# Pathogen and Microbiome Temporal Changes During Resolution of HAP

> **NIH NIH U19** · NORTHWESTERN UNIVERSITY · 2022 · $355,842

## Abstract

Project Summary Project 2: Pathogen and Microbiome Temporal Changes During Resolution of HAP
Severe pneumonia is a dreaded complication among mechanically ventilated patients and is associated with
high rates of mortality. To better understand these challenging infections, we propose to develop the Successful
Clinical Response In Pneumonia Therapy (SCRIPT) Systems Biology Center. The overall goal of SCRIPT
Research Project 2 is to create a computational model based on microbial biosignatures that predicts clinical
failure in patients with ventilator-associated pneumonia. Specific pathogens such as Pseudomonas aeruginosa
and Acinetobacter baumannii are particularly problematic in ventilator-associated pneumonia and are associated
with clinical failure rates as high as 50%, even in patients treated with appropriate antibiotic therapy. For this
reason, we will focus on pneumonia caused by these pathogens. Work from our group and others has shown
that strains of these bacteria differ dramatically in their ability to cause severe infections. Furthermore, emerging
evidence indicates that alterations in the pulmonary microbiome induced by pathogens or by the antibiotics used
to treat them may contribute to poor clinical outcomes. We hypothesize that specific genetic biosignatures of P.
aeruginosa and Acinetobacter baumannii and other spp. and particular alterations to the pulmonary microbiome
are associated with clinical failure in patients with HAP. To test this hypothesis, we will perform the following
aims: Aim 1. We will identify genetic biosignatures of P. aeruginosa and A. baumannii strains associated with
poor clinical responses in patients with severe pneumonia. Aim 2. We will identify pulmonary microbiome
constituents (bacteria, viruses, and fungi) and longitudinal microbiome patterns associated with poor clinical
responses in patients with severe pneumonia. Aim 3. Generate a computational model that integrates pathogen
genome, pathogen transcriptome, and microbiome components to predict the clinical response in severe
pneumonia caused by P. aeruginosa or A. baumannii. The data we generate will be used in an iterative manner
to create and optimize a computational model that identifies patients at risk for clinical failure based upon the
microbiology of their pneumonia. Highly discriminatory microbiological biosignatures for clinical failure will be
further examined to determine whether they play a causal role in the progression of pneumonia.

## Key facts

- **NIH application ID:** 10326815
- **Project number:** 5U19AI135964-05
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** ALAN R HAUSER
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $355,842
- **Award type:** 5
- **Project period:** 2018-01-17 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10326815

## Citation

> US National Institutes of Health, RePORTER application 10326815, Pathogen and Microbiome Temporal Changes During Resolution of HAP (5U19AI135964-05). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10326815. Licensed CC0.

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