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Host-pathogen dynamics through targeted secretome analysis of stimulated macrophages.

ABSTRACT: The pattern recognition receptors (PRRs) facilitate an organism's first line of defense against interlopers and shape the overall innate immune response through sensing and sampling pathogen-associated molecular patterns (PAMPs). The Toll-like receptor (TLR) family is the prototypic PRR family. Upon recognition of PAMPs, TLRs promote MyD88 dependent and independent responses. Understanding how different PAMPs are recognized by their specific TLRs and how pathogen recognition initiates immune activation is an intense area of research. Previously, we have reported the discovery of the temporal changes in signaling cascades of macrophage proteome and secretome post-stimulation with three different PAMPs. To extend our global proteomics approach to targeted protein abundance quantification, we describe the macrophage secretome targeted proteomics assay. We chose three different pathogens that specifically stimulate diverse TLRs (TLR2, TLR4, and TLR7). Using a simple targeted proteomics approach, combining data-dependent acquisition with an inclusion list, an array of cytokines, chemokines, and transcription factors can be profiled for their secretome abundance. This strategy facilitates the profiling and validation of pathogen-specific temporal changes in the macrophage secretome.

SUBMITTER: Khan MM

PROVIDER: S-EPMC6149218 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Project description:Amphibians, the most threatened group of vertebrates, are seen as indicators of the sixth mass extinction on earth. Thousands of species are threatened with extinction and many have been affected by an emerging infectious disease, chytridiomycosis, caused by the fungal pathogen, Batrachochytrium dendrobatidis (Bd). However, amphibians exhibit different responses to the pathogen, such as survival and population persistence with infection, or mortality of individuals and complete population collapse after pathogen invasion. Multiple factors can affect host pathogen dynamics, yet few studies have provided a temporal view that encompasses both the epizootic phase (i.e. pathogen invasion and host collapse), and the transition to a more stable co-existence (i.e. recovery of infected host populations). In the Sierra Nevada mountains of California, USA, conspecific populations of frogs currently exhibit dramatically different host/ Bd-pathogen dynamics. To provide a temporal context by which present day dynamics may be better understood, we use a Bd qPCR assay to test 1165 amphibian specimens collected between 1900 and 2005. Our historical analyses reveal a pattern of pathogen invasion and eventual spread across the Sierra Nevada over the last century. Although we found a small number of Bd-infections prior to 1970, these showed no sign of spread or increase in infection prevalence over multiple decades. After the late 1970s, when mass die offs were first noted, our data show Bd as much more prevalent and more spatially spread out, suggesting epizootic spread. However, across the ~400km2 area, we found no evidence of a wave-like pattern, but instead discovered multiple, nearly-simultaneous invasions within regions. We found that Bd invaded and spread in the central Sierra Nevada (Yosemite National Park area) about four decades before it invaded and spread in the southern Sierra Nevada (Sequoia and Kings Canyon National Parks area), and suggest that the temporal pattern of pathogen invasion may help explain divergent contemporary host pathogen dynamics.

Project description:Purpose: The purpose of this study was to simulataneously examine the host and fungal pathogen transcriptional profiles of four distinct infection fates during macrophage and Candida albicans interactions Methods: Membrane stained (Deep Red),primary, bone marrow derived, murine macrophages and Candida albicans expressing GFP and mCherry were exposed to each other over a four hour time course. Samples were collected at 0, 1, 2 and 4 hours and sorted for four infection subpopulations: 1. Macrophages which phagocytosed live C. albicans (GFP+ /mCherry+ /Deep Red +), 2. Macrophages which phagocytosed dead C. albicans (GFP- /mCherry+ /Deep Red +), 3. Uninfected macrophages(GFP- /mCherry- /Deep Red +) and 4. Unengulfed C. albicans (GFP+ /mCherry + /Deep Red -). Unexposed controls were also collected for some time points (i.e. macrophages never exposed to C. albicans and C. albicans never exposed to macrophages). Single macrophages infected with live or dead C. albicans were also sorted. Smart-seq2 was used to create libraries for both infection subpopulation and single, infected cell samples that were sequenced on Illumina’s Miseqand Nextseq. Basic quality assessment of Illumina reads and sample demultiplexing was done with Picard version 1.107 and Trimmomatic. Samples profiling exclusively the mouse transcriptional response were aligned to the mouse transcriptome generated from the v. Dec. 2011 GRCm38/mm10 and a collection of mouse rRNA sequences from the UCSC genome website. Samples profiling exclusively the yeast transcriptional response were aligned to the C. albicans transcriptome strain SC5314 version A21-s02-m09-r10 downloaded from Candida Genome Database. Samples containing both macrophages and C. albicans were aligned to a “composite transcriptome” made by combining the mouse transcriptome and C. albicans transcriptomes described above and alignment was done via BWA (version 0.7.10-r789.) Multi-reads (reads that aligned to both host and pathogen transcripts) were discarded. Then, each host or pathogen sample file were aligned to its corresponding reference using Bowtie2 and RSEM (v.1.2.21). Transcript abundance was estimated using transcripts per million (TPM). For subpopulation samples, TPM was calculated using edgeR, all as implemented in the Trinity package version 2.1.. Genes were considered differentially expressed only if they had a 4-fold change difference (> 4 FC) in TPM values and a false discovery rate below or equal to 0.001 (FDR < 0.001), unless specified otherwise. For single macrophages infected with C. albicans, samples were aligned to the combined transcriptome as described above and RSEM was used to calculate TPM. Results: We were able to simultaneously measure the host and fungal pathogen transcriptional profiles of four distinct infection fates during macrophage and Candida albicans interactions Conclusions: Our study represents an analysis of both distinct infection populations of macrophages and fungus.

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Host-pathogen dynamics through targeted secretome analysis of stimulated macrophages.

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