Microbial abundance dynamics along time axis can be used to explore complex interactions among microorganisms. This is very important to use time series data for understanding the structure and function of a microbial community and its dynamic characteristics with the purturbations of external environment and physiology. Species with Time Delay regulatory network of relationships will be more suitable for microbial interactions, because the regulation between microorganisms is often a slow process with delay, rather than an instantaneous process. In this study, a novel local linear manifold-constrained Vector Autoregression (LVAR) model that considered the time delay among microbial interactions is developed for analyzing microbiomics data in the application. The experimental results indicate that the new approach has better performance than several other VAR-based models and demonstrate its capability of extracting relevant microbial interactions.