MetaProD: A Highly-Configurable Mass Spectrometry Analyzer for Multiplexed Proteomic and Metaproteomic Data

The microbiome has been shown to be important for human
health
because of its influence on disease and the immune response. Mass
spectrometry is an important tool for evaluating protein expression
and species composition in the microbiome but is technically challenging
and time-consuming. Multiplexing has emerged as a way to make spectrometry
workflows faster while improving results. Here, we present MetaProD
(MetaProteomics in Django) as a highly configurable metaproteomic
data analysis pipeline supporting label-free and multiplexed mass
spectrometry. The pipeline is open-source, uses fully open-source
tools, and is integrated with Django to offer a web-based interface
for configuration and data access. Benchmarking of MetaProD using
multiple metaproteomics data sets showed that MetaProD achieved fast
and efficient identification of peptides and proteins. Application
of MetaProD to a multiplexed cancer data set resulted in identification
of more differentially expressed human proteins in cancer tissues
versus healthy tissues as compared to previous studies; in addition,
MetaProD identified bacterial proteins in those samples, some of which
are differentially abundant.