Randomly barcoded transposon mutant libraries for gut commensals II: Applying libraries for functional genetics.

The critical role of the intestinal microbiota in human health and disease is well recognized. Nevertheless, there are still large gaps in our understanding of the functions and mechanisms encoded in the genomes of most members of the gut microbiota. Genome-scale libraries of transposon mutants are a powerful tool to help us address this gap. Recent advances in barcoded transposon mutagenesis have dramatically lowered the cost of mutant fitness determination in hundreds of in vitro and in vivo experimental conditions. In an accompanying review, we discuss recent advances and caveats for the construction of pooled and arrayed barcoded transposon mutant libraries in human gut commensals. In this review, we discuss how these libraries can be used across a wide range of applications, the technical aspects involved, and expectations for such screens

A Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue

We have developed a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions. Spatially targeted proteomics is a technology for analyzing the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting complex protein profiles (e.g., of key tissue subregions) can pose a challenge due to the high-dimensional nature of the data. To address this challenge, we developed a multivariate approach to explore such data and applied it to analyze a published spatially targeted proteomics dataset collected from Staphylococcus aureus-infected murine kidney, 4-days and 10-days post-infection. The multivariate data analysis process we developed rapidly filters complex biological data to determine the most relevant species from hundreds to thousands of measured molecules avoiding the more traditional univariate and targeted viewpoint of tracking individual proteins. We employ principal component analysis (PCA) for dimensionality reduction and grouping of correlated and anticorrelated proteins among regions and timepoints previously measured by mass spectrometry through micro-liquid extraction surface analysis (microLESA). Subsequently, k-means clustering of the PCA-processed data was used to group samples in an unsupervised manner. Interpretation of the resultant cluster centers revealed a subset of proteins among those detected that differentiate among spatial regions of infection over two timepoints. These proteins are involved in the glycolysis and TCA metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis of the protein subsets in each cluster uncovered patterns in the dataset used related to tissue damage and repair as well as calcium-related defense mechanisms during staphylococcal infection. By applying this analysis in an infectious disease case study, we observed differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions

Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue

Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.</p

Randomly barcoded transposon mutant libraries for gut commensals II: Applying libraries for functional genetics

Summary: The critical role of the intestinal microbiota in human health and disease is well recognized. Nevertheless, there are still large gaps in our understanding of the functions and mechanisms encoded in the genomes of most members of the gut microbiota. Genome-scale libraries of transposon mutants are a powerful tool to help us address this gap. Recent advances in barcoded transposon mutagenesis have dramatically lowered the cost of mutant fitness determination in hundreds of in vitro and in vivo experimental conditions. In an accompanying review, we discuss recent advances and caveats for the construction of pooled and arrayed barcoded transposon mutant libraries in human gut commensals. In this review, we discuss how these libraries can be used across a wide range of applications, the technical aspects involved, and expectations for such screens