MULTI-OMICS DATA INTEGRATION APPROACH TO IDENTIFY ATTRACTIVE DRUG TARGETS IN LISTERIA MONOCYTOGENES

PALUMBO MIRANDA; SOSA EZEQUIEL; SERRAL FEDERICO; CASTELLO FLORENCIA; GUSTAVO SCHOTTLENDER; GORDILLO TANIA; BOCKOR SABRINA; MARÍA MERCEDES PALOMINO; DARÍO FERNANDEZ DO PORTO

Congreso; XVII Congreso Argentino de Microbiología General; 2022

Listeria monocytogenes (Lm) is a foodborne pathogen responsible for listeriosis in humans. Recently,Lm has developed resistances to a broad range of antimicrobials, including those used as the firstchoice of therapy. Moreover, multidrug-resistant strains have been detected in clinical isolates andfood processing environments. This punctuates the need for novel antimicrobials against Lm. On theother hand, increasingly available omics data has created new opportunities for rational drugdiscovery. In this work, we generated multiple layers of omics data related to Lm, aiming to prioritizeproteins that could serve as potential targets for antibiotic drug discovery. In order to determine thestructural druggability of each protein encoded in Lm genome, experimental structures were retrievedfrom the Protein Data Bank (PDB). For all remaining proteins, we predicted their structure byhomology modeling. Fpocket allowed the detection of protein cavities capable of interacting withdrug-like compounds. Afterwards, Lm proteome was used as a query in BLASTp against human andmicrobiome proteins to avoid possible cross-interference. An essentiality analysis was also performedby looking for orthologs in DEG. The degree of conservation of each protein was determined byperforming a multiple genome alignment of 25 Lm strains. Additionally, Lm metabolic network wasbuilt using Pathway Tools and analyzed as a reaction graph with Cytoscape, allowing the calculationof topological metrics. Finally, we included some previously published work that used microarraysanalysis for gene expression from relevant conditions: intracellular replication in macrophages,intestinal lumen and blood. We combined this data in Target Pathogen in order to identify and prioritize attractive drug targets. Out of 2867 Lm proteins, we obtained 1925 structures. As expected,98,5% of the structures modeled from a template co-crystallized with a drug-like compound werepredicted as druggable. A total of 434 essential, druggable proteins with no close homologs in thehuman genome were kept. Afterward, we ranked these proteins according to a scoring function whichtakes into account the metabolic context, presence/absence in Lm strains, and upregulation duringthe infection-mimicking conditions. The best-ranked protein, transaldolase Tal2, participates in thePentose Phosphate Pathway (PPP). The second one, rhamnulose-1-phosphate aldolase (RhaD), isimplicated in the rhamnose utilization pathway. Other proteins in this pathway, such asrhamnulokinase (RhaB) and rhamnose mutarotase (RhaM) also harbor many features that make PPPan attractive target. We developed and applied an integrative analysis framework for the prioritizationof protein targets in Lm. With our approach, pentose and rhamnose metabolism emerge as interestingpotential targets for future drug development works.