Bacterial cellulose (BC) nanofibers are one of the stiffest organic materials produced by nature. It consists of pure cellulose without the impurities that are commonly found in plant-based cellulose. This review discusses the metabolic pathways of cellulose-producing bacteria and the genetic pathways of Acetobacter xylinum. The fermentative production of BC and the bioprocess parameters for the cultivation of bacteria are also discussed. The influence of the composition of the culture medium, pH, temperature, and oxygen content on the morphology and yield of BC are reviewed. In addition, the progress made to date on the genetic modification of bacteria to increase the yield of BC and the large-scale production of BC using various bioreactors, namely static and agitated cultures, stirred tank, airlift, aerosol, rotary, and membrane reactors, is reviewed. The challenges in commercial scale production of BC are thoroughly discussed and the efficiency of various bioreactors is compared. In terms of the application of BC, particular emphasis is placed on the utilization of BC in advanced fiber composites to manufacture the next generation truly green, sustainable and renewable hierarchical composites.

Triggered biodegradable composites made entirely from renewable resources are urgently sought after to improve material recyclability or be able to divert materials from waste streams. Many biobased polymers and natural fibers usually display poor interfacial adhesion when combined in a composite material. Here we propose a way to modify the surfaces of natural fibers by utilizing bacteria (Acetobacter xylinum) to deposit nanosized bacterial cellulose around natural fibers, which enhances their adhesion to renewable polymers. This paper describes the process of modifying large quantities of natural fibers with bacterial cellulose through their use as substrates for bacteria during fermentation. The modified fibers were characterized by scanning electron microscopy, single fiber tensile tests, X-ray photoelectron spectroscopy, and inverse gas chromatography to determine their surface and mechanical properties. The practical adhesion between the modified fibers and the renewable polymers cellulose acetate butyrate and poly(L-lactic acid) was quantified using the single fiber pullout test.

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In recent years, the potential of stem cell research for tissue engineering-based therapies and regenerative medicine clinical applications has become well established. In 2006, Chung pioneered the first entire organ transplant using adult stem cells and a scaffold for clinical evaluation. With this a new milestone was achieved, with seven patients with myelomeningocele receiving stem cell-derived bladder transplants resulting in substantial improvements in their quality of life. While a bladder is a relatively simple organ, the breakthrough highlights the incredible benefits that can be gained from the cross-disciplinary nature of tissue engineering and regenerative medicine (TERM) that encompasses stem cell research and stem cell bioprocessing. Unquestionably, the development of bioprocess technologies for the transfer of the current laboratory-based practice of stem cell tissue culture to the clinic as therapeutics necessitates the application of engineering principles and practices to achieve control, reproducibility, automation, validation and safety of the process and the product. The successful translation will require contributions from fundamental research (from developmental biology to the 'omics' technologies and advances in immunology) and from existing industrial practice (biologics), especially on automation, quality assurance and regulation. The timely development, integration and execution of various components will be critical-failures of the past (such as in the commercialization of skin equivalents) on marketing, pricing, production and advertising should not be repeated. This review aims to address the principles required for successful stem cell bioprocessing so that they can be applied deftly to clinical applications.

Fed-batch cultures are used in producing monoclonal antibodies industrially. Existing protocols are developed empirically. Model-based tools aiming to improve productivity are useful with model reliability and computational demand being important. Herein, a systematic framework for developing predictive models is presented comprising of model development, global sensitivity analysis, optimal experimental design for parameter estimation, and predictive capability checking. Its efficacy and validity are demonstrated using a fed-batch structured/unstructured model of antibody-secreting hybridoma cultures. Global sensitivity analysis is first used to identify sensitive model parameters (initial values estimated from batch cultures). Information-rich data from an optimally designed fed-batch experiment are then used to estimate these parameters, resulting in good agreement between simulation and experimental results. Finally, the model's predictive capability is confirmed by comparison with an independent set of fed-batch cultures. This approach systematises the process of developing predictive cell culture models at a minimum experimental cost, enabling modelbased control and optimisation.3

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