Biology subjects

Tal, O.

Publications and source records attributed to Tal, O..

8 recordsLinked to original sources

bioRxiv2024

Directional swimming patterns in jellyfish aggregations

Having a profound influence on marine and coastal environments worldwide, jellyfish hold significant scientific, economic, and public interest. The predictability of outbreaks and dispersion of jellyfish is limited by a fundamental gap in our understanding of their movement. Although there is evidence that jellyfish may actively affect their position, the role of active swimming in controlling jellyfish movement, and the characteristics of jellyfish swimming behavior, are not well understood. Consequently, jellyfish are often regarded as passively drifting or randomly moving organisms, both conceptually and in process studies. Here we show that the movement of jellyfish is controlled by distinctly directional swimming patterns, which are oriented against the direction of surface gravity waves. Taking a Lagrangian viewpoint from drone videos that allows the tracking of multiple adjacent jellyfish, and focusing the scyphozoan jellyfish Rhopilema nomadica as a model organism, we show that the behavior of individual jellyfish translates into a synchronized directional swimming of the aggregation as a whole. Numerical simulations show that this counter-wave swimming behavior results in biased correlated random-walk movement patterns that reduce the risk of stranding, thus providing jellyfish with an adaptive advantage critical to their survival. Our results emphasize the importance of active swimming in regulating jellyfish movement, and open the way for a more accurate representation in model studies, thus improving the predictability of jellyfish outbreaks and their dispersion, and contributing to our ability to mitigate their possible impact on coastal infrastructure and populations.

ecology↗

bioRxiv2023

A metabolic modeling-based framework for predicting trophic dependencies in native rhizobiomes of crop plants

The exchange of metabolites (i.e., metabolic interactions) between bacteria in the rhizosphere determines various plant-associated functions. Systematically understanding the metabolic interactions in the rhizosphere, as well as in other types of microbial communities, would open the door to the optimization of specific pre-defined functions of interest, and therefore to the harnessing of the functionality of various types of microbiomes. However, mechanistic knowledge regarding the gathering and interpretation of these interactions is limited. Here, we present a framework utilizing genomics and constraint based modeling approaches, aiming to interpret the hierarchical trophic interactions in the soil environment. 243 genome-scale metabolic models of bacteria associated with a specific disease suppressive vs disease conducive apple rhizospheres were drafted based on genome resolved metagenomes, comprising an in-silico native microbial community. Iteratively simulating microbial community members growth in a metabolomics-based apple root-like environment produced novel data on potential trophic successions, used to form a network of communal trophic dependencies. Network-based analyses have characterized interactions associated with beneficial vs non-beneficial microbiome functioning, pinpointing specific compounds and microbial species as potential disease supporting and suppressing agents. This framework provides a means for capturing trophic interactions and formulating a range of testable hypotheses regarding the metabolic capabilities of microbial communities within their natural environment. Essentially, it can be applied to different environments and biological landscapes, elucidating the conditions for the targeted manipulation of various microbiomes, and the execution of countless predefined functions.

microbiology↗

bioRxiv2022

Two independent loss-of-function mutations in anthocyanidin synthase homeologous genes make sweet basil all green

Sweet basil, Ocimum basilicum L., is an important culinary herb grown worldwide. Although basil is green, many landraces, breeding lines and exotic cultivars have purple stems and flowers. This anthocyanins pigmentation is unacceptable in the traditional Italian basil. We used the recently published sweet basil genome to map quantitative trait loci (QTL) for flower and stem color in a bi-parental F2 population. It was found that the pigmentation is governed by a single QTL, harboring an anthocyanidin synthase (ANS) gene. Further analysis revealed that the basil genome harbors two homeologous ANS genes, each carrying a loss-of-function mutation. ObANS1 carries a 1-bp insertion, and ObANS2 carries a missense mutation within the active site. In the purple-flower parent, ANS1 is functional and ANS2 carries a nonsense mutation. The functionality of the active allele was validated by complementation in an Arabidopsis ANS mutant. Moreover, we have restored the functionality of the missense-mutated ANS2 using site-directed activation. We found that the non-functional alleles were expressed to similar levels as the functional allele, suggesting polyploids invest futile effort in expressing non-functional genes, harming their superior redundancy. We show here we can harness basils genomics and genetics to understand the basic mechanism of metabolic traits.

plant biology↗

bioRxiv2021

Dual transcriptional analysis of Peronospora belbahrii and Ocimum basilicum in susceptible interactions

Basil downy mildew, caused by the pathogen Peronospora belbahrii, is a major problem for sweet basil growers worldwide. The genome sequences of both Ocimum basilicum and P. belbahrii were recently completed but extensive transcriptome analysis of this pathosystem has not been completed. RNA sequencing was performed using basil leaf samples collected three and six days after inoculation with sporangia from an Illinois isolate of P. belbahrii and differentially expressed genes were identified. Gene enrichment analysis identified 22 genes that were upregulated at day three, in comparison to mock inoculated leaf samples, that were classified as defense response to oomycetes; among this group were five orthologues of Arabidopsis thaliana DOWNY MILDEW RESISTANCE 6. During the same time interval, many genes contributing to photosynthesis in the infected leaves were downregulated in comparison to control leaf samples. Many more genes were differentially expressed in the inoculated basil leaves at day six, compared to mock inoculated leaves, as the pathogen began to produce sporangiophores. On days three and six, the pathogen produced high transcript levels of secreted glycoside hydrolases, which likely release sugars from the plant cell walls needed for the growth of the pathogen. These results contribute to a better understanding of the infection process of downy mildew and will aid the development of more effective measures for reducing the severity of the disease.

plant biology↗

bioRxiv2019

Adaptive Bet-Hedging Revisited: Considerations of Risk and Time Horizon

Models of adaptive bet-hedging commonly adopt insights from Kellys famous work on optimal gambling strategies and the financial value of information. In particular, such models seek evolutionary solutions that maximize long term average growth rate of lineages, even in the face of highly stochastic growth trajectories. Here, we argue for extensive departures from the standard approach to better account for evolutionary contingencies. Crucially, we incorporate considerations of volatility minimization, motivated by interim extinction risk in finite populations, within a finite time horizon approach to growth maximization. We find that a game-theoretic competitive-optimality approach best captures these additional constraints and derive the equilibria solutions under various fitness payoff functions.

evolutionary biology↗

bioRxiv2018

Divergent interactions maintain the quaternary octameric structure of a new family of esterases

Protein oligomerization contributes significantly to the stability and function of enzymes, and the interacting interfaces that create the oligomers are expected to be conserved. The acetyl-xylo-oligosaccharide esterase, Axe2, from the thermophilic bacterium Geobacillus stearothermophilus represents a new family of esterases belonging to the SGNH superfamily of hydrolytic enzymes, and has a unique doughnut-like homo-octameric configuration, composed of four homo-dimers. The dimers of Axe2 are held together mainly by clusters of hydrogen bonds involving Tyr184 and Arg192, as was demonstrated by site directed mutagenesis. Dimeric mutants obtained by single amino acid replacements were inactive towards 2-naphthyl acetate, indicating the necessity of the octameric assembly for catalysis. The crystal structure of two homologous proteins (PDB 3RJT and 5JD3) reveal the same tertiary fold and octameric ring structure as of Axe2. Surprisingly, these octameric structures appear to be maintained by different sets of amino acids involving Asn183 in 3RJT and His185 in 5JD3 instead of Tyr184 in Axe2. These findings prompt us to investigate five more homologues proteins, which were found to have similar octameric structures, despite significant changes in their key residues. We revealed a conserved quaternary structure, which is maintained via non-conserved interactions.

biochemistry↗

bioRxiv2018

Personal clinical history predicts antibiotic resistance in urinary tract infections

The prevalence of antibiotic resistance in urinary tract infections (UTIs) often renders the prescribed antimicrobial treatment ineffective, highlighting the need for personalized prediction of resistance at time of care. Here, crossing a 10-year longitudinal dataset of over 700,000 community-acquired UTIs with over 6,000,000 personally-linked records of antibiotic purchases, we show that the resistance profile of infections can be predicted based on patient-specific demographics and clinical history. Age, gender, and retirement home residence had strong, yet differential and even non-monotonic, associations with resistance to different antibiotics. Resistance profiles were also associated with the patients records of past urine samples and antibiotic usage, with these associations persisting for months and even longer than a year. Drug usage selected specifically for its own cognate resistance, which led indirectly, through genetic linkage, also to resistance to other, even mechanistically unrelated, drugs. Applying machine learning models, these association patterns allowed good personalized predictions of resistance, which could inform and better optimize empirical prescription of antibiotics.

epidemiology↗

bioRxiv2018

New perspectives on multilocus ancestry informativeness

We present an axiomatic approach for multilocus informativeness measures for determining the amount of information that a set of polymorphic genetic markers provides about individual ancestry. We then reveal several surprising properties of a decision-theoretic based measure that is consistent with the set of proposed criteria for multilocus informativeness. In particular, these properties highlight the interplay between information originating from population priors and the information extractable from the population genetic variants. This analysis then reveals a certain deficiency of mutual information based multilocus informativeness measures when such population priors are incorporated. Finally, we analyse and quantify the inevitable inherent decrease in informativeness due to learning from finite population samples.

genetics↗