Quantitative proteomics (QP) was that which moved mere qualitative proteomic data, towards that which started making sense, not just sense but statistics. QP data is essential for predicting and validating the role of differentially expressed proteins in various cellular processes and thus QP has led to a better understanding of various diseases of high significance which has been well documented in previous reviews. However, with respect to tuberculosis (TB), an assessment of the current achievements made through QP has never been reviewed. Therefore, in this review, a coherent report regarding milestones and achievements of QP in TB research is presented. Furthermore, the strengths of labeled and label free QP as successful tools in leading to a fundamental understanding of TB and the causal organism is systematically expatiated. The challenges facing the success of QP and the scope for expanding its territories to reach newer horizons are contemplated.

定量蛋白质组学（QP）是仅将定性蛋白质组学数据转移到开始有意义的数据上的方法，不仅有意义，而且统计也是如此。QP数据对于预测和验证差异表达蛋白在各种细胞过程中的作用至关重要，因此QP导致人们更好地理解了各种具有重要意义的疾病，这在先前的综述中已得到充分证明。但是，关于结核病，从未审查过通过合格专家进行的当前成就的评估。因此，在这篇综述中，提出了有关结核病研究中QP的里程碑和成就的连贯报告。此外，系统地阐述了标记的和无标记的QP作为成功的工具的力量，这些QP可以导致人们对TB和病因有机体有基本的了解。