Brown goat yogurt: Metabolomics, peptidomics and sensory changes during production

Brown goat milk products have gained popularity for their unique taste and flavor. The emergence of chain-reversal phenomenon makes the design and development of goat milk products gradually tend to a consumer-oriented model. However, the precise mechanism of how browning and fermentation process causes characteristics is not clear. In an effort to understand how the treatments potentially lead to certain metabolite profile changes in goat milk, comprehensive, quantitative metabolomics and peptidomics analysis of goat milk samples after browning and fermentation were undertaken. An intelligent hybrid z-score standardization-principal components algorithm-multimodal denoising autoencoder was used for feature fusion and hidden layer fusion in high-dimensional variable space. The fermentation process significantly improved the flavor of brown goat yogurt through tricarboxylic acid-urea-glycolysis composite pathway. Bitter peptides HPFLEWAR, PPGLPDKY, and PPPPPKK have strong interactions with both DPP IV and ACE, proving that brown goat yogurt can be considered as effective provider of potential DPP IV and ACE inhibitors. The level of health-promoting bioactive components and sensory contributed to consumer selection. The proposed multimodal data integrative analysis platform was applicable to explain the impact of the dynamic changes of metabolites and peptides on consumer preferences.

褐变山羊乳制品因其独特的口感与风味而广受青睐。链式反转现象的出现，使得山羊乳制品的设计与开发逐渐转向以消费者为导向的模式。然而，褐变与发酵过程如何赋予产品特定风味特征的精准机制尚未阐明。为探究各类处理方式如何诱发山羊乳代谢谱与肽谱的潜在变化，研究团队对经过褐变与发酵处理的山羊乳样本开展了全面的定量代谢组学（metabolomics）与肽组学（peptidomics）分析。本研究采用智能混合算法架构：Z分数标准化（z-score standardization）-主成分算法（principal components algorithm）-多模态降噪自编码器（multimodal denoising autoencoder），用于高维变量空间内的特征融合与隐层融合。发酵过程通过三羧酸-尿素-糖酵解复合通路，显著改善了褐变山羊酸奶的风味品质。苦味肽HPFLEWAR、PPGLPDKY与PPPPPKK可与二肽基肽酶IV（DPP IV）及血管紧张素转换酶（ACE）产生强相互作用，证实褐变山羊酸奶可作为潜在DPP IV与ACE抑制剂的有效来源。有益健康的生物活性成分水平与感官属性共同影响消费者的选择偏好。本研究提出的多模态数据整合分析平台，可用于阐释代谢物与肽类的动态变化对消费者偏好的影响机制。