Biology subjects

Liberzon, A.

Publications and source records attributed to Liberzon, A..

10 recordsLinked to original sources

bioRxiv2023

Production of single-cell-protein (SCP)/poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) matrices through fermentation of archaea Haloferax mediterranei

The idea of in-situ integrating poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) sieves in a single-cell protein (SCP) represents a promising approach to enhance the properties of microbial biomass as protein alternatives. Archaea SCP/PHBV matrix was successfully produced with a concentration of 8.0 {+/-} 0.1 g L-1 and a productivity of 11.1 mg L-1 h-1 using Haloferax mediterranei. This was achieved by employing 30 g L-1 of enzymatically hydrolyzed bread waste (BW) and 200 g L-1 of red sea salt at 42 {degrees}C and with shaking at 150 rpm for 3 days. The amino acid profile of the SCP/PHBV matrix revealed a total amino acid content of 358 g kg-1, including 147 g kg-1 of essential amino acids. The protein quality of the H. mediterranei SCP/PHBV matrix was assessed using the in-vitro enzyme digestion method, indicating a high-quality protein with an in-vitro digestibility value of 0.91 and a protein digestibility-corrected amino acid score (PDCAAS) of 0.78. The PHBV component (36.0 {+/-} 6.3% w/w) in the SCP/PHBV matrix consisted of a copolymer of 3-hydroxybutyrate and 3- hydroxyvalerate in a 91:9 mol% ratio, respectively. The simultaneous production of PHBV polymeric sieves within the H. mediterranei SCP/PHBV matrix provides an alternative protein source with enhanced physicochemical and thermal properties. HighlightsO_LISCP/PHBV matrices were produced from wasted bread by archaea H. mediterranei. C_LIO_LIThis is the first report that explored the production and properties of SCP/PHBV. C_LIO_LIThe presence of PHBV in SCP affected its physicochemical and thermal properties. C_LIO_LISCP/PHBV with high-quality protein was achieved with a PDCAAS value of 0.78. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/571855v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@773447org.highwire.dtl.DTLVardef@94a96org.highwire.dtl.DTLVardef@1ffdfb8org.highwire.dtl.DTLVardef@1b8e27a_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2023

Cultivation of Ulva sp. offshore the Eastern Mediterranean Sea in experimental bioreactors: seasonal growth dynamics and environmental effects

Offshore macroalgae production could provide an alternative source of biomass for food, materials and energy. However, the offshore environment in general, and specifically the Eastern Mediterranean Sea (EMS) offshore, is a high energy and low nutrients environment and thus is challenging for macroalgae farming. This study aims to understand the effects of season, depth, and fertilization duration on growth rates and chemical composition in offshore Ulva biomass production and develop a predictive model suitable to offshore conditions. We hypothesize that offshore Ulva growth rates and chemical composition will follow a seasonal trend and that applying rapid onshore fertilization could refill nutrient storages and enable continuous offshore cultivation. We test this hypothesis by measuring Ulva biomass and internal nitrogen in offshore experiments in the nitrogen-poor EMS a few kilometers offshore the Israeli coast. We construct a predictive cultivation model to estimate N concentrations in the sea during experiments. This study demonstrates the feasibility of growing Ulva sp. offshore the EMS with an onshore nutrient supply and develops a better understanding of seasonal growth dynamics and environmental effects (nitrogen, waves, depth, etc.). Furthermore, the study showcases the applicability of the macroalgae cultivation model in the offshore environment and its potential contribution throughout the whole lifecycle of seaweed cultivation.

bioengineering↗

bioRxiv2023

Modeling of growth of Ulva sp. macroalgae in a controlled photobioreactor based on nitrogen accumulation dynamics

Macroalgae biomass production models that capture nutrient dynamics, temperature, light, and salinity are important for the design and operation of large-scale farms. The goal of this study is to understand how the nitrogen fertilizing regime, relating to fertilizing dose (M N week-1), amplitude (M N), and duration (hours), affects the dynamics of nitrogen content and biomass production of the Ulva sp. macroalgae. We hypothesize that the nitrogen fertilizing regime controls the Ulva Nitrogen Use Efficiency (NUE), defined here as the fraction of fertilizer nitrogen that is utilized and allocated to yield N, and, accordingly, also nitrogen assimilation in the biomass and the growth rate. We test this hypothesis by measuring internal nitrogen and biomass weight and by calculating NUE under various fertilization regimes in controlled photobioreactors. Based on this experimental data, we developed a biomass productivity model that predicts nitrogen and biomass dynamics in time over three weeks of cultivation. This study points out efficient fertilizing regimes and enables the development of a comprehensive understanding of the dynamic relationship between external N, internal N, and biomass production of the Ulva sp. macroalgae under varying external N levels, which is important for real-world agricultural applications. This study provides a better understanding of the external N-internal N-biomass triangle followed by an improved dynamic cultivation model, enabling better control of nutrient application and biomass production in macroalgae farming for a sustainable marine bioeconomy.

bioengineering↗

bioRxiv2021

Males perceive honest information from female released sex pheromone in a moth

There is accumulating evidence that male insects advertise their quality to conspecific females through pheromones. However, most studies of female released sex pheromone assume information transfer regarding merely the species of the female and her mating status. We show that more and precise information is conveyed through the female sex pheromone, positioning it as an honest sexual trait. We demonstrate that females in bad physical conditions (small, starved or old) lay significantly fewer eggs than females in good conditions (large, fed or young). The ratio of the sex pheromone blend in gland extracts of female pink bollworm moths accurately describes the female phenotypic condition whereas the pheromone amount in the glands fails to provide an honest signal of quality. Moreover, males use the female released pheromone blend to choose their mates and approach females that signal higher reproductive potential. In addition, surrogating the female effect, using synthetic pheromone blend that represents that of higher quality females (0.6:0.4 ZZ:ZE) more males were attracted to this blend than to the blend representing the population mean (0.5:0.5 ZZ:ZE). Both, female advertisement for males and the male choosiness, suggest that pheromones have evolved as sexual traits under directional, sexual selection.

evolutionary biology↗

bioRxiv2020

Multi-Scale Modeling of Intensive Macroalgae Cultivation and Marine Nitrogen Sequestration

Multi-scale macroalgae growth models are required for the efficient design of sustainable, economically viable and environmentally safe farms. Here, we develop a multi-scale model for Ulva sp. macroalgae growth and nitrogen sequestration in an intensive cultivation farm, regulated by temperature, light and nutrients. The model incorporates a range of scales by incorporating spatial effects in two steps: light extinction at the reactor scale (1 m) and nutrient absorption at the farm scale (1 km). The model was validated on real data from an experimental reactor installed in the sea. Biomass production rates, chemical compositions and nitrogen removal were simulated under different seasons, levels of dilution in the environment and water-exchange rate in the reactor. This multi-scale model provides an important tool for environmental authorities and seaweed farmers who desire to upscale to large bioremediation and/or macroalgae biomass production farms, thus promoting the marine sustainable development and the macroalgae-based bioeconomy.

bioengineering↗

bioRxiv2019

Quality Matters: Biocuration Experts on the Impact of Duplication and Other Data Quality Issues in Biological Databases

The volume of biological database records is growing rapidly, populated by complex records drawn from heterogeneous sources. A specific challenge is duplication, that is, the presence of redundancy (records with high similarity) or inconsistency (dissimilar records that correspond to the same entity). The characteristics (which records are duplicates), impact (why duplicates are significant), and solutions (how to address duplication), are not well understood. Studies on the topic are neither recent nor comprehensive. In addition, other data quality issues, such as inconsistencies and inaccuracies, are also of concern in the context of biological databases. A primary focus of this paper is to present and consolidate the opinions of over 20 experts and practitioners on the topic of duplication in biological sequence databases. The results reveal that survey participants believe that duplicate records are diverse; that the negative impacts of duplicates are severe, while positive impacts depend on correct identification of duplicates; and that duplicate detection methods need to be more precise, scalable, and robust. A secondary focus is to consider other quality issues. We observe that biocuration is the key mechanism used to ensure the quality of this data, and explore the issues through a case study of curation in UniProtKB/Swiss-Prot as well as an interview with an experienced biocurator. While biocuration is a vital solution for handling of data quality issues, a broader community effort is needed to provide adequate support for thorough biocuration in the face of widespread quality concerns.

scientific communication and education↗

bioRxiv2019

Open source computational simulation for a moth-inspired navigation algorithm

Olfactory navigation in insects, for instance when males search for mates, is a navigational problem of a self-propelled agent with limited sensor capabilities in a scalar field (odor) convected and diffused by turbulent wind. There are numerous navigation strategies proposed to explain the navigation paths of insects to food (flowers) or mating partners (females). In a search for a mate, the males use airborne pheromone puffs in turbulent environments around trees and vegetation. It is difficult to compare the various strategies because of a lack of a single simulation framework that can change a single parameter in time and test all the strategies against a controlled environment. This work aims at closing this gap, suggesting an open source, freely accessible simulation framework, abbreviated MothPy. We implement the simulation framework using another open source package (\"pompy\") that recreates a state-of-the-art puff-based odor plume model of Farrell et al. [1]. We add four different navigation strategies to the simulation framework based on and extending the previously published models [2, 3], and compare their performance with different wind and odor spread parameters. We test a sensitivity analysis of the navigation strategies to the plume meandering and to increased turbulence levels that are effectively expressed as the elevated puff spread rates. The simulations are compared statistically and provide an interesting view on the robustness and effectiveness of various strategies. This benchmarking-ready simulation framework could be useful for the biology-oriented, as well as engineering-oriented studies, assisting to deduce the evolutionary efficient strategies and improving self-propelled autonomous systems in complex environments.

animal behavior and cognition↗

bioRxiv2017

A unified web platform for network-based analyses of genomic data

Functional genomics networks are widely used to identify unexpected pathway relationships in large genomic datasets. However, it is challenging to quantitatively compare the signal-to-noise ratio of different networks, the biology they describe, and to identify the optimal network to interpret a particular genetic dataset. Via GeNets users can train a machine-learning model (Quack) to make such comparisons; and they can execute, store, and share analyses of genetic and RNA sequencing datasets.

genomics↗

bioRxiv2017

A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles

We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.\n\nHIGHLIGHTSO_LIA new gene expression profiling method, L1000, dramatically lowers cost\nC_LIO_LIThe Connectivity Map database now includes 1.3 million publicly accessible L1000 perturbational profiles\nC_LIO_LIThis expanded Connectivity Map facilitates discovery of small molecule mechanism of action and functional annotation of genetic variants\nC_LIO_LIThe work establishes feasibility and utility of a truly comprehensive Connectivity Map\nC_LI

genomics↗

bioRxiv2016

GSKB: A gene set database for pathway analysis in mouse

Interpretation of high-throughput genomics data based on biological pathways constitutes a constant challenge, partly because of the lack of supporting pathway database. In this study, we created a functional genomics knowledgebase in mouse, which includes 33,261 pathways and gene sets compiled from 40 sources such as Gene Ontology, KEGG, GeneSetDB, PANTHER, microRNA and transcription factor target genes, etc. In addition, we also manually collected and curated 8,747 lists of differentially expressed genes from 2,526 published gene expression studies to enable the detection of similarity to previously reported gene expression signatures. These two types of data constitute a Gene Set Knowledgebase (GSKB), which can be readily used by various pathway analysis software such as gene set enrichment analysis (GSEA). Using our knowledgebase, we were able to detect the correct microRNA (miR-29) pathway that was suppressed using antisense oligonucleotides and confirmed its role in inhibiting fibrogenesis, which might involve upregulation of transcription factor SMAD3. The knowledgebase can be queried as a source of published gene lists for further meta-analysis. Through meta-analysis of 56 published gene lists related to retina cells, we revealed two fundamentally different types of gene expression changes. One is related to stress and inflammatory response blamed for causing blindness in many diseases; the other associated with visual perception by normal retina cells. GSKB is available online at http://ge-lab.org/gs/, and also as a Bioconductor package (gskb, https://bioconductor.org/packages/gskb/). This database enables in-depth interpretation of mouse genomics data both in terms of known pathways and the context of thousands of published expression signatures.

bioinformatics↗