• Research

Regulation of autophagy by Salmonella

A combined computational and wet lab approach to understand how Salmonella is controlling our cells in the gut.

Project summary.

Led by: Korcsmáros Group

Start date: 17 March 2014

Duration: Ongoing

Grant: EI CSP WP2 / QIB Gut Microbes and Health ISP

Our key research aim is to examine how the functions of intestinal cells are compromised as a consequence of autophagy down-regulation, caused by Salmonella infection. Autophagy is a common recycling process in which cells degrade their unnecessary or damaged parts. It is important in the defence against infections, which is why pathogens like Salmonella hijack it. Bacteria such as Salmonella enter gut cells and then aim to avoid those cells’ degradation. A better understanding of how they do it would help us to develop new drugs or treatments for several illnesses.

We develop new bioinformatics resources and combine existing technologies for studying the host response to infection (ARN and SalmoNet). We identify human gut cell autophagy proteins whose quantity changes with Salmonella infection. Using bioinformatics tools and resources we search for the affected proteins’ associated regulators, and test the likely candidates in experiments. Rather than experiment with actual human gut, we use cell culture, organ cultures (‘organoids’), which are near-physiological 3D model systems that facilitate studying a range of in vivo biological processes including cell differentiation, anti-microbial peptide production, and host-microbe interactions.

The validated autophagy regulators affected by Salmonella could enable drug development projects of pharmaceutical companies to design novel drugs against Salmonella infection (which is the second most common cause of childhood mortality in the developing world), and the list of Salmonella-affected proteins can be used to develop gut health promoting treatments and personalised medicine-based strategies to identify risk for certain diseases.

Details.

In the last decade, network representation has allowed us to identify essential molecules at the systems-level. It has also furthered our understanding of how changes in cellular processes can lead to complex diseases, such as inflammatory bowel disease (IBD) and cancer. Many changes have apparent pro- or anti-disease effects but there are some processes for which the effect is not that clear. One of them is autophagy, a cellular degradation process. Autophagy is known to be important in stress responses, regulation of inflammation, and intestinal homeostasis, including the elimination of intracellular pathogens. Conversely, autophagy is often hijacked or manipulated by intestinal pathogenic bacteria, such as Salmonella. A better understanding the effect of certain bacterial species on the regulation of human intestinal autophagy could help us to propose IBD and colon cancer prognosis markers.

Autophagy is a complex cellular process and its major post-translational regulators are well known, however, they have not yet been collected comprehensively. The precise and context dependent regulation of autophagy necessitates additional regulators, including transcriptional and post-transcriptional components that are listed in various datasets. Prompted by the lack of systems-level autophagy-related information, we developed an online resource, Autophagy Regulatory Network (ARN), to provide an integrated database for autophagy research. ARN contains manually curated, imported and predicted interactions of autophagy components in humans. We listed transcription factors and miRNAs that could regulate autophagy components or their protein regulators.

The user-friendly website of ARN allows researchers without computational background to search, browse and download the database. The database can be downloaded in various file formats. ARN has the potential to facilitate the experimental validation of novel autophagy components and regulators. In addition, ARN helps the investigation of transcription factors, miRNAs and signaling pathways implicated in the control of the autophagic pathway.

To investigate how Salmonella is modulating autophagy we developed SalmoNet, the first large-scale network resource for Salmonella enterica, integrating known and predicted regulatory, metabolic and signalling interactions (http://SalmoNet.org). Then, we integrated earlier identified Salmonella-host interactions and data from ARN to list and predict novel genes responsible for autophagy modulation in the gut. With network analysis and literature mining, we select Salmonella-host interactions for experimental validation in gut organoid models.

To validate the pathogen-host interactions - predicted through the combination of these network resources -, we are doing in vitro (cell cultures or organoids) and in vivo (mice) invasion assays with Salmonella. We are sorting the generated samples by FACS, and using the extracted RNA to measure the gene expression and hence compare for example infected vs. non-infected cells or cells infected with different strains of Salmonella by qPCR or RNAseq.

Tools.

Autophagy Regulatory Network

ARN can be used to examine the autophagy system in humans for both global or for gene-specific studies and will assist researchers in their investigation of the autophagic process. ARN contains manually curated, imported and predicted interactions of autophagy components, their post-translattional, transcriptional and post-transcriptonal regulators (enzymes, transcription factors and microRNAs), and the dataset is available in several community standard file formats.

SalmoNet

SalmoNet combines manual curation, high-throughput data and computational predictions to provide an integrated network for Salmonella at the transcriptional regulatory, metabolic and protein-protein interaction levels. SalmoNet provides the networks separately for five gastro-intestinal and five extra-intestinal strains. SalmoNet as a multi-layered, multi-strain database containing experimental data is the first dedicated network resource for Salmonella

Publications.

Targeted interplay between bacterial pathogens and host autophagy

Sudhakar P, Claire-Jacomin A, Hautefort I, Samavedam S, Fatemian K, Ari E, Gul L, Demeter A, Jones E, Korcsmaros T and Nezis I. P. (Autophagy in Press)

What We Learned From Big Data for Autophagy Research. 

Claire-Jacomin A, Gul L,  Sudhakar P, Nezis I. P, Korcsmaros T. (Front. Cell Dev. Biol.)

Network biology approaches to identify molecular and systems-level differences between Salmonella pathovars.

Olbei M, Korcsmaros T, Sudhakar P. Book chapter. In Press 2018/2019. Food Pathogens. (Springer Publishers)

Technology used.

The transcriptomics and miRNA analysis of the organoid samples are being carried out with EI's Genomics Pipelines group. We used the HPC cluster to predict the transcriptional regulatory networks of Salmonella strains.

Collaborators.

Robert A. Kingsley

QIB - collaborator in the development of SalmoNet and in the validation of Salmonella-autophagy connections.

Jozsef Baranyi

QIB - collaborator in the development of SalmoNet.

Tom Wileman

QIB/UEA - collaborator in the organoid works for the validation of Salmonella-autophagy connections.

Alastair Watson

UEA - collaborator in the validation of Salmonella-autophagy connections and the transcriptomic analysis of mice infected with Salmonella.

Devina Divekar

UEA - collaborator in the validation of Salmonella-autophagy connections and the transcriptomic analysis of mice infected with Salmonella.

Ioannis Nezis

University of Warwick - collaborator working on the role of autophagy in developmental mechanisms and selective autophagy.

Impact statement.

With this project we will identify the systems level, dynamic relationship between a gut pathogen, Salmonella and a host defense mechanism, autophagy. The complex interplay between Salmonella and autophagy has been investigated in the last two decades, providing a substantial amount of data for this project. We will advance our understanding by investigating the multi-scale nature of the Salmonella-autophagy connection, focusing specifically on pathways in intestinal cells and the homeostasis of the gut.

Throughout the project, we iteratively combine state-of-the-art and novel computational and experimental methods (network analysis and organoid infection works) and build on existing in silico and wet lab resources. The results will extend our understanding of Salmonella infection (from causing mild food poisoning to life-threatening gastrointestinal diseases in humans and animal livestock) and the role of intestinal cells during infection and, in general, to the maintenance of gut homeostasis.

Related reading.