Molecular diagnostics for the prediction and improvement of mixed starter culture performance in cheese production

2007年，乳制品销售额估计为116亿美元，占加拿大食品和饮料行业的15%。切达奶酪的产量继续增加，2008年仅魁北克就达到67127,000公斤，占加拿大切达奶酪产量的46.5%。奶酪占加拿大乳制品出口的24.6%，但这些出口仅占国际市场乳制品的1%。制作这种数量的奶酪所需的大量乳酸发酵剂是一项重要的投资，任何质量控制方面的问题都可能由于发酵或成熟失败而导致相当大的损失。对于切达奶酪，开胃菜是由乳酸乳球菌亚种的混合菌株组成的。奶酪的质量和风味与所使用的乳球菌菌株的技术能力有很强的关系。然而，并非所有菌株在混合培养中都是兼容的，并且可能产生不希望的效果，例如奶酪中的苦味或异味，只有在昂贵的成熟期之后才能检测到，从而导致奶酪降级并失去消费者的信心。许多菌株对噬菌体的攻击变得敏感，必须加以替换。因此，大量的时间和金钱投入到表征和评价乳酸球菌菌株的代谢活性方面的传统方法。工业菌株的合理选择必须建立在技术能力和性能的客观标准之上，这可以通过基因和蛋白质表达对菌株稳定性和兼容性的更深入理解来促进创新的预测模型。本项目的目的是通过将基因和蛋白质表达谱分类为牛奶发酵性能的指标

In 2007, dairy products sales were evaluated at $11.6 billion, accounting for 15% of the Canadian food and beverage sector. Cheddar production continues to increase, hitting 67,127,000 kg in 2008 for Quebec alone, which is 46.5% of Canada's production of Cheddar cheese. Cheeses represent 24.6% of Canadian dairy product exports, but these exports make up only 1% of dairy products on the international market. The large quantity of lactic starter cultures required for making this amount of cheese represents an important investment and any problems with quality control can lead to considerable losses due to fermentation or ripening failures. For Cheddar cheese, starters are composed of mixed strains of Lactococcus lactis subsp. cremoris and there is a strong relationship between cheese quality and flavour and the technological aptitudes of the lactococcal strains used. However, not all strains are compatible in mixed culture and may produce undesired effects such as bitter or off-flavours in the cheese that are only detected after the costly ripening period, resulting in cheese downgrading and loss of consumer confidence. Many strains become sensitive to phage attack, and must be replaced. Thus, considerable effort in time and money is put into characterization and evaluation of the performance of lactococcal strains by conventional methods in terms of their metabolic activities. A rational choice of industrial strains must be founded on objective criteria of technological aptitude and performance, which could be facilitated using innovative predictive modelling issuing from a deeper understanding of strain stability and compatibility that will be revealed through gene and protein expression. The aim of this project is to predict milk fermentation performance by classifying gene and protein expression profiles as indicators of