FISH-FACS Proteomics: Enhanced label-free quantitative proteome analysis from ultra-low cell numbers of environmental microorganisms

Metaproteomics is an essential approach to analyse the in situ metabolic activity of microbes across various environments. In such highly diverse environmental samples, the functionality of specific microorganisms of importance often remains underexplored due to the protein inference problem arising from sequence homologies between organisms. One approach to overcome this challenge is the enrichment of non-culturable target organisms. However, this often result in samples with low protein content. In this study, we have developed a workflow that combines fluorescence in situ hybridisation (FISH) and fluorescence-activated cell sorting (FACS) with mass spectrometry-based proteomics to analyse proteins from non-culturable bacteria directly from environmental samples. We show that 1x105 cells are sufficient for reliable qualitative protein identifications, while 5x105 to 1x106 cells allow for reproducible protein quantification after FISH and FACS. Furthermore, the use of a taxon-specific database improves data analysis by significantly reducing the size of protein groups compared to metaproteomics data.

宏蛋白质组学（Metaproteomics）是解析各类环境中微生物原位代谢活性的核心手段。在高度多样的环境样品中，由于不同生物体间序列同源性引发的蛋白质推断问题，特定重要微生物的功能往往仍未得到充分探索。解决该挑战的一种思路是富集不可培养的目标微生物，但该方法通常会导致样品蛋白质含量偏低。本研究开发了一套整合荧光原位杂交（FISH）、荧光激活细胞分选（FACS）与基于质谱的蛋白质组学的实验流程，可直接从环境样品中对不可培养细菌的蛋白质进行分析。研究结果表明，1×10⁵个细胞即可满足可靠的定性蛋白质鉴定需求，而5×10⁵至1×10⁶个细胞则可在完成FISH与FACS处理后实现可重复的蛋白质定量。此外，相较于常规宏蛋白质组学数据，使用类群特异性数据库可显著缩小蛋白质群组的规模，从而优化数据分析流程。