Balance between asymmetric allocation and repair of somatic damage in unicellular life forms as an ancient form of r/K selection.

Over the course of multiple divisions, cells accumulate diverse nongenetic, somatic damage including misfolded and aggregated proteins and cell wall defects. If the rate of damage accumulation exceeds the rate of dilution through cell growth, a dedicated mitigation strategy is required to prevent eventual population collapse. Strategies for somatic damage control can be divided into two categories, asymmetric allocation and repair, which are not, in principle, mutually exclusive. We explore a mathematical model to identify the optimal strategy, maximizing the total cell number, over a wide range of environmental and physiological conditions. The optimal strategy is primarily determined by extrinsic, damage-independent mortality and the physiological model for damage accumulation that can be either independent (linear) or increasing (exponential) with respect to the prior accumulated damage. Under the linear regime, the optimal strategy is either exclusively repair or asymmetric allocation, whereas under the exponential regime, the optimal strategy is a combination of asymmetry and repair. Repair is preferred when extrinsic mortality is low, whereas at high extrinsic mortality, asymmetric damage allocation becomes the strategy of choice. We hypothesize that at an early stage of life evolution, optimization over repair and asymmetric allocation of somatic damage gave rise to r and K selection strategists.

In viral games, refs go to the replay.

After more than 2 years of intensive investigation, the direct ancestors of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain unidentified. Molecular epidemiology strongly supports a timeline marked by multiple, independent zoonoses in late 2019 (Pekar et al, 2022) solidifying the consensus hypothesis that close relatives of SARS-CoV-2 with high zoonotic potential were naturally circulating prior to the start of the pandemic (Andersen et al, 2020). Understanding where and when these ancestors acquired the genomic features that resulted in a virus with epidemic potential could enable the identification and mitigation of future pandemic viruses, even before the first human infection.

Human pathogenic RNA viruses establish noncompeting lineages by occupying independent niches.

Many pathogenic viruses are endemic among human populations and can cause a broad variety of diseases, some potentially leading to devastating pandemics. How virus populations maintain diversity and what selective pressures drive population turnover is not thoroughly understood. We conducted a large-scale phylodynamic analysis of 27 human pathogenic RNA viruses spanning diverse life history traits, in search of unifying trends that shape virus evolution. For most virus species, we identify multiple, cocirculating lineages with low turnover rates. These lineages appear to be largely noncompeting and likely occupy semiindependent epidemiological niches that are not regionally or seasonally defined. Typically, intralineage mutational signatures are similar to interlineage signatures. The principal exception are members of the family Picornaviridae, for which mutations in capsid protein genes are primarily lineage defining. Interlineage turnover is slower than expected under a neutral model, whereas intralineage turnover is faster than the neutral expectation, further supporting the existence of independent niches. The persistence of virus lineages appears to stem from limited outbreaks within small communities, so that only a small fraction of the global susceptible population is infected at any time. As disparate communities become increasingly connected through globalization, interaction and competition between lineages might increase as well, which could result in changing selective pressures and increased diversification and/or pathogenicity. Thus, in addition to zoonotic events, ongoing surveillance of familiar, endemic viruses appears to merit global attention with respect to the prevention or mitigation of future pandemics.

Molecular adaptations during viral epidemics.

In 1977, the world witnessed both the eradication of smallpox and the beginning of the modern age of genomics. Over the following half-century, 7 epidemic viruses of international concern galvanized virologists across the globe and led to increasingly extensive virus genome sequencing. These sequencing efforts exerted over periods of rapid adaptation of viruses to new hosts, in particular, humans provide insight into the molecular mechanisms underpinning virus evolution. Investment in virus genome sequencing was dramatically increased by the unprecedented support for phylogenomic analyses during the COVID-19 pandemic. In this review, we attempt to piece together comprehensive molecular histories of the adaptation of variola virus, HIV-1 M, SARS, H1N1-SIV, MERS, Ebola, Zika, and SARS-CoV-2 to the human host. Disruption of genes involved in virus-host interaction in animal hosts, recombination including genome segment reassortment, and adaptive mutations leading to amino acid replacements in virus proteins involved in host receptor binding and membrane fusion are identified as the key factors in the evolution of epidemic viruses.

Ongoing global and regional adaptive evolution of SARS-CoV-2.

Understanding the trends in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution is paramount to control the COVID-19 pandemic. We analyzed more than 300,000 high-quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the region of the nucleocapsid protein associated with nuclear localization signals (NLS) are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region-specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS-associated variants across multiple partitions rose to global prominence in March to July, during a period of stasis in terms of interregional diversity. Finally, beginning in July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.

CTRL - a label-free artificial intelligence method for dynamic measurement of single-cell volume.

Measuring the physical size of a cell is valuable in understanding cell growth control. Current single-cell volume measurement methods for mammalian cells are labor intensive, inflexible and can cause cell damage. We introduce CTRL: Cell Topography Reconstruction Learner, a label-free technique incorporating the deep learning algorithm and the fluorescence exclusion method for reconstructing cell topography and estimating mammalian cell volume from differential interference contrast (DIC) microscopy images alone. The method achieves quantitative accuracy, requires minimal sample preparation, and applies to a wide range of biological and experimental conditions. The method can be used to track single-cell volume dynamics over arbitrarily long time periods. For HT1080 fibrosarcoma cells, we observe that the cell size at division is positively correlated with the cell size at birth (sizer), and there is a noticeable reduction in cell size fluctuations at 25% completion of the cell cycle in HT1080 fibrosarcoma cells.

Cytoskeletal tension regulates mesodermal spatial organization and subsequent vascular fate.

Morphogenesis during human development relies on the interplay between physiochemical cues that are mediated in part by cellular density and cytoskeletal tension. Here, we interrogated these factors on vascular lineage specification during human-induced pluripotent stem-cell (hiPSC) fate decision. We found that independent of chemical cues, spatially presented physical cues induce the self-organization of Brachyury-positive mesodermal cells, in a RhoA/Rho-associated kinase (ROCK)-dependent manner. Using unbiased support vector machine (SVM) learning, we found that density alone is sufficient to predict mesodermal fate. Furthermore, the long-withstanding presentation of spatial confinement during hiPSC differentiation led to an organized vascular tissue, reminiscent of native blood vessels, a process dependent on cell density as found by SVM analysis. Collectively, these results show how tension and density relate to vascular identity mirroring early morphogenesis. We propose that such a system can be applied to study other aspects of the stem-cell niche and its role in embryonic patterning.

Ergodicity, hidden bias and the growth rate gain.

Many single-cell observables are highly heterogeneous. A part of this heterogeneity stems from age-related phenomena: the fact that there is a nonuniform distribution of cells with different ages. This has led to a renewed interest in analytic methodologies including use of the 'von Foerster equation' for predicting population growth and cell age distributions. Here we discuss how some of the most popular implementations of this machinery assume a strong condition on the ergodicity of the cell cycle duration ensemble. We show that one common definition for the term ergodicity, 'a single individual observed over many generations recapitulates the behavior of the entire ensemble' is implied by the other, 'the probability of observing any state is conserved across time and over all individuals' in an ensemble with a fixed number of individuals but that this is not true when the ensemble is growing. We further explore the impact of generational correlations between cell cycle durations on the population growth rate. Finally, we explore the 'growth rate gain'-the phenomenon that variations in the cell cycle duration leads to an improved population-level growth rate-in this context. We highlight that, fundamentally, this effect is due to asymmetric division.

The twisted tauopathies: surface interactions of helically patterned filaments seen in alzheimer's disease and elsewhere.

This paper broadly examines the dynamics of helically patterned filaments interacting with a surface and focuses on the surface interaction of amyloid fibrils formed by tau protein. Two structures are addressed in detail: cylindrical filaments with periodic thinning (CF-PT) and paired helical filaments (PHFs). PHFs are observed in neural tissue affected by Alzheimer's disease and may aggregate to form the pathological neurofibrillary tangles associated with the illness. Work using electron microscopy has demonstrated the conversion of CF-PT into PHFs in vitro, suggesting CF-PT to be a PHF precursor in vivo. Here we model CF-PT as a patterned elastic rod placed on a flat surface (characteristic of the environment during microscopy) and examine the conformational changes resulting in stable surface bonding. Analysis of this conformational space reveals structures resembling PHFs and thus provides a mechanistic explanation of the CF-PT to PHF transition. We develop a general phase diagram of the filament conformation as a function of filament twist and bend rigidity. Results of this work also suggest that we can obtain desired filament conformations by patterning interactions of elastic filaments with a substrate, and therefore can be used as a method in microfabrication.

Unicellular life balances asymmetric allocation and repair of somatic damage representing the origin of r/K selection.

Over the course of multiple divisions, cells accumulate diverse non-genetic, somatic damage including misfolded and aggregated proteins and cell wall defects. If the rate of damage accumulation exceeds the rate of dilution through cell growth, a dedicated mitigation strategy is required to prevent eventual population collapse. Strategies for somatic damage control can be divided into two categories, asymmetric allocation and repair, which are not, in principle, mutually exclusive. Through mathematical modelling, we identify the optimal strategy, maximizing the total cell number, over a wide range of environmental and physiological conditions. The optimal strategy is primarily determined by extrinsic (damage-independent) mortality and the physiological model for damage accumulation that can be either independent (linear) or increasing (exponential) with respect to the prior accumulated damage. Under the linear regime, the optimal strategy is either exclusively repair or asymmetric allocation whereas under the exponential regime, the optimal strategy is mixed. Repair is preferred when extrinsic mortality is low, whereas at high extrinsic mortality, asymmetric damage allocation becomes the strategy of choice. We hypothesize that optimization over somatic damage repair and asymmetric allocation in early cellular life forms gave rise to the r and K selection strategies.

Epistasis at the SARS-CoV-2 Receptor-Binding Domain Interface and the Propitiously Boring Implications for Vaccine Escape.

At the time of this writing, December 2021, potential emergence of vaccine escape variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a grave global concern. The interface between the receptor-binding domain (RBD) of SARS-CoV-2 spike (S) protein and the host receptor (ACE2) overlaps the binding site of principal neutralizing antibodies (NAb), limiting the repertoire of viable mutations. Nonetheless, variants with multiple RBD mutations have risen to dominance. Nonadditive, epistatic relationships among RBD mutations are apparent, and assessing the impact of such epistasis on the mutational landscape, particularly the risk of vaccine escape, is crucial. We employed protein structure modeling using Rosetta to compare the effects of all single mutants at the RBD-NAb and RBD-ACE2 interfaces for the wild type and Delta, Gamma, and Omicron variants. Overall, epistasis at the RBD interface appears to be limited, and the effects of most multiple mutations are additive. Epistasis at the Delta variant interface weakly stabilizes NAb interaction relative to ACE2 interaction, whereas in Gamma, epistasis more substantially destabilizes NAb interaction. Despite bearing many more RBD mutations, the epistatic landscape of Omicron closely resembles that of Gamma. Thus, although Omicron poses new risks not observed with Delta, structural constraints on the RBD appear to hamper continued evolution toward more complete vaccine escape. The modest ensemble of mutations relative to the wild type that are currently known to reduce vaccine efficacy is likely to contain the majority of all possible escape mutations for future variants, predicting the continued efficacy of the existing vaccines. IMPORTANCE Emergence of vaccine escape variants of SARS-CoV-2 is arguably the most pressing problem during the COVID-19 pandemic as vaccines are distributed worldwide. We employed a computational approach to assess the risk of antibody escape resulting from mutations in the receptor-binding domain of the spike protein of the wild-type SARS-CoV-2 virus as well as the Delta, Gamma, and Omicron variants. The efficacy of the existing vaccines against Omicron could be substantially reduced relative to the wild type, and the potential for vaccine escape is of grave concern. Our results suggest that although Omicron poses new evolutionary risks not observed for Delta, structural constraints on the RBD make continued evolution toward more complete vaccine escape from either Delta or Omicron unlikely. The modest set of escape-enhancing mutations already identified for the wild type likely include the majority of all possible mutations with this effect.

Clinical SARS-CoV-2 Kinetic Profiles Are Dependent on the Viral Strain and Host Vaccination Status.

The SARS-CoV-2 infection kinetics in a real-world, clinical setting represent a knowledge gap in understanding the underlying COVID-19 pathogenesis. There are scant reports on the dynamics describing the two principal components of the viral life cycle, namely the rapid proliferation and slower clearance phases. Here, we present results from an ongoing workplace clinical surveillance study where two vaccinated participants became infected with SARS-CoV-2 Omicron variant (BA.1. lineage). The subjects were followed longitudinally at high temporal resolution allowing the kinetics of both viral phases to be characterized. The viral doubling times in the proliferation phase (3.3-3.5 h) and maximum measured viral loads were similar to those observed for unvaccinated individuals infected with an earlier SARS-CoV-2 strain. However, the clearance phase was much shorter in the current study and unexpectedly displayed a multimodal profile. Longitudinal whole genome SARS-CoV-2 sequencing identified a stable mutation that arose in one of the participants over the 2-week period of positivity. Our small study provides a rare insight into the clinical SARS-CoV-2 dynamics holding significance to public health measures and the biology underlying COVID-19.

Clinical SARS-CoV-2 Kinetic Profiles Are Dependent on the Viral Strain and Host Vaccination Status.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection kinetics in a real-world, clinical setting represent a knowledge gap in understanding the underlying coronavirus disease 2019 (COVID-19) pathogenesis. There are scant reports of the dynamics describing the two principal components of the viral life cycle, namely, the rapid proliferation and slower clearance phases. Here, we present results from an ongoing workplace clinical surveillance study during which two vaccinated participants became infected with SARS-CoV-2 Omicron variant (BA.1. lineage). The subjects were followed longitudinally with high temporal resolution, allowing the kinetics of both viral phases to be characterized. The viral doubling times in the proliferation phase (3.3 to 3.5 h) and maximum measured viral loads were similar to those observed for unvaccinated individuals infected with an earlier SARS-CoV-2 strain. However, the clearance phase was much shorter in the current study and unexpectedly displayed a multimodal profile. Longitudinal whole-genome SARS-CoV-2 sequencing identified a stable mutation that arose in one of the participants over the 2-week period of positivity. Our small study provides rare insight into the clinical SARS-CoV-2 dynamics, with significance for public health measures and the biology underlying COVID-19. IMPORTANCE We are conducting an ongoing SARS-CoV-2 workplace clinical study based on frequent, longitudinal disease surveillance of staff and household members. Here, we investigated the viral dynamics in two recently vaccinated participants who became infected with the same Omicron variant of SARS-CoV-2. Because the subjects were enrolled in our study, we were able to track the entire viral life cycle with high temporal resolution, with samples collected every 12 h. Surprisingly, the short viral proliferation phase and maximum viral loads in nasal swab samples were similar to our previous observations with unvaccinated participants and an earlier viral strain. However, the decay phase, indicative of viral clearance, was much shorter here. Our results provide a rare, real-world glimpse of the clinical SARS-CoV-2 replication kinetics, potentially impacting immediate therapies and awareness of earlier and greater transmission potential.

Host age structure reshapes parasite symbiosis: collaboration begets pathogens, competition begets virulent mutualists.

BACKGROUND: Symbiotic relationships are ubiquitous in the biosphere. Inter-species symbiosis is impacted by intra-specific distinctions, in particular, those defined by the age structure of a population. Older individuals compete with younger individuals for resources despite being less likely to reproduce, diminishing the fitness of the population. Conversely, however, older individuals can support the reproduction of younger individuals, increasing the population fitness. Parasitic relationships are commonly age structured, typically, more adversely affecting older hosts. RESULTS: We employ mathematical modeling to explore the differential effects of collaborative or competitive host age structures on host-parasite relationships. A classical epidemiological compartment model is constructed with three disease states: susceptible, infected, and recovered. Each of these three states is partitioned into two compartments representing young, potentially reproductive, and old, post-reproductive, hosts, yielding 6 compartments in total. In order to describe competition and collaboration between old and young compartments, we model the reproductive success to depend on the fraction of young individuals in the population. Collaborative populations with relatively greater numbers of post-reproductive hosts enjoy greater reproductive success whereas in purely competitive populations, increasing the post-reproductive subpopulation reduces reproductive success. CONCLUSIONS: We demonstrate that, in collaborative host populations, pathogens strictly impacting older, post-reproductive individuals can reduce population fitness even more than pathogens that directly impact younger, potentially reproductive individuals. In purely competitive populations, the reverse is observed, and we demonstrate that endemic, virulent pathogens can oxymoronically form a mutualistic relationship with the host, increasing the fitness of the host population. Applications to endangered species conservation and invasive species containment are discussed.

Evolution of human respiratory virus epidemics.

Background: Pathogens are often assumed to evolve towards reduced virulence, but counterexamples abound. Faced with a new pathogen, such as SARS-CoV-2, it is crucial to be able to forecast the case fatality rate (CFR) and the overall disease burden. Considerable effort has been invested towards developing a mathematical framework for predicting virulence evolution. Although many approaches accurately recapitulate complex outcomes, most rely on an assumed trade-off between CFR and infection rate. It is often impractical to empirically validate this constraint for human pathogens. Methods: A compartment model with parameters tuning the degree to which symptomatic individuals are isolated and the duration of immunity is constructed and evaluated at both short timescales and at equilibrium. Results: We reveal kinetic constraints whereby variation of multiple parameters in concert leads to decreased CFR and increased pathogen fitness, whereas independent variation of the parameters decreases pathogen fitness. Smallpox, SARS-CoV-2, and influenza are analyzed as diverse representatives of human respiratory viruses. We show that highly virulent viruses, such as smallpox, are often constrained by the host behavior, whereas moderately virulent viruses, such as SARS-CoV-2, appear to be typically constrained by the relationship between the duration of immunity and CFR. Conclusions: Evolution of human respiratory epidemics appears to be often kinetically constrained and a reduction in CFR should not be assumed. These results agree with previous work demonstrating an increase in virulence for smallpox and further predict that SARS-CoV-2 is likely to continue presenting a substantial disease burden. Herd immunity against SARS-CoV-2 and viruses with similar life history traits might be unachievable without vaccination. However, partial isolation of symptomatic individuals can have a major effect on the epidemic dynamics not only by reducing the number of fatalities in the short term but also by changing the evolutionary trajectory of moderate CFR viruses towards reduced CFR.

Substantial impact of post-vaccination contacts on cumulative infections during viral epidemics.

Background: The start of 2021 was marked by the initiation of a global vaccination campaign against the novel coronavirus SARS-CoV-2. Formulating an optimal distribution strategy under social and economic constraints is challenging. Optimal distribution is additionally constrained by the potential emergence of vaccine resistance. Analogous to chronic low-dose antibiotic exposure, recently inoculated individuals who are not yet immune play an outsized role in the emergence of resistance. Classical epidemiological modelling is well suited to explore how the behavior of the inoculated population impacts the total number of infections over the entirety of an epidemic. Methods: A deterministic model of epidemic evolution is analyzed, with seven compartments defined by their relationship to the emergence of vaccine-resistant mutants and representing three susceptible populations, three infected populations, and one recovered population. This minimally computationally intensive design enables simulation of epidemics across a broad parameter space. The results are used to identify conditions minimizing the cumulative number of infections. Results: When an escape variant is only modestly less infectious than the originating strain within a naïve population, there exists an optimal rate of vaccine distribution. Exceeding this rate increases the cumulative number of infections due to vaccine escape. Analysis of the model also demonstrates that inoculated individuals play a major role in the mitigation or exacerbation of vaccine-resistant outbreaks. Modulating the rate of host-host contact for the inoculated population by less than an order of magnitude can alter the cumulative number of infections by more than 20%. Conclusions: Mathematical modeling shows that optimization of the vaccination rate and limiting post-vaccination contacts can perceptibly affect the course of an epidemic. The consideration of limitations on post-vaccination contacts remains relevant for the entire duration of any vaccination campaign including the current status of SARS-CoV-2 vaccination.

Ongoing Global and Regional Adaptive Evolution of SARS-CoV-2.

Understanding the trends in SARS-CoV-2 evolution is paramount to control the COVID-19 pandemic. We analyzed more than 300,000 high quality genome sequences of SARS-CoV-2 variants available as of January 2021. The results show that the ongoing evolution of SARS-CoV-2 during the pandemic is characterized primarily by purifying selection, but a small set of sites appear to evolve under positive selection. The receptor-binding domain of the spike protein and the nuclear localization signal (NLS) associated region of the nucleocapsid protein are enriched with positively selected amino acid replacements. These replacements form a strongly connected network of apparent epistatic interactions and are signatures of major partitions in the SARS-CoV-2 phylogeny. Virus diversity within each geographic region has been steadily growing for the entirety of the pandemic, but analysis of the phylogenetic distances between pairs of regions reveals four distinct periods based on global partitioning of the tree and the emergence of key mutations. The initial period of rapid diversification into region-specific phylogenies that ended in February 2020 was followed by a major extinction event and global homogenization concomitant with the spread of D614G in the spike protein, ending in March 2020. The NLS associated variants across multiple partitions rose to global prominence in March-July, during a period of stasis in terms of inter-regional diversity. Finally, beginning July 2020, multiple mutations, some of which have since been demonstrated to enable antibody evasion, began to emerge associated with ongoing regional diversification, which might be indicative of speciation.