Volatile fatty acids as indicators of process imbalance in anaerobic digestors

In continuously stirred tank reactor experiments, with manure as substrate at thermophilic temperatures, the use of volatile fatty acids (VFA) as process indicators was investigated. Changes in VFA level were shown to be a good parameter for indicating process instability. The VFA were evaluated according to their relative changes caused by changes in hydraulic loading, organic loading or temperature. Butyrate and isobutyrate together were found to be particularly good indicators. Butyrate and isobutyrate concentrations increased significantly 1 or 2 days after the imposed perturbation, which makes these acids suitable for process monitoring and important for process control of the anaerobic biological system. In addition it was shown in a batch experiment that VFA at concentrations up to 50 mM did not reduce the overall methane production rate. This showed that VFA accumulation in anaerobic reactors was the result of process imbalance, not the cause of inhibition, thus justifying the use of VFA as process indicators.     

A Note on Maritime Delimitation in a Multizonal Context: The Case of the Mediterranean

This article points out some of the issues that may arise during the delimitation of maritime boundary in a sea area where coastal states have proclaimed various maritime zones. Issues considered include delimitation in the presence of overlapping or coincident zones, the role of existing boundaries, use of all-purpose maritime boundaries, and the delimitation of future zones. Special reference is made to the Mediterranean Sea where coastal states have advanced various claims consisting of zones sometimes different from the ones provided for in the 1982 United Nations Convention on the Law of the Sea.     

Cutting edge: L-selectin (CD62L) expression distinguishes small resting memory CD4+ T cells that preferentially respond to recall antigen

Naive CD4+ T cells use L-selectin (CD62L) expression to facilitate immune surveillance. However, the reasons for its expression on a subset of memory CD4+ T cells are unknown. We show that memory CD4+ T cells expressing CD62L were smaller, proliferated well in response to tetanus toxoid, had longer telomeres, and expressed genes and proteins consistent with immune surveillance function. Conversely, memory CD4+ T cells lacking CD62L expression were larger, proliferated poorly in response to tetanus toxoid, had shorter telomeres, and expressed genes and proteins consistent with effector function. These findings suggest that CD62L expression facilitates immune surveillance by programming CD4+ T cell blood and lymph node recirculation, irrespective of naive or memory CD4+ T cell phenotype.     

MHCPred: bringing a quantitative dimension to the online prediction of MHC binding

The accurate prediction of T cell epitopes is one of the key aspirations of immunoinformatics. We have developed a partial least squares-based, robust multivariate statistical method for the quantitative prediction of peptide binding to major histocompatibility complexes (MHCs), the principal checkpoint on the antigen presentation pathway. As a service to the immunobiology community, we have made a Perl implementation of the method available as a World Wide Web server.     

Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.     

Anaerobic biotechnological approaches for production of liquid energy carriers from biomass

In recent years, increasing attention has been paid to the use of renewable biomass for energy production. Anaerobic biotechnological approaches for production of liquid energy carriers (ethanol and a mixture of acetone, butanol and ethanol) from biomass can be employed to decrease environmental pollution and reduce dependency on fossil fuels. There are two major biological processes that can convert biomass to liquid energy carriers via anaerobic biological breakdown of organic matter: ethanol fermentation and mixed acetone, butanol, ethanol (ABE) fermentation. The specific product formation is determined by substrates and microbial communities available as well as the operating conditions applied. In this review, we evaluate the recent biotechnological approaches employed in ethanol and ABE fermentation. Practical applicability of different technologies is discussed taking into account the microbiology and biochemistry of the processes.     

VaxiJen: a server for prediction of protective antigens,tumour antigens and subunit vaccines

Background  

Vaccine development in the post-genomic era often begins with the in silico screening of genome information, with the most probable protective antigens being predicted rather than requiring causative microorganisms to be grown. Despite the obvious advantages of this approach – such as speed and cost efficiency – its success remains dependent on the accuracy of antigen prediction. Most approaches use sequence alignment to identify antigens. This is problematic for several reasons. Some proteins lack obvious sequence similarity, although they may share similar structures and biological properties. The antigenicity of a sequence may be encoded in a subtle and recondite manner not amendable to direct identification by sequence alignment. The discovery of truly novel antigens will be frustrated by their lack of similarity to antigens of known provenance. To overcome the limitations of alignment-dependent methods, we propose a new alignment-free approach for antigen prediction, which is based on auto cross covariance (ACC) transformation of protein sequences into uniform vectors of principal amino acid properties.