Shift in vacuolar to cytosolic regime of infecting Salmonella from a dual proteome perspective.

By applying dual proteome profiling to Salmonella enterica serovar Typhimurium (S. Typhimurium) encounters with its epithelial host (here, S. Typhimurium infected human HeLa cells), a detailed interdependent and holistic proteomic perspective on host-pathogen interactions over the time course of infection was obtained. Data-independent acquisition (DIA)-based proteomics was found to outperform data-dependent acquisition (DDA) workflows, especially in identifying the downregulated bacterial proteome response during infection progression by permitting quantification of low abundant bacterial proteins at early times of infection when bacterial infection load is low. S. Typhimurium invasion and replication specific proteomic signatures in epithelial cells revealed interdependent host/pathogen specific responses besides pointing to putative novel infection markers and signalling responses, including regulated host proteins associated with Salmonella-modified membranes.

Use of Hybrid Data-Dependent and -Independent Acquisition Spectral Libraries Empowers Dual-Proteome Profiling.

In the context of bacterial infections, it is imperative that physiological responses can be studied in an integrated manner, meaning a simultaneous analysis of both the host and the pathogen responses. To improve the sensitivity of detection, data-independent acquisition (DIA)-based proteomics was found to outperform data-dependent acquisition (DDA) workflows in identifying and quantifying low-abundant proteins. Here, by making use of representative bacterial pathogen/host proteome samples, we report an optimized hybrid library generation workflow for DIA mass spectrometry relying on the use of data-dependent and in silico-predicted spectral libraries. When compared to searching DDA experiment-specific libraries only, the use of hybrid libraries significantly improved peptide detection to an extent suggesting that infection-relevant host-pathogen conditions could be profiled in sufficient depth without the need of a priori bacterial pathogen enrichment when studying the bacterial proteome. Proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD017904 and PXD017945.

Bacterial Genetic Engineering by Means of Recombineering for Reverse Genetics.

Serving a robust platform for reverse genetics enabling the in vivo study of gene functions primarily in enterobacteriaceae, recombineering -or recombination-mediated genetic engineering-represents a powerful and relative straightforward genetic engineering tool. Catalyzed by components of bacteriophage-encoded homologous recombination systems and only requiring short ∼40-50 base homologies, the targeted and precise introduction of modifications (e.g., deletions, knockouts, insertions and point mutations) into the chromosome and other episomal replicons is empowered. Furthermore, by its ability to make use of both double- and single-stranded linear DNA editing substrates (e.g., PCR products or oligonucleotides, respectively), lengthy subcloning of specific DNA sequences is circumvented. Further, the more recent implementation of CRISPR-associated endonucleases has allowed for more efficient screening of successful recombinants by the selective purging of non-edited cells, as well as the creation of markerless and scarless mutants. In this review we discuss various recombineering strategies to promote different types of gene modifications, how they are best applied, and their possible pitfalls.

Proteogenomics in Aid of Host-Pathogen Interaction Studies: A Bacterial Perspective.

By providing useful tools to study host-pathogen interactions, next-generation omics has recently enabled the study of gene expression changes in both pathogen and infected host simultaneously. However, since great discriminative power is required to study pathogen and host simultaneously throughout the infection process, the depth of quantitative gene expression profiling has proven to be unsatisfactory when focusing on bacterial pathogens, thus preferentially requiring specific strategies or the development of novel methodologies based on complementary omics approaches. In this review, we focus on the difficulties encountered when making use of proteogenomics approaches to study bacterial pathogenesis. In addition, we review different omics strategies (i.e., transcriptomics, proteomics and secretomics) and their applications for studying interactions of pathogens with their host.