Cycles Of Selection Research Articles

Enhancing Cellular and Enzymatic Properties Through In Vivo Continuous Evolution.

Directed evolution seeks to evolve target genes at a rate far exceeding the natural mutation rate, thereby endowing cellular and enzymatic properties with desired traits. In vivo continuous directed evolution achieves these purposes by generating libraries within living cells, enabling a continuous cycle of mutant generation and selection, enhancing the exploration of gene variants. Continuous evolution has become powerful tools for unraveling evolution mechanism and improving cellular and enzymatic properties. This review categorizes current continuous evolution into three distinct classes: non-targeted chromosomal, targeted chromosomal, and extra-chromosomal hypermutation approaches. It also compares various continuous evolution strategies based on different principles, providing a reference for selecting suitable methods for specific evolutionary goals. Furthermore, this review discusses the two primary limitations for further widespread application of in vivo continuous evolution, which are lack of general applicability and insufficient mutagenic capability. We envision that developing generally applicable mutagenic components and methods to enhance mutation rates for in vivo continuous evolution are promising future directions for wide range applications of continuous evolution.

Punjab Tar-1: A New Short Duration, High Yielding and Disease Resistance Long Melon Variety (Cucumis melo) Released in Pakistan.

The development of new crop varieties with favorable features is a continuing effort. With the passage of time, a cultivated variety becomes subjected to various biotic and abiotic plant stresses. This article describes development of an innovative and imaginative long melon cultivar called "Punjab Tar-1."This article discusses creation of a novel and inventive long melon variety known as "Punjab Tar-1." Current long melon varieties in Pakistan are sensitive to climatic conditions and susceptible to pest and disease attack. A New Short Duration, High Yielding and Disease Resistance Long Melon Variety (Cucumis melo) is released in Pakistan to address these current issues of long melon varieties A high yielding and early maturing variety of long melon “Punjab Tar-1” has been developed by Vegetable Research Institute, Faisalabad, Pakistan through mass selection. Plants were selected from an open pollinated indigenous source population with main emphasis on earliness, fruit shape, color and taste and yield. Selection intensity was 15% in 1st three selection cycles and 30% in subsequent four selection cycles whereas yield trials were started from 8th selection cycle. The fruit of this variety has a strong longitudinal rib that makes it difficult for eating by caterpillars. This variety has wide adaptability and exhibits stable yield across multiple environments. Notably, "Punjab Tar-1" contains 10.59 % crude protein and 1.08% crude fat content. Genetic uniformity and distinctiveness of this variety was confirmed through SSR polymorphism. Punjab Tar-1 variety has been approved by Punjab Seed Council in its meeting held on 2021 and was recommended for general cultivation in Punjab, Pakistan. Its certified seed is available for farmers at Vegetable Research Institute, Faisalabad. This newly approved variety will aid to save the precious foreign reserves by reducing vegetable seed import bill. In Pakistan, seed market of long melon is occupied by improved varieties. In multi-location evaluation, one said variety has exhibited high yield and stability than exotic germplasm. This is the first variety developed in Pakistan having good taste, early maturity, long shape, and high yield potential. DNA fingerprinting has further confirmed that it is distinct from local material, having novelty and diversity.

Genetic analysis of Vicia faba L.: Advancements, hereditary traits, and correlations in ‘Sakha 3’ × ‘Nubaria 3’

Genetic diversity, heritability, and genetic advance are crucial considerations in the field of plant breeding. This research aimed to evaluate these factors for traits related to yield in faba bean (Vicia faba L.), specifically focusing on the F3 and F4 generations resulting from the cross between ‘Sakha 3’ and ‘Nubaria 3’. In the initial season (2021/ 2022), 200 families from each F3 population were cultivated with specific spacing, and selection criteria included seed yield per plant (SYP) and the number of pods per plant (NPP). Top-performing plants were identified for the second cycle of pedigree selection. In the following season (2022/2023), the F4 families were arranged in a randomised complete block design. Traits like the number of branches per plant (NBP), NPP, SYP, and seed index (SI) showed substantial phenotypic and genotypic coefficients of variation, indicating their noteworthy variation. Phenotypic and genotypic correlation analyses showed positive associations between SYP and the NBP and NPP. Additionally, path coefficient analysis indicated that these traits had high positive direct effects on SYP. This research provides valuable insights into the genetic variability, heritability, and selection parameters for yield-related traits in faba bean, offering a foundation for future breeding programs aimed at improving yield and productivity.

5178 TNFα-dependent altered miRNA expression regulates endometrial stromal cell proliferation

Abstract Disclosure: I. Chowdhury: None. S. Banerjee: None. W. Xu: None. A. Driss: None. C. Nezhat: None. N. Sidell: None. R.N. Taylor: None. W.E. Thompson: None. Abstract: Aberrant upregulation of cytokines, including tumor necrosis factor α (TNFα) and activation of nuclear factor κB (NF-κB) with disbalance of microRNAs (miRNAs) are often found in endometrium of endometriosis subjects, which causes directly or indirectly pelvic inflammation, pain, and infertility, Although, the pathophysiology of endometriosis is not clearly established yet, inflammation is an essential feature. MicroRNAs are emerging as potential regulatory factors in cellular processes such as cell growth, survival, migration, and invasion. In the current study, we examined the direct effects of exogenous recombinant TNFα dependent regulation of miRNAs involved in proliferation in primary cultures of normal endometrial stromal cells (NESC) and compared with the untreated cells derived from endometriosis-ESC (EESC). NanoString nCounter-based assays and quantitative real-time polymerase chain reaction (RT-PCR) were used to identify and validate differentially expressed miRNAs linked to cell proliferation in EESC compared to NESC and TNFα treated NESCs. The expression level of miRNAs linked to cell cycle was downregulated significantly in EESCs compared to NESCs. Interestingly, a dose and time-dependent exogenous TNFα treatment in NESCs showed a similar cell cycle regulator miRNAs expression pattern with EESCs. In further studies, protein analysis by Western Blots of selective cell cycle regulators such as PCNA, Ki67, CDK2, CDK4, CDK6, p21, and p27, and cell proliferation assay demonstrated an inverse correlation between cell cycle regulators and miRNA expression pattern both in EESC and TNFα treated NESCs. These findings suggest that TNFα dependent dysregulation of miRNAs in EESCs may promote proliferation of endometriosis. Further research is needed to investigate the detailed mechanisms by which TNFα regulates miRNA expression and determine these findings' potential therapeutic implications. Acknowledgments: This study was supported in part by National Institutes of Health Grants 1SC3 GM113751, 1SC1 GM130544, U01 HD66439, 1R01HD057235, U54 CA118948, HD41749, S21MD000101, and G12-RR03034. This investigation was conducted in a facility constructed with support from Research Facilities Improvement Grant #C06 RR18386 from NIH/NCRR. Presentation: 6/2/2024

Potential genetic gains from targeted recombination versus recurrent selection for maize yield and moisture

AbstractRecurrent selection is a proven method and targeted recombination is a potential method for achieving genetic gain. Our objectives were to determine the (1) equivalency in predicted gains between cycles of recurrent selection and targeted recombination in maize (Zea mays L.), (2) correspondence between targeted‐recombination positions when gains from nontargeted chromosomes are considered versus ignored, and (3) trade‐offs in predicted gains for yield and moisture in targeted recombination. From genomewide marker effects for 2911 single nucleotide polymorphism loci in 270 biparental populations, we obtained predicted gains from fixed numbers of targeted recombinations and compared these gains to the genotypic‐value distributions of doubled haploids obtained from different cycles of simulated recurrent selection. On average, it took three cycles of single‐trait recurrent selection to obtain at least a few doubled haploid lines with the same performance achieved with nine or 10 targeted recombinations in Cycle 0. Results indicated that when targeting recombinations across the genome, gains from segregation on nontargeted chromosomes do not need to be considered. Predicted increases in yield were associated with increases in moisture. Given the logistics of pyramiding targeted recombinations and the lack of mature technologies for routine targeted recombination, recurrent selection is currently the preferred approach for accumulating favorable recombinations.

Enriching productive mutational paths accelerates enzyme evolution.

Darwinian evolution has given rise to all the enzymes that enable life on Earth. Mimicking natural selection, scientists have learned to tailor these biocatalysts through recursive cycles of mutation, selection and amplification, often relying on screening large protein libraries to productively modulate the complex interplay between protein structure, dynamics and function. Here we show that by removing destabilizing mutations at the library design stage and taking advantage of recent advances in gene synthesis, we can accelerate the evolution of a computationally designed enzyme. In only five rounds of evolution, we generated a Kemp eliminase-an enzymatic model system for proton transfer from carbon-that accelerates the proton abstraction step >108-fold over the uncatalyzed reaction. Recombining the resulting variant with a previously evolved Kemp eliminase HG3.17, which exhibits similar activity but differs by 29 substitutions, allowed us to chart the topography of the designer enzyme's fitness landscape, highlighting that a given protein scaffold can accommodate several, equally viable solutions to a specific catalytic problem.

Multi-trait modeling and machine learning discover new markers associated with stem traits in alfalfa.

Alfalfa biomass can be fractionated into leaf and stem components. Leaves comprise a protein-rich and highly digestible portion of biomass for ruminant animals, while stems constitute a high fiber and less digestible fraction, representing 50 to 70% of the biomass. However, little attention has focused on stem-related traits, which are a key aspect in improving the nutritional value and intake potential of alfalfa. This study aimed to identify molecular markers associated with four morphological traits in a panel of five populations of alfalfa generated over two cycles of divergent selection based on 16-h and 96-h in vitro neutral detergent fiber digestibility in stems. Phenotypic traits of stem color, presence of stem pith cells, winter standability, and winter injury were modeled using univariate and multivariate spatial mixed linear models (MLM), and the predicted values were used as response variables in genome-wide association studies (GWAS). The alfalfa panel was genotyped using a 3K DArTag SNP markers for the evaluation of the genetic structure and GWAS. Principal component and population structure analyses revealed differentiations between populations selected for high- and low-digestibility. Thirteen molecular markers were significantly associated with stem traits using either univariate or multivariate MLM. Additionally, support vector machine (SVM) and random forest (RF) algorithms were implemented to determine marker importance scores for stem traits and validate the GWAS results. The top-ranked markers from SVM and RF aligned with GWAS findings for solid stem pith, winter standability, and winter injury. Additionally, SVM identified additional markers with high variable importance for solid stem pith and winter injury. Most molecular markers were located in coding regions. These markers can facilitate marker-assisted selection to expedite breeding programs to increase winter hardiness or stem palatability.

Resistance to acetyl-CoA carboxylase (ACCase)-inhibiting herbicides in Lolium multiflorum Lam. populations of Argentina.

Italian ryegrass (Lolium multiflorum Lam.) is one of the most troublesome grass weeds in Argentina. The extensive and repetitive use of acetyl-CoA carboxylase (ACCase)-inhibiting herbicides has induced resistance in this weed species. The objectives of this study were to quantify the resistance levels to ACCase-inhibiting herbicides in two resistant populations and to identify the target-site mutations associated with their resistance. Two resistant Italian ryegrass populations, Roldán and H2, were studied. Roldán was a suspected haloxyfop-resistant population, located in a wheat field from Santa Fe province with a history of ACCase-inhibiting herbicide use. The H2 population was obtained from the susceptible Hernandarias population (H0) after two cycles of selection with the herbicide quizalofop-ethyl. Whole-plant dose-response assays revealed that the resistant populations exhibited a high resistance to haloxyfop, with resistance factors (RF) exceeding 97-fold. Additionally, both populations showed a moderate resistance to pinoxaden (RF > 7), while maintaining susceptibility to clethodim. Partial chloroplastic ACCase sequences revealed isoleucine-to-asparagine substitution at position 2041 (Ile-2041-Asn) in both resistant populations. This work provides a better understanding of cross-resistance to ACCase-inhibiting herbicides in L. multiflorum populations and represents the first report of the target-site mutation Ile-2041-Asn conferring resistance in populations from Argentina. © 2024 Society of Chemical Industry.

Selection environment impacts genetic gains for persistence in three temperate perennial forage grasses

Grasses and legumes are regularly grown in association, despite often being unbalanced or incompatible. This study was intended to conduct selection for persistence in three perennial grass species that have compatibility issues with alfalfa (Medicago sativa L.) or red clover (Trifolium pratense L.) and are poorly adapted to management-intensive rotational grazing. Five cycles of selection for persistence were conducted over a 24-year period for three grass species (reed canarygrass, smooth bromegrass, and timothy) in each of five selection environments: alfalfa mixture, red clover mixture, monocultures with a three-harvest hay management, tall fescue mixture with frequent defoliation, and monocultures with frequent defoliation. Selection in the two legume mixtures led to significant increases in persistence only when evaluated in legume mixtures. Selection responses were strongest when evaluated under the same legume as in the selection environment, indicating some species specificity. Selection for persistence under frequent defoliation was successful under both conditions (monoculture and tall fescue mixture), but led to no changes when evaluated with legumes. For these three grass species, cultivar development for use in mixture with legumes or for use in management-intensive rotational grazing should be based on a selection environment that mimics, as close as possible, the target production environment.

Genomic and phenotypic selection indices for decreased birth weight, shortening fattening period, and regulating total weight gain in beef cattle.

To develop genomic and phenotypic indices for beef cattle selection that afford progeny with reduced birth weight and fattening period. The indices should also allow regulating total weight gain during the fattening period and avoid marked increases of inbreeding. Whether addition of constraint on total weight gain to constraints on body weight gain at up to four specific time points during the fattening process was effective for the weight gain until the end of the fattening period was examined in two selection indices with the selection trait being a phenotypic or a genomic breeding value random regression coefficient. Both indices afforded cattle with desired weight gains at specific time points and desired total weight gains. One cycle of index-based selection made it possible to shorten the fattening period two weeks compared with that before selection while maintaining the same final fattening weight as before selection. The impact of constraining total weight gain was smallest when the number of weight gain constraints at specific time points was three or four. However, constraining total weight gain was necessary to avoid poor total weight gain when the number of weight gain constraints at specific time points was only one or two. The developed indices make it possible to regulate total weight gain during the fattening process and to achieve desired weight gains at specific time points. Importantly, the indices bring about genetic improvement without an excessive increase of inbreeding. Thus, we expect that these indices will contribute to sustainable genetic improvement in cattle while maintaining genetic diversity.

Predicting Surgical Resident Performance With Situational Judgment Tests.

Situational judgment tests (SJTs) have been proposed as an efficient, effective, and equitable approach to residency program applicant selection. This study examined how SJTs can predict milestone performance during early residency. General surgery residency program applicants during 3 selection cycles (2018-2019, 2019-2020, 2020-2021) completed SJTs. Accreditation Council for Graduate Medical Education milestone performance data from selected applicants were collected in March and April 2019, 2020, and 2021 and from residents in March 2020, August 2020, March 2021, September 2021, and March 2022. Descriptive statistics and correlations were computed and analysis of variance tests performed to examine differences among 4 SJT performance groups: green, top 10% to 25%; yellow, next 25% to 50%; red, bottom 50%; and unknown, did not complete the SJT. Data were collected for 70 residents from 7 surgery residency programs. Differences were found for patient care ( F3,189 = 3.19, P = .03), medical knowledge ( F3,176 = 3.22, P = .02), practice-based learning and improvement ( F3,189 = 3.18, P = .04), professionalism ( F3,189 = 3.82, P = .01), interpersonal and communication skills ( F3,190 = 3.35, P = .02), and overall milestone score ( F3,189 = 3.44, P = .02). The green group performed better on patient care, medical knowledge, practice-based learning and improvement, professionalism, and overall milestone score. The yellow group performed better than the red group on professionalism and overall milestone score, better than the green group on interpersonal and communication skills, and better than the unknown group on all but practice-based learning and improvement. The red group outperformed the unknown group on all but professionalism and outperformed the green group on medical knowledge. SJTs demonstrate promise for assessing important noncognitive attributes in residency applicants and align with national efforts to review candidates more holistically and minimize potential biases.

Empirical comparison of genomic selection to phenotypic selection for biomass yield of switchgrass

AbstractSwitchgrass (Panicum virgatum L.) is one of several grass species being bred for use as a biomass crop to support the biofuel industry. Increases in biomass yield are imperative to ensure that crops such as switchgrass can sustainably meet the needs of this industry. Genomic selection is one strategy that can accelerate breeding gains for complex traits such as biomass yield. The goal of this study was to conduct three cycles of genomic selection in a previously trained Liberty switchgrass population and compare that to one cycle of phenotypic selection, both of which required 3 years to complete. The advanced lines were tested across five locations and three hardiness zones in the Central United States using a randomized complete block design with four replicates. There were strong genotype × location interactions, but the first two generations of genomic selection were superior to Liberty at four of the five evaluation locations. Conversely, phenotypic selection failed to result in significant gains in biomass yield for any of the five evaluation locations. Based on these results from Liberty switchgrass, genomic selection methods are expected to at least double the rates of gain in biomass yield relative to previous estimates using phenotypic selection methods.

Research on Low-Carbon Design and Energy Efficiency by Harnessing Indigenous Resources through BIM-Ecotect Analysis in Hot Climates

In the face of contemporary challenges, such as economic instability, environmental degradation, and the urgent global warming crisis, the imperative of sustainability and energy efficiency has reached unparalleled significance. Sustainability encompasses not only the natural environment, but also extends to our immediate surroundings, including the built structures and the communities they serve. Embracing this comprehensive perspective, we embarked on a mission to conceive and construct a model house that harnesses state-of-the-art energy-efficient technologies. Our goal was to seamlessly integrate these features not only to meet our sustainability objectives, but also to mitigate environmental threats.This model embodies a harmonious fusion of indigenous resources, employing locally sourced stone and employing traditional construction techniques. Through this approach, we achieved significant reductions in carbon emissions and established a framework for passive cooling and heating systems. Moreover, the design is intrinsically attuned to its contextual surroundings, preserving the diverse tapestry of regional architectural styles. This study stands as a testament to the potential of innovative design and technology in shaping a sustainable future. The research employs a multi-dimensional approach, encompassing strategies of architectural design with a traditional planning approach, sustainable material selection, energy efficiency, and life cycle assessment across a diverse set of case studies. Building energy analysis is conducted through the application of BIM (Ecotect), providing insights into how BIM can adapt and thrive in various environments. Key findings underscore that thermal performance, minimizing energy loads, and reducing carbon emissions are pivotal aspects in designating a building as both green and energy efficient.

Exploring population genetics for mutant mungbean [Vigna radiata (L.) R. Wilczek] lines: Insights from augmented block design

AbstractThe current study was initiated to assess mungbean [Vigna radiata (L.) R. Wilczek] mutant lines for yield and their attributes in the mutation generation third (M3) generation using an augmented block design. Note that 1200 mutated mungbean lines were selected from the γ‐irradiated (400–700 Gy) population and distributed into 21 blocks, along with three popular varieties (checks) replicated in each block. To evaluate mean performance, variance, and population genetics, the observations on days to flowering, days to maturity, plant height (cm), number of clusters per plant, number of pods per plant, pod length (cm), protein percentage, seed index, and seed yield (g) were measured and analyzed. All the lines under consideration showed highly significant variations for all the variables, except for days to flowering. Seventy‐nine mutant lines were found to have significantly better yield attributes than checks and are currently being evaluated under station trial. Skewness and kurtosis analysis unveiled the presence of gene interactions, offering opportunities for targeted improvement and efficacy of γ rays as a mutagen, facilitating the release of variability within the population. Future mungbean breeding programs will benefit from the successful isolation of mutant plants with yield‐enhancing traits, such as up to 20 clusters per plant, 71 pods per plant, 8.55 cm pod length, 26.69% protein content (5% higher than parent), and 29 gram seeds per plant. In early selection cycles without the need for replicated trials, this study demonstrated the effectiveness of the mutagen and augmented design in creating novel variations, evaluating and identifying superior genotypes with improved yield potential.

RAbDesFlow: a novel workflow for computational recombinant antibody design for healthcare engineering.

Recombinant antibodies (rAbs) have emerged as a promising solution to tackle antigen specificity, enhancement of immunogenic potential and versatile functionalization to treat human diseases. The development of single chain variable fragments has helped accelerate treatment in cancers and viral infections, due to their favorable pharmacokinetics and human compatibility. However, designing rAbs is traditionally viewed as a genetic engineering problem, with phage display and cell free systems playing a major role in sequence selection for gene synthesis. The process of antibody engineering involves complex and time-consuming laboratory techniques, which demand substantial resources and expertise. The success rate of obtaining desired antibody candidates through experimental approaches can be modest, necessitating iterative cycles of selection and optimization. With ongoing advancements in technology, in silico design of diverse antibody libraries, screening and identification of potential candidates for in vitro validation can be accelerated. To meet this need, we have developed rAbDesFlow, a unified computational workflow for recombinant antibody engineering with open-source programs and tools for ease of implementation. The workflow encompasses five computational modules to perform antigen selection, antibody library generation, antigen and antibody structure modeling, antigen-antibody interaction modeling, structure analysis, and consensus ranking of potential antibody sequences for synthesis and experimental validation. The proposed workflow has been demonstrated through design of rAbs for the ovarian cancer antigen Mucin-16 (CA-125). This approach can serve as a blueprint for designing similar engineered molecules targeting other biomarkers, allowing for a simplified adaptation to different cancer types or disease-specific antigens.

Differential gene expression of salt-tolerant alfalfa in response to salinity and inoculation by Ensifer meliloti

BackgroundAlfalfa (Medicago sativa L.) experiences many negative effects under salinity stress, which may be mediated by recurrent selection. Salt-tolerant alfalfa may display unique adaptations in association with rhizobium under salt stress.ResultsTo elucidate inoculation effects on salt-tolerant alfalfa under salt stress, this study leveraged a salt-tolerant alfalfa population selected through two cycles of recurrent selection under high salt stress. After experiencing 120-day salt stress, mRNA was extracted from 8 random genotypes either grown in 0 or 8 dS/m salt stress with or without inoculation by Ensifer meliloti. Results showed 320 and 176 differentially expressed genes (DEGs) modulated in response to salinity stress or inoculation x salinity stress, respectively. Notable results in plants under 8 dS/m stress included upregulation of a key gene involved in the Target of Rapamycin (TOR) signaling pathway with a concomitant decrease in expression of the SNrK pathway. Inoculation of salt-stressed plants stimulated increased transcription of a sulfate-uptake gene as well as upregulation of the Lysine-27-trimethyltransferase (EZH2), Histone 3 (H3), and argonaute (AGO, a component of miRISC silencing complexes) genes related to epigenetic and post-transcriptional gene control.ConclusionsSalt-tolerant alfalfa may benefit from improved activity of TOR and decreased activity of SNrK1 in salt stress, while inoculation by rhizobiumstimulates production of sulfate uptake- and other unique genes.

Predictive Study on the Occurrence of Wheat Blossom Midges Based on Gene Expression Programming with Support Vector Machines.

This study addresses the challenges in plant pest and disease prediction within the context of smart agriculture, highlighting the need for efficient data processing techniques. In response to the limitations of existing models, which are characterized by slow training speeds and a low prediction accuracy, we introduce an innovative prediction method that integrates gene expression programming (GEP) with support vector machines (SVM). Our approach, the gene expression programming-support vector machine (GEP-SVM) model, begins with encoding and fitness function determination, progressing through cycles of selection, crossover, mutation, and the application of a convergence criterion. This method uniquely employs individual gene values as parameters for SVM, optimizing them through a grid search technique to refine genetic parameters. We tested this model using historical data on wheat blossom midges in Shaanxi Province, spanning from 1933 to 2010, and compared its performance against traditional methods, such as GEP, SVM, naive Bayes, K-nearest neighbor, and BP neural networks. Our findings reveal that the GEP-SVM model achieves a leading back-generation accuracy rate of 90.83%, demonstrating superior generalization and fitting capabilities. These results not only enhance the computational efficiency of pest and disease prediction in agriculture but also provide a scientific foundation for future predictive endeavors, contributing significantly to the optimization of agricultural production strategies.

A novel alloy design approach in developing CoNi-based high entropy superalloy using high entropy alloys thermodynamic and spark plasma sintering

This study introduces an innovative alloy design strategy by integrating HEAs principles to develop CoNi-based high entropy superalloys (HESAs). The powder of designed HESA produced using gas atomization and consolidated using spark plasma sintering (SPS). The alloy design strategy validated by CALPHAD to mitigate detrimental phase precipitation and segregation during powder production, material consolidation, and post-processing heat treatments. CoNi-HESA powder with a calculated mixing entropy of 1.568R was successfully developed and consolidated using SPS. Optimization of SPS parameters at 1175 °C, 10 min, and 100 °C/min achieved a relative density of 99.9 %. Subsequent heat treatments further improved the material's characteristics. Solutionizing at 1190 ± 10 °C for 2 h with water quenching resulted in a fine grain structure of ∼7 μm grain size. Aging at 900 °C for 24 h, followed by water quenching, yielded uniformly distributed fine γ′ precipitates comprising approximately 65 % of the γ matrix, without unwanted secondary precipitates or TCP phases. This study demonstrates the effectiveness of the novel approach in designing CoNi-based HESAs and optimizing their properties through careful process parameter selection and post-heat treatment cycles. The combination of thermodynamic calculations, HEA principles, and powder metallurgy techniques offers a promising approach for developing advanced high entropy superalloys with tailored microstructures.

In vitro selection of DNA aptamers against staphylococcal enterotoxin A

Staphylococcal enterotoxin A (SEA) is the most frequently reported in staphylococcal food poisoning (SFP) outbreaks. Aptamers are single-stranded nucleic acids that are seen as promising alternatives to antibodies in several areas, including diagnostics. In this work, systematic evolution of ligands by exponential enrichment (SELEX) was used to select DNA aptamers against SEA. The SELEX protocol employed magnetic beads as an immobilization matrix for the target molecule and real-time quantitative PCR (qPCR) for monitoring and optimizing sequence enrichment. After 10 selection cycles, the ssDNA pool with the highest affinity was sequenced by next generation sequencing (NGS). Approximately 3 million aptamer candidates were identified, and the most representative cluster sequences were selected for further characterization. The aptamer with the highest affinity showed an experimental dissociation constant (KD) of 13.36 ± 18.62 nM. Increased temperature negatively affected the affinity of the aptamer for the target. Application of the selected aptamers in a lateral flow assay demonstrated their functionality in detecting samples containing 100 ng SEA, the minimum amount capable of causing food poisoning. Overall, the applicability of DNA aptamers in SEA recognition was demonstrated and characterized under different conditions, paving the way for the development of diagnostic tools.

Settling selection of Chlamydomonas reinhardtii for samarium uptake.

Samarium (Sm) is a rare-earth element recently included in the list of critical elements due to its vital role in emerging new technologies. With an increasing demand for Sm, microbial bioremediation may provide a cost-effective and a more ecologically responsible alternative to remove and recover Sm. We capitalized on a previously selected Chlamydomonas reinhardtii strain tolerant to Sm (1.33 × 10-4 M) and acidic pH and carried out settling selection to increase the Sm uptake performance. We observed a rapid response to selection in terms of cellular phenotype. Cellular size decreased and circularity increased in a stepwise manner with every cycle of selection. After four cycles of selection, the derived CSm4 strain was significantly smaller and was capable of sequestrating 41% more Sm per cell (1.7 × 10-05 ± 1.7 × 10-06 ng) and twice as much Sm in terms of wet biomass (4.0 ± 0.4 mg Sm · g-1) compared to the ancestral candidate strain. The majority (~70%) of the Sm was bioaccumulated intracellularly, near acidocalcisomes or autophagic vacuoles as per TEM-EDX microanalyses. However, Sm analyses suggest a stronger response toward bioabsorption resulting from settling selection. Despite working with Sm and pH-tolerant strains, we observed an effect on fitness and photosynthesis inhibition when the strains were grown with Sm. Our results clearly show that phenotypic selection, such as settling selection, can significantly enhance Sm uptake. Laboratory selection of microalgae for rare-earth metal bioaccumulation and sorption can be a promising biotechnological approach.