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Schreiber, S.

Publications and source records attributed to Schreiber, S..

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A chemical biology view of bioactive small molecules and a binder-based approach to connect biology to precision medicines

Introduction Introduction Conclusion References A simplistic view of drug discovery is that it begins, most often using \"model organisms\", with biological inferences of a disease that suggest the need to interfere with some activity, function or process. An enzyme should be inhibited or a pathogen should be killed. Chemical experimentation yields the desired inhibitor, and clinical investigations then test the underlying hypothesis in humans. If the stars align, an effective drug emerges.\n\nThe high cost of testing and low rate of success of this paradigm has led the drug-discovery enterprise to search for new and more effective approaches. In this essay, I explore a concept that focuses on the discovery of compounds that bind targets rather than inhibit a biochemical activity. I present evidence that such binders can affect protein activity in under-app ...

biochemistry

Neolithic and Medieval virus genomes reveal complex evolution of Hepatitis B

The hepatitis B virus (HBV) is one of the most widespread human pathogens known today, yet its origin and evolutionary history are still unclear and controversial. Here, we report the analysis of three ancient HBV genomes recovered from human skeletons found at three different archaeological sites in Germany. We reconstructed two Neolithic and one medieval HBV genomes by de novo assembly from shotgun DNA sequencing data. Additionally, we observed HBV-specific peptides using paleo-proteomics. Our results show that HBV circulates in the European population for at least 7000 years. The Neolithic HBV genomes show a high genomic similarity to each other. In a phylogenetic network, they do not group with any human-associated HBV genome and are most closely related to those infecting African non-human primates. These ancient virus forms appear to represent distinct lineages that have no close relatives today and went possibly extinct. Our results reveal the great potential of ancient DNA from human skeletons in order to study the long-time evolution of blood borne viruses.

evolutionary biology

Does deterministic coexistence theory matter in a finite world? Insights from serpentine annual plants

Contemporary studies of species coexistence are underpinned by deterministic models that assume that competing species have continuous (i.e. non-integer) densities, live in infinitely large landscapes, and coexist over infinite time horizons. By contrast, in nature species are composed of discrete individuals subject to demographic stochasticity, and occur in habitats of finite size where extinctions occur in finite time. One consequence of these discrepancies is that metrics of species coexistence derived from deterministic theory may be unreliable predictors of the duration of species coexistence in nature. These coexistence metrics include invasion growth rates and niche and fitness differences, which are now commonly applied in theoretical and empirical studies of species coexistence. Here we test the efficacy of deterministic coexistence metrics on the duration of species coexistence in a finite world. We introduce new theoretical and computational methods to estimate coexistence times in stochastic counterparts of classic deterministic models of competition. Importantly, we parameterized this model using experimental field data for 90 pairwise combinations of 18 species of annual plants, allowing us to derive biologically-informed estimates of coexistence times for a natural system. Strikingly, we find that for species expected to deterministically coexist, habitat sizes containing only tens of individuals have predicted coexistence times of greater than 1, 000 years. We also find that invasion growth rates explain 60% of the variation in intrinsic coexistence times, reinforcing their general usefulness in studies of coexistence. However, only by integrating information on both invasion growth rates and species equilibrium population sizes could most (> 99%) of the variation in species coexistence times be explained. This integration is achieved with demographically uncoupled single species models solely determined by the invasion growth rates and equilibrium population sizes. Moreover, because of a complex relationship between niche overlap/fitness differences and equilibrium population sizes, increasing niche overlap and increasing fitness differences did not always result in decreasing coexistence times as deterministic theory would predict. Nevertheless, our results tend to support the informed use of deterministic theory for understanding the duration of species coexistence, while highlighting the need to incorporate information on species equilibrium population sizes in addition to invasion growth rates.

ecology

Predicting Evolutionarily Stable Strategies from Functional Trade-offs of Sonoran Desert Annuals

For many decades, researchers have studied how plants use bet-hedging strategies to insure against unpredictable, unfavorable conditions. We improve upon earlier analyses by explicitly accounting for how variable precipitation affects annual plant species bet-hedging strategies. We consider how the survival rates of dormant seeds (in a seed bank) interact with precipitation responses to influence optimal germination strategies. Specifically, we incorporate how response to resource availability (i.e. the amount of offspring (seeds) generated per plant in response to variation in desert rainfall) influences the evolution of germination fractions. Using data from 10 Sonoran Desert annual plants, we develop models that explicitly include these responses to model fitness as a function of precipitation. For each of the species, we identify the predicted evolutionarily stable strategies (ESS) for the fraction of seeds germinating each year and then compare our estimated ESS values to the observed germination fractions. We also explore the relative importance of seed survival and precipitation responses in shaping germination strategies by regressing ESS values and observed germination fractions against these traits. We find that germination fractions are lower for species with higher seed survival, with lower reproductive success in dry years, and with better yield responses in wet years. These results illuminate the evolution of bethedging strategies in an iconic system, and provide a framework for predicting how current and future environmental conditions may reshape those strategies.

ecology

Topography and refractometry of sperm cells using SLIM

Characterization of spermatozoon viability is a common test in treating infertility. Recently, it has been shown that label-free, phase-sensitive imaging can provide a valuable alternative for this type of assay. Here, we employ spatial light interference microscopy (SLIM) to decouple the thickness and refractive index information of individual cells. This procedure was enabled by quantitative phase imaging cells on media of two different refractive indices and using a numerical tool to remove the curvature from the cell tails. This way, we achieved ensemble averaging of topography and refractometry of 100 cells in each of the two groups. The results show that the thickness profile of the cell tail goes down to 150 nm and the refractive index can reach values of 1.6 close to the head.

cell biology

Identifying Crohns disease signal from variome analysis

BackgroundAfter many years of concentrated research efforts, the exact cause of Crohns disease remains unknown. Its accurate diagnosis, however, helps in management and even preventing the onset of disease. Genome-wide association studies have identified 140 loci associated with CD, but these carry very small log odds ratios and are uninformative for diagnoses.\n\nResultsHere we describe a machine learning method - AVA,Dx (Analysis of Variation for Association with Disease) - that uses whole exome sequencing data to make predictions of CD status. Using the person-specific variation in these genes from a panel of only 111 individuals, we built disease-prediction models informative of previously undiscovered disease genes. In this panel, our models differentiate CD patients from healthy controls with 71% precision and 73% recall at the default cutoff. By additionally accounting for batch effects, we are also able to predict individual CD status for previously unseen individuals from a separate CD study (84% precision, 73% recall).\n\nConclusionsLarger training panels and additional features, including regulatory variants and environmental factors, e.g. human-associated microbiota, are expected to improve model performance. However, current results already position AVA,Dx as both an effective method for highlighting pathogenesis pathways and as a simple Crohns disease risk analysis tool, which can improve clinical diagnostic time and accuracy.

bioinformatics

The structured demography of open populations in fluctuating environments

At the spatial scale relevant to many field studies and management policies, populations may experience more external recruitment than internal recruitment. These sources of recruitment, as well as local demography, are often subject to stochastic fluctuations in environmental conditions. Here, we introduce a class of stochastic models accounting for these complexities and provide analytic methods for understanding their long-term behavior. The population state n(x) of these stochastic models is a function or vector keeping track of densities of individuals with continuous (e.g. size) or discrete (e.g. age) traits x taking values in a compact metric space. This state variable is updated by a stochastic affine equation nt+1 = At+1nt + bt+1 where At+1 is a time varying operator (e.g. an integral operator or a matrix) that updates the local demography, and bt+1 is a time varying function or vector representing external recruitment. When the realized per-capita growth rate of the local demography is negative, we show that all initial conditions converge to the same time-varying trajectory. Furthermore, when A1, A2... and b1, b2, ... are stationary sequences, this limiting behavior is determined by a unique stationary distribution. When the stationary sequences are periodic, uncorrelated, or a mixture of these two types of stationarity, we derive explicit formulas for the mean, within-year covariance, and auto-covariance of the stationary distribution. Sensitivity formulas for these statistical features are also given. The analtyic methods are illustrated with applications to discrete size-structured models of space-limited coral populations, and continuously size-structured models of giant clam populations.

ecology

When rarity has costs: coexistence under positive frequency-dependence and environmental stochasticity

Stable coexistence relies on negative frequency-dependence, in which rarer species invading a patch benefit from a lack of conspecific competition experienced by residents. In nature, however, rarity can have costs, resulting in positive frequency-dependence (PFD) particularly when species are rare. Many processes can cause positive frequency-dependence, including a lack of mates, mutualist interactions, and reproductive interference from heterospecifics. When species become rare in the community, positive frequency-dependence creates vulnerability to extinction, if frequencies drop below certain thresholds. For example, environmental fluctuations can drive species to low frequencies where they are then vulnerable to PFD. Here, we analyze deterministic and stochastic mathematical models of two species interacting through both PFD and resource competition in a Chessonian framework. Reproductive success of individuals in these models is reduced by a product of two terms: the reduction in fecundity due to PFD, and the reduction in fecundity due to competition. Consistent with classical coexistence theory, the effect of competition on individual reproductive success exhibits negative frequency-dependence when individuals experience greater intraspecific competition than interspecific competition i.e., niche overlap is less than one. In the absence of environmental fluctuations, our analysis reveals that (1) a synergistic effect of PFD and niche overlap that hastens exclusion, (2) trade-offs between susceptibility to PFD and maximal fecundity can mediate coexistence, and (3) coexistence, when it occurs, requires that neither species is initially rare. Analysis of the stochastic model highlights that environmental fluctuations, unless perfectly correlated, coupled with PFD ultimately drive one species extinct. Over any given time frame, this extinction risk decreases with the correlation of the demographic responses of the two species to the environmental fluctuations, and increases with the temporal autocorrelation of these fluctuations. For species with overlapping generations, these trends in extinction risk persist despite the strength of the storage effect decreasing with correlated demographic responses and increasing with temporal autocorrelations. These results highlight how the presence of PFD may alter the outcomes predicted by modern coexistence mechanisms.

ecology