This article mainly describes a fermentation and purification method for expressing recombinant collagen protein in Escherichia coli. The method comprises constructing engineered bacteria expressing human type III collagen and adopting a strategy of feeding in batches for high-density fermentation. The rapid proliferation of bacterial cells is promoted at 37°C, and then the culture is inoculated into a fermentation tank with different carbon sources for growth. When glycerol is used as the main carbon source, the yield of recombinant collagen protein can reach 0.25 to 0.40 g/L. The method allows exploration of the differences in recombinant collagen production with different carbon sources in order to identify the most suitable fermentation medium component. The human type III collagen produced by the method has the typical structure of collagen, with high cell adhesion and the stability of tissue structure. Therefore, it can be used as the raw material for various collagen products, especially facial fillers, dressings, freeze-dried fibers, and gels. © 2025 Wiley Periodicals LLC. Basic Protocol: Fermentation and purification of recombinant human type III collagen expressed in Escherichia coli.
Cancer drug resistance, whether intrinsic or acquired, underlies most relapses and treatment failures. Reliable preclinical models are crucial to define resistance mechanisms and test counterstrategies. This overview article concisely compares three model classes: (1) clinical, patient‑derived xenografts that retain tumor heterogeneity and can mirror patient resistance; (2) induced‑resistance models produced by prolonged drug selection in vivo or in vitro that recapitulate tumor evolution under therapy; and (3) engineered isogenic cell lines that isolate specific resistance drivers. We summarize some key resistance mechanisms revealed and potential therapeutic approaches informed by these models, including rational combinations, mutation‑targeted inhibitors/degraders, efflux/epigenetic modulators, and immune-related combinations. Each model has trade‑offs, but integrating them accelerates mechanistic insight and translational drug development. This overview guides selection of preclinical models and design of strategies to overcome cancer drug resistance. © 2025 Wiley Periodicals LLC.
Tumor-treating fields (TTFields) represent an innovative approach to cancer treatment that leverages low-intensity (1-3 V/cm) alternating electric fields operating at intermediate frequencies (100-300 kHz). These electric fields are specifically designed to disrupt the mitotic process, thereby inhibiting the proliferation of malignant cells. Recent research has shown that TTFields not only induce direct cytotoxic effects but also modulate the immune system by triggering immunogenic cancer cell death, thereby enhancing immune cell infiltration into tumor sites. This dual mechanism opens up new possibilities for synergistic integration with immunotherapy, which has already revolutionized oncology through the advent of immune-checkpoint inhibitors, adoptive cell therapies, and cancer vaccines. Given the immune-modulatory properties of TTFields, there is growing interest in exploring their potential synergistic effect to enhance immunotherapeutic efficacy. Recognizing the complementary role of TTFields in cancer treatment paves the way for innovative combinatorial strategies that may further improve patient outcomes by enhancing the effectiveness of both TTFields and immunotherapy. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC.
Unattended endotoxin (ETX) contamination in biological samples constitute a major challenge for in vitro and in vivo applications. Besides being potentially life-threatening, ETX contamination is especially relevant in global transcriptome analyses, where competing ETX stimulation can significantly skew the final gene expression profile. Our studies in mice and cultured skin epithelial cells (epidermal keratinocytes) aiming to characterize the effect of antibodies such as AK23 immunoglobulins (IgG directed against the cell-cell adhesion molecule desmoglein [DSG] 3) in the autoimmune disease pemphigus vulgaris (PV) revealed that laboratory-produced and even commercial control antibodies can exhibit non-negligible ETX contaminations. Moreover, these contaminants are extremely difficult to remove. To overcome these challenges, we have devised a simple yet nontoxic and scalable two-step protocol to efficiently reduce ETX levels during or after the IgG purification process. It consists firstly of 0.5 M NaOH pre-treatment of all devices, including the protein A resin, used during IgG sanitization and purification, in parallel with meticulous in-process monitoring of ETX levels. Secondly, before IgG elution from protein A, ETX is stripped from IgG by ion-exchange with the common amino acid arginine. This two-step approach successfully reduces ETX by >95% from hybridoma-derived, laboratory-produced AK23 IgG, as well as patient PV and control IgG, resulting in an 85% IgG recovery rate and ETX levels compatible with U.S. Pharmacopeia guidelines. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Sanitization of devices and protein A resin with 0.5 M NaOH Basic Protocol 2: On-column stripping of ETX from AK23 IgG Basic Protocol 3: Quality control of sanitized AK23 IgG.
Large-scale genomics efforts led to the identification of an increasing number of mutations in various cancers. However, the functional role of a vast majority of these mutations in disease pathogenesis remains unknown. For enzymes whose activity can be blocked by approved drugs, knowledge regarding the effect of novel or uncommon mutations on inhibitor sensitivity helps in opting for effective treatment strategies. However, it is impossible to experimentally evaluate pathogenic effect and drug sensitivity for all mutations that are being identified in multiple diseases. Therefore, computational predictions of pathogenicity and drug sensitivity can potentially help in the design of an individualized treatment approach. This article includes computational methods to: (a) predict the pathogenicity of mutations based on primary and tertiary structures of the target enzyme, (b) study the effect of mutations on protein conformation, and (c) predict the binding affinity of mutant structures towards targeted therapeutics. All the methods utilize freely available computational tools and have considerable translational value in improving patient outcomes with targeted therapy. © 2025 Wiley Periodicals LLC. Basic Protocol 1: Pathogenicity prediction of mutations based on primary and tertiary structures Basic Protocol 2: Homology modeling of mutant protein structures Basic Protocol 3: Understanding the effect of mutations on protein conformation Basic Protocol 4: Predicting the binding affinities of mutant proteins towards specific inhibitors.
