Friday, June 27, 2025 6/27/2025

Single-cell genomic profiling to identify immune signatures of bacterial sepsis in humans

Award Number: R01AI153142
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 03/03/2021
PERIOD OF PERFORMANCE END DATE: 02/28/2026

Group Awards By:

View Award Description

Single-cell genomic profiling to identify immune signatures of bacterial sepsis in humans - Sepsis, life-threatening organ dysfunction due to a dysregulated host response to infection, is prevalent and highly lethal. Early detection is a major challenge, largely because, as we and others showed, sepsis is a heterogeneous syndrome, with many patients presenting with vague symptoms and signs; improved biomarkers would enable earlier diagnosis, especially of these patients. A second major challenge is the shortage of treatments, as mechanisms of immune dysfunction and vascular leakage in sepsis are poorly understood, limiting therapeutic development. We hypothesize that unbiased single-cell transcriptional profiling (scRNA-seq) of circulating immune cells will identify transcriptional signatures that address both challenges. In our proof-of- principle study (Reyes et al. Nat Med 2020), we discovered a unique monocyte cell state (MS1) that is expanded in patients with urosepsis and absent in patients with milder urinary tract infection or healthy controls. MS1 discriminates septic patients from patients with other diseases in public transcriptomic data, in a second cohort of bacterial sepsis, and in preliminary data from our new cohort of patients with sepsis from any body site. Our goals in this proposal are to test the hypothesis that when extended to patients with sepsis from all body sites, unbiased single-cell approaches will generate immune signatures that distinguish sepsis from non-infectious organ dysfunction, define new clinically-relevant sepsis endotypes, identify markers that enhance sepsis diagnostics and subtyping, and reveal critical mechanistic biology underlying the immune dysfunction and vascular leak present in sepsis, thus facilitating future development of endotype-specific therapeutics. In this proposal, we will test our hypothesis that among patients presenting to the ED with acute organ dysfunction, transcriptional signatures can be identified that distinguish those with sepsis from those with non-infectious etiologies. We propose to: (1) discover blood single-cell transcriptional signatures that discriminate sepsis from non-infectious organ dysfunction, define unbiased molecular endotypes, and associate with clinical outcomes (Aim 1); (2) identify cell surface markers associated with scRNA-seq-defined cell states, including MS1, that are significantly expanded in sepsis (Aim 2); (3) define alterations in cellular functions in patients and mice with sepsis and in response to sepsis-induced MS1 cells (Aim 3). The proposed studies are highly likely to lead to substantially improved cellular and molecular signatures for sepsis that could be translated into clinical use and to new insights into the nature of immune dysregulation in sepsis. Investigations into the function of genes and pathways identified in our studies will impact mechanistic understanding of sepsis and may lead to new therapeutic concepts, especially for subsets of sepsis patients stratified based on single cell-derived molecular endotypes. Whereas sepsis remains among of the most challenging problems in human health, our use of a high-resolution unbiased approaches to address the major questions of heterogeneity and mechanism will provide highly useful datasets for the field and promote the development of new targeted therapeutics.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $970,158 )
2025	2025	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Allergy and Infectious Diseases Research	000	5	2/13/2025	NON-COMPETING CONTINUATION	$970,158
														Subtotal = $970,158

Issue Date FY: 2024 ( Subtotal = $1,012,832 )
2024	2024	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Allergy and Infectious Diseases Research	000	4	2/1/2024	NON-COMPETING CONTINUATION	$911,551
2024	2024	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Allergy and Infectious Diseases Research	001	4	5/31/2024	NON-COMPETING CONTINUATION	$101,281
														Subtotal = $1,012,832

Issue Date FY: 2023 ( Subtotal = $939,914 )
2023	2023	THE GENERAL HOSPITAL CORPORATION	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Allergy and Infectious Diseases Research	000	3	2/24/2023	NON-COMPETING CONTINUATION	$939,914
														Subtotal = $939,914

Issue Date FY: 2022 ( Subtotal = $1,019,588 )
2022	2022	MASSACHUSETTS GENERAL HOSPITAL, THE	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Allergy and Infectious Diseases Research	000	2	2/10/2022	NON-COMPETING CONTINUATION	$1,019,588
														Subtotal = $1,019,588

Issue Date FY: 2021 ( Subtotal = $1,014,363 )
2021	2021	MASSACHUSETTS GENERAL HOSPITAL, THE	55 FRUIT ST	BOSTON	MA	02114	SUFFOLK	USA	Allergy and Infectious Diseases Research	000	1	3/3/2021	NEW	$1,014,363
														Subtotal = $1,014,363

Grand Total All Awards = $4,956,855

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Single-cell genomic profiling to identify immune signatures of bacterial sepsis in humans

Award Number: R01AI153142

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 03/03/2021

PERIOD OF PERFORMANCE END DATE: 02/28/2026

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer