysogenization caused by phage coinfections, a well-known trigger of lysogeny, in marine and gut microbial environments. Coinfections were quantified by developing a biophysical model that incorporated the traits of viral and bacterial communities. Lysogenization via coinfection was more frequent in highly productive environments like the gut, due to higher microbial densities and higher phage adsorption rates. At low cell densities, lysogenization occurred in bacteria with long duplication times. These results bridge the molecular understanding of lysogeny with the ecology of complex microbial communities.

Temperate phages can associate with their bacterial host to form a lysogen, often modifying the phenotype of the host. Lysogens are dominant in the microbially dense environment of the mammalian gut. This observation contrasts with the long-standing hypothesis of lysogeny being favored at low microbial densities, such as in oligotrophic marine environments. Here, we hypothesized that phage coinfections—a well-understood molecular mechanism of lysogenization—increase at high microbial abundances. To test this hypothesis, we developed a biophysical model of coinfection for marine and gut microbiomes. The model stochastically sampled ranges of phage and bacterial concentrations, adsorption rates, lysogenic commitment times, and community diversity from each environment. In 90% of the sampled marine communities, less than 10% of the bacteria were predicted to be lysogenized via coinfection. In contrast, 25% of the sampled gut communities displayed more than 25% of lysogenization. The probability of lysogenization in the gut was a consequence of the higher densities and higher adsorption rates. These results suggest that, on average, coinfections can form two trillion lysogens in the human gut every day. In marine microbiomes, which were characterized by lower densities and phage adsorption rates, lysogeny via coinfection was still possible for communities with long lysogenic commitment times. Our study indicates that different physical factors causing coinfections can reconcile the traditional view of lysogeny at poor host growth (long commitment times) and the recent Piggyback-the-Winner framework proposing that lysogeny is favored in rich environments (high densities and adsorption rates).

IMPORTANCE The association of temperate phages and bacterial hosts during lysogeny manipulates microbial dynamics from the oceans to the human gut. Lysogeny is well studied in laboratory models, but its environmental drivers remain unclear. Here, we quantified the probability of lysogenization caused by phage coinfections, a well-known trigger of lysogeny, in marine and gut microbial environments. Coinfections were quantified by developing a biophysical model that incorporated the traits of viral and bacterial communities. Lysogenization via coinfection was more frequent in highly productive environments like the gut, due to higher microbial densities and higher phage adsorption rates. At low cell densities, lysogenization occurred in bacteria with long duplication times. These results bridge the molecular understanding of lysogeny with the ecology of complex microbial communities.

Noise-driven cell differentiation and the emergence of spatiotemporal patterns

The emergence of phenotypic diversity in a population of cells and their arrangement in space and time is one of the most fascinating features of living systems. In fact, understanding multicellularity is unthinkable without explaining the proximate and the ultimate causes of cell differentiation in time and space. Simpler forms of cell differentiation can be found in unicellular organisms, such as bacterial biofilm, where reversible cell differentiation results in phenotypically diverse populations. In this manuscript, we attempt to start with the simple case of reversible nongenetic phenotypic to construct a model of differentiation and pattern formation. Our model, which we refer to as noise-driven differentiation (NDD) model, is an attempt to consider the prevalence of noise in biological systems, alongside what is known about genetic switches and signaling, to create a simple model which generates spatiotemporal patterns from bottom-up. Our simulations indicate that the presence of noise in cells can lead to reversible differentiation and the addition of signaling can create spatiotemporal pattern.

Cell Size-Based Decision-Making of a Viral Gene Circuit

Latently infected T cells able to reinitiate viral propagation throughout the body remain a major barrier to curing HIV. Distinguishing between latently infected cells and uninfected cells will advance efforts for viral eradication. HIV decision-making between latency and active replication is stochastic, and drug cocktails that increase bursts of viral gene expression enhance reactivation from latency. Here, we show that a larger host-cell size provides a natural cellular mechanism for enhancing burst size of viral expression and is necessary to destabilize the latent state and bias viral decision-making. Latently infected Jurkat and primary CD4+ T cells reactivate exclusively in larger activated cells, while smaller cells remain silent. In addition, reactivation is cell-cycle dependent and can be modulated with cell-cycle-arresting compounds. Cell size and cell-cycle dependent decision-making of viral circuits may guide stochastic design strategies and applications in synthetic biology and may provide important determinants to advance diagnostics and therapies.

Bohn-Wippert et al. investigate reactivation of T cells latently infected with HIV. They discover that only larger cells exit latency, while smaller cells remain silent. Viral expression bursts are cell size and cell-cycle dependent, presenting dynamic cell states, capable of active control, as sources of viral fate determination.

Optimality of the spontaneous prophage induction rate

Lysogens are bacterial cells that have survived after genomically incorporating the DNA of temperate bacteriophages infecting them. If an infection results in lysogeny, the lysogen continues to grow and divide normally, seemingly unaffected by the integrated viral genome known as a prophage. However, the prophage can still have an impact on the host's phenotype and overall fitness in certain environments. Additionally, the prophage within the lysogen can activate the lytic pathway via spontaneous prophage induction (SPI), killing the lysogen and releasing new progeny phages. These new phages can then lyse or lysogenize other susceptible nonlysogens, thereby impacting the competition between lysogens and nonlysogens. In a scenario with differing growth rates, it is not clear whether SPI would be beneficial or detrimental to the lysogens since it kills the host cell but also attacks nonlysogenic competitors, either lysing or lysogenizing them. Here we study the evolutionary dynamics of a mixture of lysogens and nonlysogens and derive general conditions on SPI rates for lysogens to displace nonlysogens. We show that there exists an optimal SPI rate for bacteriophage λ and explain why it is so low. We also investigate the impact of stochasticity and conclude that even at low cell numbers SPI can still provide an advantage to the lysogens. These results corroborate recent experimental studies showing that lower SPI rates are advantageous for phage-phage competition, and establish theoretical bounds on the SPI rate in terms of ecological and environmental variables associated with lysogens having a competitive advantage over their nonlysogenic counterparts.

Modeling cell population dynamics

 Quantitative modeling is quickly becoming an integral part of biology, due to the ability of mathematical models and computer simulations to generate insights and predict the behavior of living systems. Single-cell models can be incapable or misleading for inferring population dynamics, as they do not consider the interactions between cells via metabolites or physical contact, nor do they consider competition for limited resources such as nutrients or space. Here we examine methods that are commonly used to model and simulate cell populations. First, we cover simple models where analytic solutions are available, and then move on to more complex scenarios where computational methods are required. Overall, we present a summary of mathematical models used to describe cell population dynamics, which may aid future model development and highlights the importance of population modeling in biology.

Modeling cell population dynamics

 Quantitative modeling is quickly becoming an integral part of biology, due to the ability of mathematical models and computer simulations to generate insights and predict the behavior of living systems. Single-cell models can be incapable or misleading for inferring population dynamics, as they do not consider the interactions between cells via metabolites or physical contact, nor do they consider competition for limited resources such as nutrients or space. Here we examine methods that are commonly used to model and simulate cell populations. First, we cover simple models where analytic solutions are available, and then move on to more complex scenarios where computational methods are required. Overall, we present a summary of mathematical models used to describe cell population dynamics, which may aid future model development and highlights the importance of population modeling in biology.

The role of side tail fibers during the infection cycle of phage lambda

Bacteriophage λ has served as an important model for molecular biology and different cellular processes over the past few decades. In 1992, the phage strain used in most laboratories around the world, thought of as λ wild type, was discovered to carry a mutation in the stf gene which encodes four side tail fibers. Up to now, the role of the side tail fibers during the infection cycle, especially at the single-cell level, remains largely unknown. Here we utilized fluorescent reporter systems to characterize the effect of the side tail fibers on phage infection. We found that the side tail fibers interfere with phage DNA ejection process, most likely through the binding with their receptors, OmpC, leading to a more frequent failed infection. However, the side tail fibers do not seem to affect the lysis-lysogeny decision-making or lysis time.

High-resolution studies of lysis-lysogeny decision-making in bacteriophage lambda

Cellular decision-making guides complex development such as cell differentiation and disease progression. Much of our knowledge about decision-making is derived from simple models, such as bacteriophage lambda infection, in which lambda chooses between the vegetative lytic fate and the dormant lysogenic fate. This paradigmatic system is broadly understood but lacking mechanistic details, partly due to limited resolution of past studies. Here, we discuss how modern technologies have enabled high-resolution examination of lambda decision-making to provide new insights and exciting possibilities in studying this classical system. The advent of techniques for labeling specific DNA, RNA, and proteins in cells allows for molecular-level characterization of events in lambda development. These capabilities yield both new answers and new questions regarding how the isolated lambda genetic circuit acts, what biological events transpire among phages in their natural context, and how the synergy of simple phage macromolecules brings about complex behaviors.

The mobility of packaged phage genome controls ejection dynamics

The cell decision between lytic and lysogenic infection is strongly influenced by dynamics of DNA injection into a cell from a phage population, as phages compete for limited resources and progeny. However, what controls the timing of viral DNA ejection events was not understood. This in vitro study reveals that DNA ejection dynamics for phages can be synchronized (occurring within seconds) or desynchronized (displaying minutes-long delays in initiation) based on mobility of encapsidated DNA, which in turn is regulated by environmental factors, such as temperature and extra-cellular ionic conditions. This mechano-regulation of ejection dynamics is suggested to influence viral replication where the cell’s decision between lytic and latent infection is associated with synchronized or desynchronized delayed ejection events from phage population adsorbed to a cell. Our findings are of significant importance for understanding regulatory mechanisms of latency in phage and Herpesviruses, where encapsidated DNA undergoes a similar mechanical transition.

Viruses are tiny ‘parasites’ that smuggle their genetic material inside a cell and then hijack its resources for their own benefit. A viral infection can either be lytic or latent. In a lytic cycle, viruses make their host produce many copies of themselves, ultimately killing the cell. In contrast, during a latent infection, the viruses go ‘dormant’: for instance, some of them can insert their genetic material into the DNA of their host, which then gets passed on as the cell divides.

Certain viruses are capable of both lytic and latent infections. One example is the lambda phage, which targets Escherichia coli bacteria. In the first stage of infection, the genetic material ‘shoots out’ of the virus and gets injected inside the bacterium. The dynamics of the ejection process determine the type of infection that will follow. If multiple phages release their genomes quickly and within seconds of each other into the same cell, the bacterium tends to incorporate the viral DNA into its own genome, leading to a latent cycle. If the infections take place more slowly and not all at the same time, the cell is more likely to go through a lytic phase. However, the mechanism behind the different injection behaviors is still unknown; in particular, it is unclear which factors control the specificities of the ejection process in the first place.

Here, Alex Evilevitch demonstrates that the mechanical state of the phage DNA just before ejection dictates how the genetic material will then be injected in the bacteria. The experiments measured the stiffness of the DNA and the amount of heat given off during infection. Like fluid toothpaste, if the DNA is more liquid and flexible, it gets ejected quickly and simultaneously from several phages. Then, the genetic information of these viruses can be incorporated in the genome of the bacteria. On the other hand, if the DNA is more solid, it is likely to ‘stick’ and take time before it can be squeezed out: the injections become unsynchronised, which leads to a lytic phase.

Evilevitch then shows that the environment can influence the properties of the phages’ genome. A little more heat, or certain chemicals, can make the DNA more fluid inside the viruses, and change the way it can be injected inside the bacteria.

Many viruses that cause diseases in humans – from cold sores to glandular fever – can switch between the lytic and latent cycles. For the first time, these results show that the mechanical properties of the DNA inside a virus influence the ‘decision’ between the two types of infection. This knowledge could help us prevent infections from becoming lytic and ultimately allow us to control the spread of disease.

Coupling of DNA Replication and Negative Feedback Controls Gene Expression for Cell-Fate Decisions

Cellular decision-making arises from the expression of genes along a regulatory cascade, which leads to a choice between distinct phenotypic states. DNA dosage variations, often introduced by replication, can significantly affect gene expression to ultimately bias decision outcomes. The bacteriophage lambda system has long served as a paradigm for cell-fate determination, yet the effect of DNA replication remains largely unknown. Here, through single-cell studies and mathematical modeling we show that DNA replication drastically boosts cI expression to allow lysogenic commitment by providing more templates. Conversely, expression of CII, the upstream regulator of cI, is surprisingly robust to DNA replication due to the negative autoregulation of the Cro repressor. Our study exemplifies how living organisms can not only utilize DNA replication for gene expression control but also implement mechanisms such as negative feedback to allow the expression of certain genes to be robust to dosage changes resulting from DNA replication.