Biotechnology annual review最新文献

The chapter informs about different types of antibiotics, their structure, biosynthesis and their regulation. Industrial cultivation and isolation of antibiotics is described in the chapter. Search for microorganisms producing antibiotics and preparation of high-producing strains is described. Resistance against antibiotics in producing microorganisms and pathogens is discussed.

Solid-state fermentation has centuries of history, but it is only in the last two decades that there has been a concerted effort to understand the bioprocessing issues involved and to apply them to a wide range of new products. This article provides an overview of the knowledge of solid-state bioprocessing that has been gained over this time. It shows that, although significant advances have been achieved in understanding of what controls process performance, much research is still required.

The separation of biosynthetic polyunsaturated fatty acid (PUFA) was undertaken with supercritical fluid. The polyunsaturated fatty acid was synthesised by WL-1021, which is a strain of marine bacterium isolated from marine fish. The polyunsaturated fatty acid can be very efficiently extracted from WL-1021 that has the characteristics of rapid growth in the artificial medium. The PUFA in WL-1021 has been successfully separated by supercritical fluid extraction (SFE). The SFE process parameters including pressure, temperature and culture temperature variations have been measured by High Performance Liquid Chromatography (HPLC), GC/FT-IR and GC/MS.

The folate receptor is a cell surface protein that has recently been identified as a tumor marker, due to its differential overexpression in several malignancies. Current research indicates that folate can be covalently attached to the surface of liposomes to mediate their selective internalization by tumor cells through the folate receptor-mediated endocytic pathway. Optimized liposome formulations, characterized by improvements in drug loading, extended residence times in the circulation and improved drug release, have been developed to improve the biodistribution of therapeutic molecules. Theoretically, folate receptor-targeting can be combined with liposome encapsulation to synergistically affect disease outcome by enhancing the delivery of chemotherapeutic agents to neoplastic cells, while reducing systemic toxicities to normal tissues. The purpose of this chapter is to characterize the components of folate receptor-targeted liposomes, and summarize their applications in gene and drug delivery.

In silico biology has gathered momentum as, worldwide, scientists have united in a common quest to sequence, store and analyse complete genomes. This year, a pivotal achievement of this cooperative endeavour was realised in the release of a public draft of the human genome, and with it the promises to improve our understanding of diverse aspects of biology and to yield a healthier future with safe personalized medicines. Key to these goals will be the need to elucidate and characterise the genes and gene products encoded not just in the human genome, but in many genomes. These tasks are underpinned by the concepts and processes of genome and gene/protein evolution, regulation of gene expression, mechanisms of protein folding, the manifestation of protein function, and so on, all of which must be understood in the context of complex, dynamic biological systems. Our use of computers to model such concepts and systems must be placed in the context of the current limits of our understanding of them:- it is important to recognise, for example, that we don't have a common understanding either of what constitutes a gene or a protein function; we can't invariably say that a particular sequence or fold has arisen via divergent or convergent evolution; and we don't fully understand the rules of protein folding. Accepting what we can't do in silico is essential in appreciating what we can do. Without this understanding, it is easy to be misled, as notions of what particular computational approaches can achieve are sometimes rather optimistic. There are valuable lessons to be learned here from the field of Artificial Intelligence, principal among which is the realisation that capturing and representing complex knowledge is time consuming, expensive and hard. Thus, we argue here that if bioinformatics is to tackle biological complexity in earnest, it would be wise to absorb the experience distilled from decades of artificial intelligence research, and to approach the road ahead with caution, rigour and pragmatism.