Reduced incorporation of the influenza B virus BM2 protein in virus particles decreases infectivity

BM2 is the fourth integral membrane protein encoded by the influenza B virus genome. It is synthesized late in infection and transported to the plasma membrane from where it is subsequently incorporated into progeny virus particles. It has recently been reported that BM2 has ion channel activity and may be the functional homologue of the influenza A virus M2 protein acting as an ion channel involved in viral entry. Using a reverse genetic approach it was not possible to recover virus which lacked BM2. A recombinant influenza B virus was generated in which the BM2 AUG initiation codon was mutated to GUG. This decreased the efficiency of translation of BM2 protein such that progeny virions contained only 1/8 the amount of BM2 seen in wild-type virus. The reduction in BM2 incorporation resulted in a reduction in infectivity although there was no concomitant decrease in the numbers of virions released from the infected cells. These data imply that the incorporation of sufficient BM2 protein into influenza B virions is required for infectivity of the virus particles. (C) 2004 Elsevier Inc. All rights reserved.

Fully automated software solution for protein quantitation by global metabolic labeling with stable isotopes

Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

Comparison of a trained sensory panel and an electronic tongue in the assessment of bitter dairy protein hydrolsates

The bitter taste elicited by dairy protein hydrolysates (DPH) is a renowned issue for their acceptability by consumers and therefore incorporation into foods. The traditional method of assessment of taste in foods is by sensory analysis but this can be problematic due to the overall unpleasantness of the samples. Thus, there is a growing interest into the use of electronic tongues (e-tongues) as an alternative method to quantify the bitterness in such samples. In the present study the response of the e-tongue to the standard bitter agent caffeine and a range of both casein and whey based hydrolysates was compared to that of a trained sensory panel. Partial least square regression (PLS) was employed to compare the response of the e-tongue and the sensory panel. There was strong correlation shown between the two methods in the analysis of caffeine (R2 of 0.98) and DPH samples with R2 values ranging from 0.94-0.99. This study exhibits potential for the e-tongue to be used in bitterness screening in DPHs to reduce the reliance on expensive and time consuming sensory panels.