Biology subjects

Shemesh, E.

Publications and source records attributed to Shemesh, E..

4 recordsLinked to original sources

bioRxiv2025

Microbiota Dynamics in Lionfish (Pterois): Insights into Invasion and Establishment in the Mediterranean Sea

Lionfishes (Pterois spp.), originally native to the Indo-Pacific and Red Sea, have become one of the most invasive marine species globally, including the recent establishment in the Mediterranean Sea. This study investigates the microbiota of lionfish to explore its potential role in their invasion success and establishment. Using high-throughput sequencing and microbiota analyses, we characterized the species-specific core microbiome and identified habitat-specific markers across different regions (Red Sea, Mediterranean Sea, Caribbean, and aquarium populations) and organs. Focusing on the Mediterranean invasion, we tracked lionfish distribution and population dynamics along the Israeli coastline from 2017 to 2023, monitoring size, seasonal trends, and depth preferences. Our findings reveal that lionfish initially established themselves in deeper waters before expanding to shallower habitats, with a gradual increase in population size and body length over time. From a microbial aspect, we compared the microbiota of lionfish organs and identified a similar pattern (Photobacterium), to Earlier Lessepsian migrants fish species. This study provides novel insights into the interactions between microbiota and host ecology, shedding light on the mechanisms that may support the successful invasion. This study contributes to the understanding of lionfish invasion dynamics in the Mediterranean. It highlights the microbiota as an integral component for studying the ecological and biological mechanisms underpinning invasive species success and establishment of lionfish.

ecology↗

bioRxiv2022

Phenotyping technology for assessing protein content in seaweed by field spectroscopy and a machine learning algorithm

Determining seaweed protein concentration and the associated phenotype is critical for food industries that require precise tools to moderate concentration fluctuations and attenuate risks. Algal protein extraction and profiling have been widely investigated, but content determination involves a costly, time-consuming, and high-energy, laboratory-based fractionation technique. The present study examines the potential of field spectroscopy technology as a precise, high-throughput, non-destructive tool for on-site detection of red seaweed protein concentration. By using information from a large dataset of 144 Gracilaria sp. specimens, studied in a land-based cultivation set-up, under six treatment regimes during two cultivation seasons, and an artificial neural network, machine learning algorithm and diffuse visible-near infrared reflectance spectroscopy, predicted protein concentrations in the algae were obtained. The prediction results were highly accurate (R2 = 0.95; RMSE = 0.84), exhibiting a high correlation with the analytically determined values. External validation of the model derived from a separate trial, exhibited even better results (R2 = 0.99; RMSE = 0.45). This model, trained to convert phenotypic spectral measurements and pigment intensity into accurate protein content predictions, can be adapted to include diversified algae species and usages. HighlightNon-destructive determination of protein content in the edible red seaweed Gracilaria sp. by in-situ, VIS-NIR spectroscopy and a machine learning algorithm.

biochemistry↗

bioRxiv2021

The worm affair: Genetic diversity in two species of symbionts that co-occur in tubeworms from the Mediterranean Sea

The symbioses between the vestimentiferan tubeworms and their chemosynthetic partners (Gammaproteobacteria, Chromatiales, Sedimenticolaceae) hallmark the success of these organisms in hydrothermal vent and hydrocarbon seep deep-sea habitats. The fidelity of these associations varies, as both the hosts and the symbionts can be loose in partner choice. Some tubeworms may host distinct symbiont phylotypes, which often co-occur in a single host individual. To better understand the genetic basis for the promiscuity of tubeworm symbioses, we curated and investigated metagenome-assembled genomes of two symbiont phylotypes (species, based on the average nucleotide identity <95%) in Lamellibrachia anaximandri, a vestimentiferan endemic to the Mediterranean Sea, in individuals collected from Palinuro hydrothermal vents (Italy) and hydrocarbon seeps (Eratosthenes seamount and Palmahim disturbance). Using comparative genomics, we show that mainly mobilome and defense mechanism-related features distinguish the symbiont genotypes. While many central metabolic functions are conserved in the tubeworm symbionts, nitrate respiration (Nar, Nap and Nas proteins) is modular, yet this modularity is not linked to speciation, but rather to local adaptation. Our results hint that variation in a single moonlighting protein may be responsible for the host-symbiont fidelity.

microbiology↗

bioRxiv2020

Effect of different derivatization protocols on the calculation of trophic position using amino acids compound-specific stable isotopes

Amino acids compound-specific nitrogen stable isotope (AA-CSIA) is an emerging tool in ecology for understanding trophic system dynamics. While it has been successfully used for several independent studies across a range of environments and study locations, researchers have encountered calculation issues for determining trophic position values. Most studies introduce modifications to the constants of trophic position equation calculations, but then fail to account for the equation variations when comparing the results of separate research studies. The acceptance of this approach is related to the underlying presumption that no addition of the exogenous nitrogen atom occurs in the different methods and, therefore, such variations should not affect the outcome. In this paper, we evaluate the use of the EZfaast amino acid derivatization kit (chloroformate) and compare it to the isotopic results of two other derivatization methods. We highlight new considerations for working with AA-CSIA that might account for some of the variations in the results and lead researchers to modify constants in the equation. This likely requires developing the unique constants per derivatization method in order to be able to compare the trophic position results across different studies.

ecology↗