Biotechnology Industry Research Articles

Knowledge diversity and technology innovation output: intraorganizational collaboration networks

PurposeThis study investigates the impact of knowledge diversity on technology innovation output with a particular focus on communities within intraorganizational collaboration networks. It further explores the moderating effects of the quantity of star scientists and community cohesion.Design/methodology/approachA dataset of patent information from the Chinese biotechnology industry spanning 1985 to 2022, sourced from the CNIPR platform, is used to construct intraorganizational collaboration networks and measure variables. The greedy modularity algorithm is applied to identify community structures within these networks. Additionally, a negative binomial regression model is employed to test the proposed hypotheses.FindingsKnowledge diversity positively influences the technology innovation output of communities within intraorganizational collaboration networks. Meanwhile, the quantity of star scientists and community cohesion have negative and positive moderating effects, respectively. Furthermore, higher community cohesion attenuates the negative moderating effect of the quantity of star scientists.Originality/valuePrevious studies have highlighted the critical role of intraorganizational collaboration networks in facilitating the utilization of diverse knowledge. However, most research has primarily focused on organizations as a whole or teams within organizations. This study shifts the emphasis to the role of communities and pays particular attention to the quantity of star scientists and community cohesion, two critical conditional factors that moderate the influence of knowledge diversity. By incorporating these factors, this study provides a comprehensive perspective on both the microstructures and macrostructures of network communities.

Interspecies interactions promote dual-species biofilm formation by Lactiplantibacillus plantarum and Limosilactobacillus fermentum: Phenotypic and metabolomic insights.

Interspecies interactions promote dual-species biofilm formation by Lactiplantibacillus plantarum and Limosilactobacillus fermentum: Phenotypic and metabolomic insights.

Structure, rheology and antioxidant properties of a polysaccharide from Atractylodes macrocephala in Pan'an.

Structure, rheology and antioxidant properties of a polysaccharide from Atractylodes macrocephala in Pan'an.

Controlled ionic-induced self-assembly of phycocyanin: Structure, binding mechanism, and molecular dynamics simulation.

Controlled ionic-induced self-assembly of phycocyanin: Structure, binding mechanism, and molecular dynamics simulation.

Biosensor-guided evolution boosts itaconic acid production, unveiling unique insights into the stringent response.

Biosensor-guided evolution boosts itaconic acid production, unveiling unique insights into the stringent response.

Application of a Rational Crystal Contact Engineering Strategy on a Poly(ethylene terephthalate)-Degrading Cutinase

Industrial biotechnology offers a potential ecological solution for PET recycling under relatively mild reaction conditions via enzymatic degradation, particularly using the leaf branch compost cutinase (LCC) quadruple mutant ICCG. To improve the efficient downstream processing of this biocatalyst after heterologous gene expression with a suitable production host, protein crystallization can serve as an effective purification/capture step. Enhancing protein crystallization was achieved in recent studies by introducing electrostatic (and aromatic) interactions in two homologous alcohol dehydrogenases (Lb/LkADH) and an ene reductase (NspER1-L1,5) produced with Escherichia coli. In this study, ICCG, which is difficult to crystallize, was utilized for the application of crystal contact engineering strategies, resulting in ICCG mutant L50Y (ICCGY). Previously focused on the Lys-Glu interaction for the introduction of electrostatic interactions at crystal contacts, the applicability of the engineering strategy was extended here to an Arg-Glu interaction to increase crystallizability, as shown for ICCGY T110E. Furthermore, the rationale of the engineering approach is demonstrated by introducing Lys and Glu at non-crystal contacts or sites without potential interaction partners as negative controls. These resulting mutants crystallized comparably but not superior to the wild-type protein. As demonstrated by this study, crystal contact engineering emerges as a promising approach for rationally enhancing protein crystallization. This advancement could significantly streamline biotechnological downstream processing, offering a more efficient pathway for research and industry.

Analysis of Human Gut Microbiota Enzymes for Biotechnological and Food Industrial Applications.

The human gut microbiota is a complex and dynamic ecosystem, recognized for its valuable and wide array of physiological functions. This study investigated the human gut microbiota as a source of enzymes for innovative applications in the biomedicine, bioremediation, and food and feed biotechnological industries by integrating data from combined in silico and in vitro approaches. A total of 93 easily cultivable strains were selected from a bank of isolated microorganisms generated from the gut microbiota of children under different media and conditions. First, genomic data screening and enzyme interrogation of reference genomes corresponding to the selected species were carried out using a custom bioinformatic searching protocol. The extraction and interpretation of encoding enzymes from the genomic taxa results focused on four major phyla (Bacillota, Bacteroidota, Actinomycetota, and Pseudomonadota) and seven genera (Bacillus, Bacteroides, Clostridium, Enterobacter, Enterococcus, Microbacterium, and Staphylococcus) according to their cultivability and biotechnological relevance and interest. A total of 364 enzymes were identified across protein annotations, highlighting amylases, cellulases, inulinases, lipases, proteases, and laccases. Second, phenotypic assays confirmed these main enzymatic activities in 80.6% of 93 isolates. Notable findings included Bacillus species displaying relevant amylase and laccase activity. This study demonstrates the utility of combining genomic annotations with functional assays, offering a robust approach for exploiting gut microbiota enzymes to develop innovative and sustainable biotechnological processes. Moreover, regulatory mechanisms governing enzyme expression in gut resilient microbes are essential steps toward unlocking the full potential of gut microbiota-derived biocatalysts.

Modern Microbiology: Exploring Microbial Frontiers in Health, Environment, and Biotechnology

Microbiology, the study of microscopic organisms including bacteria, viruses, fungi, archaea, and protozoa, remains one of the most dynamic and transformative disciplines in modern science. It is foundational to understanding diverse biological systems, from molecular genetics to ecosystem function, and is integral to advancements in biotechnology, medicine, and environmental science. The field has expanded significantly with the advent of molecular biology and omics technologies, enabling precise exploration of microbial genetics, physiology, and metabolic networks. Microorganisms, while recognized as agents of disease, are also vital for global biogeochemical cycles, nutrient turnover, and ecological resilience. Recent decades have seen a surge in interest driven by the emergence of antibiotic resistance, the global burden of infectious diseases, and the need to decode host microbe interactions. Innovations such as next generation sequencing, metagenomics, and single cell analysis have redefined microbial ecology by revealing the complexity and ubiquity of unculturable microbial communities across environments—from the human gut microbiota to extreme ecosystems like deep sea hydrothermal vents. Simultaneously, the rise of synthetic biology and microbial bioengineering has paved the way for novel applications in sustainable energy, environmental remediation, and industrial biotechnology. Particularly, the human microbiome has emerged as a frontier linking microbial diversity to immunity, metabolic health, and neurodevelopmental outcomes. As microbiology increasingly converges with computational biology, nanotechnology, and systems medicine, it is poised to offer transformative solutions to global challenges in health, food security, and environmental sustainability. This overview synthesizes the current landscape of microbiological research, spotlighting core concepts and emerging directions that define the field’s evolution.

Advances in Diversity, Evolutionary Dynamics and Biotechnological Potential of Restriction-Modification Systems.

Restriction-modification systems (RMS) are ubiquitous in prokaryotes and serve as primitive immune-like mechanisms that safeguard microbial genomes against foreign genetic elements. Beyond their well-known role in sequence-specific defense, RMS also contribute significantly to genomic stability, drive evolutionary processes, and mitigate the deleterious effects of mutations. This review provides a comprehensive synthesis of current insights into RMS, emphasizing their structural and functional diversity, ecological and evolutionary roles, and expanding applications in biotechnology. By integrating recent advances with an analysis of persisting challenges, we highlight the critical contributions of RMS to both fundamental microbiology and practical applications in biomedicine and industrial biotechnology. Furthermore, we discuss emerging research directions in RMS, particularly in light of novel technologies and the increasing importance of microbial genetics in addressing global health and environmental issues.

From data extraction to analysis: a comparative study of ELISE capabilities in scientific literature.

The exponential growth of scientific literature presents challenges for pharmaceutical, biotechnological, and Medtech industries, particularly in regulatory documentation, clinical research, and systematic reviews. Ensuring accurate data extraction, literature synthesis, and compliance with industry standards require AI tools that not only streamline workflows but also uphold scientific rigor. This study evaluates the performance of AI tools designed for bibliographic review, data extraction, and scientific synthesis, assessing their impact on decision-making, regulatory compliance, and research productivity. The AI tools assessed include general-purpose models like ChatGPT and specialized solutions such as ELISE (Elevated LIfe SciencEs), SciSpace/Typeset, Humata, and Epsilon. The evaluation is based on three main criteria: Extraction, Comprehension, and Analysis with Compliance and Traceability (ECACT) as additional dimensions. Human experts established reference benchmarks, while AI Evaluator models ensure objective performance measurement. The study introduces the ECACT score, a structured metric assessing AI reliability in scientific literature analysis, regulatory reporting and clinical documentation. Results demonstrate that ELISE consistently outperforms other AI tools, excelling in precise data extraction, deep contextual comprehension, and advanced content analysis. ELISE's ability to generate traceable, well-reasoned insights makes it particularly well-suited for high-stakes applications such as regulatory affairs, clinical trials, and medical documentation, where accuracy, transparency, and compliance are paramount. Unlike other AI tools, ELISE provides expert-level reasoning and explainability, ensuring AI-generated insights align with industry best practices. ChatGPT is efficient in data retrieval but lacks precision in complex analysis, limiting its use in high-stakes decision-making. Epsilon, Humata, and SciSpace/Typeset exhibit moderate performance, with variability affecting their reliability in critical applications. In conclusion, while AI tools such as ELISE enhance literature review, regulatory writing, and clinical data interpretation, human oversight remains essential to validate AI outputs and ensure compliance with scientific and regulatory standards. For pharmaceutical, biotechnological, and Medtech industries, AI integration must strike a balance between automation and expert supervision to maintain data integrity, transparency, and regulatory adherence.

MstH Is the Major High-Affinity Glucose Transporter with Pleiotropic Roles in Carbon Utilization Regulation and Citric Acid Production in Aspergillus niger.

Aspergillus niger is a versatile industrial workhorse for bulk biomanufacturing of organic acids and enzymic proteins owing to its remarkable capacity to utilize diverse crude carbon sources. Glucose, a primary carbon source, plays a critical role in industrial bioprocesses; however, the key components and mechanisms of its dual-affinity transport system in A. niger remain poorly characterized. Herein, we employed transcriptomic profiling and functional analysis of null mutants to comprehensively investigate the glucose transport system. We identified MstH as the principal high-affinity glucose transporter, surpassing MstA in importance, and demonstrated its collaboration with MstC under glucose-abundant conditions. Overexpression of MstH in A. niger significantly enhanced citric acid production by 41.94% compared to that of the parent strain. Furthermore, coexpression of MstH, MstC, and the citrate exporter CexA, along with the deletion of the byproduct-associated genes agdA (α-glucosidase) and oahA (oxaloacetate acetyl hydrolase), led to a citric acid titer of 155.87 ± 0.86 g/L, representing a 3-fold improvement. Transcriptomic analysis revealed that MstH overexpression downregulated the carbon catabolite repressor creA while activating the transcription factor amyR, resulting in upregulation of mstA and mstF and extensive derepression of amylolytic enzymes. Importantly, the point-mutated MstH variant MstHR156K, with impaired transport function, retained its regulatory effects on creA and amyR, suggesting a moonlighting role for MstH in glucose uptake and carbon utilization regulation. These findings offer new insights into the underlying mechanisms of carbon source utilization and highlight the promising engineering targets for strain optimization in industrial biotechnology.

Membrane Selectivity Mechanisms of the Antimicrobial Peptide Snakin-Z Against Prokaryotic and Eukaryotic Membrane Models.

Snakin-Z, a novel cationic antimicrobial peptide (AMP) derived from Zizyphus jujuba fruits, exhibits broad-spectrum antimicrobial activity against bacteria and fungi. Importantly, it displays minimal hemolytic activity toward human red blood cells (RBCs). Elucidating the molecular basis of membrane selectivity of Snakin-Z is essential for its development as a novel antimicrobial agent. In this study, all-atom molecular dynamics (MD) simulations were employed to provide detailed molecular insights into the interactions between Snakin-Z and bacterial, fungal, and RBC membrane models. The simulations revealed a helical-coil conformation for Snakin-Z, with its amphipathic structure, polarity, and residues such as Arg, Lys, Ser, and Tyr playing crucial roles in mediating selective interactions with the microbial membrane models. Specifically, Arg28, Lys29, and Arg3 were identified as playing a crucial role in mediating membrane binding and stability. Snakin-Z was observed to be deeply embedded in the Candida albicans and Bacillus subtilis membrane models, followed by Escherichia coli and RBC membrane models. A considerable thinning and strong disordering of Candida albicans, Bacillus subtilis and Escherichia coli membranes acyl chains were observed. The presence of cholesterol in the RBC membrane contributes to its resistance to Snakin-Z-mediated disruption. This study presents the first comprehensive investigation of the selective mechanism underlying the antimicrobial activity of Snakin-Z against bacterial membrane models. Our findings provide insights into the antimicrobial properties of Snakin-Z at the molecular level, highlighting its significant potential for use in the food and biotechnology industries as a promising alternative to conventional antibiotics and preservatives.

Metabolic Engineering of Yeast.

Microbial cell factories have been developed to produce various compounds in a sustainable and economically viable manner. The yeast Saccharomyces cerevisiae has been used as a platform cell factory in industrial biotechnology with numerous advantages, including ease of operation, rapid growth, and tolerance for various industrial stressors. Advances in synthetic biology and metabolic models have accelerated the design-build-test-learn cycle in metabolic engineering, significantly facilitating the development of yeast strains with complex phenotypes, including the redirection of metabolic fluxes to desired products, the expansion of the spectrum of usable substrates, and the improvement of the physiological properties of strain. Strains with enhanced titer, rate, and yield are now competing with traditional petroleum-based industrial approaches. This review highlights recent advances and perspectives in the metabolic engineering of yeasts for the production of a variety of compounds, including fuels, chemicals, proteins, and peptides, as well as advancements in synthetic biology tools and mathematical modeling.

Enhanced Production, Purification, and Characterization of α-Glucosidase from NTG-Mutagenized Aspergillus niger for Industrial Applications

α-Glucosidase is an essential enzyme widely used in the food and biotechnology industries for the production of isomaltose oligosaccharides (IMOs). In this study, Aspergillus niger ASP004 was subjected to two rounds of nitrosoguanidine (NTG) mutagenesis, yielding a high-producing strain, NTG-II-3-64, with a 3.7-fold increase in enzyme activity under optimized fermentation conditions. The enzyme was purified through ultrafiltration, ethanol precipitation, DEAE ion-exchange, and gel filtration chromatography, resulting in an electrophoretically pure heterodimeric protein with a native molecular mass of approximately 230 kDa, composed of two subunits. The purified α-glucosidase exhibited optimal activity at 60 °C and pH 4.5, maintaining over 90% activity within a pH range of 3.0–6.0. Kinetic analysis using p-nitrophenyl-α-D-glucopyranoside as the substrate showed a Km of 0.17 mM and a Vmax of 18.7 µmol min−1 mg−1. Additionally, the enzyme displayed transglucosidase activity, converting maltose into isomaltose oligosaccharides (IMOs), including isomaltose, panose, and isomaltriose. These findings highlight the effectiveness of NTG mutagenesis for enhancing α-glucosidase production and support its industrial application.

Bridging the Skills Gap: Insights and Recommendations for Updating Medical Biotechnology Master's Curriculum in Iran

Background: Biotechnology is a rapidly developing field, and Iran aims to enhance its position in biosimilars through improved educational frameworks. Successful nations, such as the U.S., UK, Switzerland, China, and India, exemplify the positive impact of targeted educational programs in producing skilled graduates who advance the biotech sector. Research indicates a significant connection between curriculum relevance and graduate employability, suggesting that comprehensive curriculum assessment and reform can enhance student success and faculty involvement. This study investigated the necessity of revising the Master's curriculum in Medical Biotechnology in Iran to align with industry demands and global advancements. Methods: The current curriculum's effectiveness using the Delphi method was assessed to survey Master's students, professors, and industry stakeholders. Results: Findings revealed that while the current curriculum moderately aligns with educational objectives, significant gaps exist in practical training and resource availability. Many students reported feeling inadequately prepared for employment, particularly in essential skills such as animal cell culture, vaccine and monoclonal antibody design and production, and human skills like effective communication and teamwork. To address these deficiencies, some new courses focusing on practical experience and interdisciplinary approaches were recommended. Recommendations included enhancing laboratory facilities, integrating internships, and adopting team-based learning methods to improve student engagement and skill acquisition. Conclusion: Continuous investment in biotechnology education is crucial for maintaining competitive advantages in a globalized market. Overall, this research highlighted the importance of adapting educational programs to meet the dynamic needs of the biotechnology industry, ensuring graduates possess the necessary skills for successful careers in this field.

Acquisitions as catalysts for inventor departures in the biotechnology industry

In high-tech industries, where intellectual property is crucial, the acquisition of intangible assets and tacit knowledge of employees is one of the main motivations for Mergers and Acquisitions (M&As). The takeover wave in the biotechnology industry in the 1990s following the molecular biology revolution is a well-known example of how M&As were used to absorb new knowledge. However, after an M&A, it is uncertain whether key R&D employees who embody valuable knowledge and potential future innovations can be retained. Even if not all employees are relevant to the success of the acquisition, inventors are among the most valuable. This is especially true when acquiring an innovative startup. In this paper, we estimate how likely it is that an inventor working for an acquired biotechnology company will leave. Using a difference-in-differences approach with matching for both firms and inventors. We find that inventors affected by acquisitions are 20% more likely to leave the company. Our results contribute to the current debate on acqui-hiring of high-tech startups.

Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning.

Digital twins (DTs) are advancing biotechnology by providing digital models for drug discovery, digital health applications, and biological assets, including microorganisms. However, the hypothesis posits that implementing micro- and nanoscale DTs, especially for biological entities like bacteria, presents substantial challenges. These challenges stem from the complexities of data extraction, transmission, and computation, along with the necessity for a specialized Internet of Things (IoT) infrastructure. To address these challenges, this article proposes a novel framework that leverages bio-network technologies, including the Internet of Bio-Nano Things (IoBNT), and decentralized deep learning algorithms such as federated learning (FL) and convolutional neural networks (CNN). The methodology involves using CNNs for robust pattern recognition and FL to reduce bandwidth consumption while enhancing security. IoBNT devices are utilized for precise microscopic data acquisition and transmission, which ensures minimal error rates. The results demonstrate a multi-class classification accuracy of 98.7% across 33 bacteria categories, achieving over 99% bandwidth savings. Additionally, IoBNT integration reduces biological data transfer errors by up to 98%, even under worst-case conditions. This framework is further supported by an adaptable, user-friendly dashboard, expanding its applicability across pharmaceutical and biotechnology industries.

Purification of CRISPR Cas12a from E. coli cell lysates using peptide affinity ligands

Purification of CRISPR Cas12a from E. coli cell lysates using peptide affinity ligands

Engineering a cpGFP-based biosensor for enhanced quantification of glycolate production in Escherichia coli.

Engineering a cpGFP-based biosensor for enhanced quantification of glycolate production in Escherichia coli.

Molecular process control for industrial biotechnology.

Molecular process control for industrial biotechnology.