BioTech最新文献

The dairy sector produces considerable amounts of nutrient-rich effluents, which are frequently undervalued as simple by-products or waste. In particular, Second Cheese Whey (SCW), also known as scotta, exhausted whey, or deproteinized whey, represents the liquid fraction from ricotta cheese production. Despite its abundance and high organic and saline content, SCW is often improperly discharged into terrestrial and aquatic ecosystems, causing both environmental impact and resource waste. The available purification methods are expensive for dairy companies, and, at best, SCW is reused as feed or fertilizer. In recent years, increasing awareness of sustainability and circular economy principles has increased interest in the valorization of SCW. Biological treatment of SCW using microalgae represents an attractive strategy, as it simultaneously reduces the organic load and converts waste into algal biomass. This biomass can be further valorized as a source of proteins, pigments, and bioactive compounds with industrial relevance, supporting applications in food, nutraceuticals, biofuels, and cosmetics. This review, starting from analyzing the characteristics, production volumes, and environmental issues associated with SCW, focused on the potential of microalgae application for their valorization. In addition, the broader regulatory and sustainability aspects related to biomass utilization and treated SCW are considered, highlighting both the promises and limitations of microalgae-based strategies by integrating technological prospects with policy considerations.

The detection of allergens is essential for ensuring food safety, protecting public health, and providing accurate information to consumers. Wheat (Triticum aestivum L.) and maize (Zea mays L.) are recognized as important food allergens. In this study, novel PCR methods were developed for the reliable detection of wheat and maize allergens, including wheat high-molecular-weight glutenin subunit (HMW-GS) and low-molecular-weight glutenin subunit (LMW-GS), as well as three maize allergens, namely, Zea m 14, Zea m 8, and zein. Wheat and maize genomic DNA, as well as allergen genes, were examined during 60 min of baking at 180 °C and 220 °C. Agarose gel electrophoresis revealed degradation of genomic DNA and amplified PCR fragments in correlation with increasing baking temperature and time. For each target gene, the best primers were identified that could detect HMW-GS and LMW-GS genes in wheat samples and Zea m 14, Zea m 8, and zein genes in maize samples after baking at 220 °C for 60 min and 40 min, respectively. The results indicate that these PCR methods can be used for the reliable and sensitive detection of wheat and maize allergens in processed foods.

This study evaluates the impact of biotic elicitors and hormone regimes on the in vitro establishment, shoot multiplication, and organogenesis of Solanum tuberosum L. cv. Fianna under controlled laboratory conditions. Explants derived from pre-treated tubers were cultured on Murashige and Skoog (MS) medium supplemented with vitamins and varying concentrations of growth regulators or elicitors. Aseptic establishment achieved a high success rate (~95%) using a 6% sodium hypochlorite disinfection protocol. Multiplication was significantly enhanced with a combination of 0.2 mg L^-1 naphthaleneacetic acid (NAA) and 0.5-1.0 mg L^-1 benzylaminopurine (BAP), producing the greatest number and length of shoots and roots. Direct organogenesis was stimulated by bio-elicitors Activane^®, Micobiol^®, and Stemicol^® in (MS) basal medium at mid-level concentrations (0.5 g or mL L^-1), improving shoot number, elongation, and root development. Activane^®, Micobiol^®, and Stemicol^® are commercial elicitors that stimulate plant defense pathways and morphogenesis through salicylic acid, microbial, and jasmonic acid signaling mechanisms, respectively. Indirect organogenesis showed significantly higher callus proliferation in Stemicol^® and Micobiol^® treatments compared to the control medium, resulting in the highest fresh weight, diameter, and friability of callus. The results demonstrate the potential of biotic elicitors as alternatives or enhancers to traditional plant growth regulators in potato tissue culture, supporting more efficient and cost-effective micropropagation strategies.

Organic-waste-derived volatile fatty acids (VFAs) are promising substrates for fungal biomass cultivation, offering a nutrient-rich medium capable of meeting microbial growth requirements. However, the growth and biomass productivity are highly influenced by the VFAs' composition and mode of operation. This study investigated the cultivation of Aspergillus oryzae fungal biomass using agro-industrial-derived VFA effluent, employing repeated-batch and fed-batch (stepwise and continuous-feeding) cultivation modes to evaluate fungal growth and biomass composition. The highest dry biomass yield of 0.41 dry biomass/gVFAs_fed (g/g) was achieved in fed-batch mode with continuous feeding, where the biomass exhibited pellet morphology, facilitating ease of harvesting. The crude protein content varied according to the cultivation strategy, reaching 45-53% in continuous-feeding fed-batch mode, while it was 34-42% in stepwise fed-batch mode. Additionally, the fungal biomass contained significant levels of essential macronutrients and trace elements, including Mg, Ca, K, Mn, and Fe, which are crucial if the biomass is intended to be used in animal feed formulations. This study highlights the effects of cultivation modes on biomass composition and the potential of VFA-derived fungal biomass as a sustainable feed ingredient.

Breast cancer is the most prevalent cancer among women and is challenging to diagnose and treat due to its diverse subtypes and stages. Precision medicine aims to improve early detection, prognosis, and treatment planning by identifying new clinical biomarkers. The review emphasizes the importance of using cutting-edge technology and artificial intelligence (AI) to identify new biomarkers associated with epithelial-mesenchymal transition (EMT). During EMT, epithelial cells transform into a mesenchymal state, a process driven by genetic and epigenetic alterations that facilitate cancer progression. The review discusses how statistical analysis and machine learning methods applied to multi-omics data facilitate the discovery of novel EMT-related biomarkers, thereby advancing therapeutic strategies. This conclusion is supported by numerous clinical and preclinical studies on breast cancer.

Pectins are high-value plant cell-wall polysaccharides with extensive applications in the food, pharmaceutical, textile, paper, and environmental sectors. Traditional extraction and processing methodologies rely heavily on harsh acids, high temperatures, and non-renewable solvents, generating substantial environmental and economic costs. This review consolidates recent advances across the entire Bacillus-pectinase value chain, from green pectin extraction and upstream substrate characterization, through process and statistical optimization of enzyme production, to industrial biocatalysis applications. We propose a practical roadmap for developing high-efficiency, low-environmental-footprint enzyme systems that support circular bioeconomy objectives. Critical evaluation of optimization strategies, including submerged versus solid-state fermentation, response surface methodology, artificial neural networks, and design of experiments, is supported by comparative data on strain performance, fermentation parameters, and industrial titers. Sector-specific case studies demonstrate the efficacy of Bacillus pectinases in fruit-juice clarification, textile bio-scouring, paper bio-bleaching, bio-based detergents, coffee and tea processing, oil extraction, animal feed enhancement, wastewater treatment, and plant-virus purification. Remaining challenges, including enzyme stability in complex matrices, techno-economic scale-up, and structure-guided protein engineering, are identified. Future directions are charted toward CRISPR-driven enzyme design and fully integrated circular-economy bioprocessing platforms.

Models that predict the 3D structure of proteins enable us to easily analyze the structure of unknown proteins. Though many of these models have been found to be accurate, their application in plant proteins is not always entirely accurate. Thus, we aimed to develop a versatile yet simple pipeline that can predict novel proteins with a specific function. As an example, via benchmark studies, we sought to discover novel UDP-glycosyltransferases (UGTs) potentially involved in ginsenoside biosynthesis. Since the functionality of these UGTs has been shown to be determined by a few amino acids, a 3D-structure-based pipeline was required. Our pipeline includes four sequential steps: a sequence-based homology search, AlphaFold3-based 3D structure prediction, docking simulations with ginsenoside intermediates using SwissDock and CB-Dock2, and MPEK analysis to assess interaction stability. Through the application of this benchmark, we optimized the role of each module in the pipeline and successfully identified four novel UGT candidates. These candidates are predicted to catalyze the conversion of protopanaxadiol (PPD) to compound K (CK) or protopanaxatriol (PPT) to ginsenoside F1. This pilot study demonstrates how our pipeline can be used for the functional annotation of plant proteins and the discovery of enzymes involved in specialized pathways.

While databases are emerging across various domains, from small molecules to genomics and proteins, aptamer databases remain scarce, if not entirely absent. Such databases could serve as a comprehensive resource for advancing research, innovation, and the applications of aptamer technology across multiple fields. This advancement would likely lead to improvements in healthcare, environmental monitoring, and biotechnology. Furthermore, the establishment of aptamer databases would facilitate molecular modelling and machine learning, opening doors to further advancements in understanding and utilizing aptamers. Against this backdrop, in this study, we present and benchmark the Base Randomization Algorithm (BRA) as a potential solution to the scarcity of aptamer databases. Through statistical analysis, we examine key factors such as minimum free energy (MFE), base compositions, and base arrangements. Notably, sequences generated using the BRA exhibit a Gaussian distribution pattern. We also examine the details of how each base within a sequence is chosen using mathematical principles, ensuring that the sequences are valid and optimized statistically. Additionally, we explore how the length of the randomized generated sequences can affect the folding of their structures at both the secondary and tertiary levels. Based on composition analysis, we propose that the base mean of the dataset can be approximated as x¯B≈Px × N, for dataset of sequences with the same length and x¯B≈Px × M, where M is the median and N the mean, for a dataset with randomized length that follows a Gaussian distribution.

Insect-derived frass is gaining attention as a circular bioeconomy product with fertilizing and pest-suppressive potential. This study investigates Tenebrio molitor frass as a soil amendment for promoting beneficial nematodes and suppressing Meloidogyne incognita. A 40-day pot experiment on clay loam soil tested with six inputs: raw and heat-treated frass (0.5%, 1% w/w), Melia azedarach fruit powder (1.6%), and an untreated control. Soil nematode communities were assessed at 5 and 40 days after application (DAA), and nematicidal activity was evaluated in vitro. Raw frass at 1% induced a rapid response from free-living nematodes at 5 DAA, with increased abundance of bacterivorous taxa such as Rhabditis and Acrobeloides, alongside a higher Enrichment Index (EI), indicating short-term nutrient availability. At 40 DAA, only 1% raw frass consistently supported more cp-1 bacterivores and slightly increased Shannon diversity. Network analysis revealed more connected, modular structures in raw frass treatments, suggesting enhanced food web complexity. However, omnivore and predator effects were limited. Raw frass extracts caused over 80% paralysis of Meloidogyne incognita juveniles within 24 h, significantly outperforming heat-treated frass and Melia extracts. T. molitor frass moderately stimulates opportunistic nematodes and provides strong nematicidal effects, supporting its potential as a multifunctional input for sustainable soil management.

The adult lumbar spinal cord plays a critical role in locomotor control and somatosensory integration, whose transcriptional architecture under physiological conditions has been characterized in various studies with restricted numbers of individuals (up to four). Here, we present an integrative single-nucleus RNA sequencing (snRNA-seq) atlas of the healthy adult mouse lumbar spinal cord, assembled from over 86,000 nuclei from 16 samples across five public datasets. Using a harmonized computational pipeline, we identify all major spinal cell lineages and resolve 17 transcriptionally distinct neuronal subtypes. A central novelty of our approach is the systematic inclusion of non-coding RNAs (ncRNAs), including long non-coding RNAs (lncRNAs) and pseudogenes. By comparing transcriptomic analyses based on coding-only, non-coding-only, and combined gene sets, we show that ncRNAs, despite accounting to a 10% of the recorded information of each cell, contribute to cell type-specific signatures. This resource offers a high-resolution, ncRNA-inclusive reference for the adult spinal cord and provides a foundation for future studies on spinal plasticity, injury, and regeneration.