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Data · dataset · 2026

Investigating the antimicrobial efficacy of mesenchymal stromal cells as a novel potential therapy for Mycobacterium avium pulmonary infection

Listed in ZivaHub and Deakin Research Online and DMU Figshare and UCL Research Data Repository — shown once because both records carry DOI 10.17034/32633382.v1

Non-tuberculous mycobacteria (NTM) are an emerging group of drug-resistant and opportunistic pathogens.

Description

Case numbers of non-tuberculous mycobacterial pulmonary disease (NTM-PD) are rising rapidly around the world, particularly in high-income countries. There is a growing cohort of susceptible patients, typically with pre-existing lung disease and/or impaired immunity, for whom NTM-PD carries a poor prognosis.

Mycobacterium avium complex (MAC) is the leading bacterial cause and survives by subverting lung macrophages in susceptible patients. Current treatment strategies are unsatisfactory, consisting of protracted courses of multiple antimicrobial drugs which are poorly tolerated and carry a high failure rate of 40-60% within 5 years. <br> <br>Three research priorities that are regarded as important to improving outcomes for patients with NTM-PD and are the focus of this thesis: <br><br>1) detailed epidemiological characterisation <br><br>2) clinically-relevant disease modelling <br><br>3) novel therapeutic strategies <br> <br>Chapter 3 describes the epidemiological profile of NTM-PD in Northern Ireland.

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NTM isolates from patient specimens has risen more than 3-fold in the last 12 years. This is driven by the isolation of MAC from the pulmonary specimens of older people, particularly males over 50 years old. These findings warrant urgent attention into improving the recognition of NTM-PD in at-risk patients <br> <br>Chapter 4 describes the characterisation of a clinically-relevant in vitro model of MAC infection using primary human macrophages (monocyte-derived macrophages, MDMs).

Important outcomes such as bacterial uptake, intracellular proliferation, pro-inflammatory cytokine response are variably dependent on macrophage donor and multiplicity of infection (MOI). An MOI of 1 appears to achieve a rate of bacterial uptake that correlates with significant levels of intracellular proliferation and pro-inflammatory cytokine response, but without significant cytotoxicity. Yet, there remain further variations in bacterial uptake and proliferation between MAC strains (laboratory and clinical strains) which will necessitate the use of multiple strains in testing candidate therapies <br><br>The focus of the thesis is reporting the testing of mesenchymal stromal cells (MSCs) in cellular (chapter 5) and animal (chapter 6) models of MAC-PD.

MSCs) have antimicrobial and immunomodulatory properties that are being investigated for many infectious diseases, but their potential in MAC infection remains unknown. I hypothesised that MSCs can directly kill MAC, and/or promote their clearance by macrophages. <br><br>MSCs had no direct activity against MAC but inhibited their intracellular growth in human MDMs by 30% over 72 hours (p<0.05). This activity was dependent on MSC COX-2 activity and mediated through MSC secretion of PGE2.

Activation of PI3K in infected MDMs by MSC PGE2 appeared to be important for inhibiting intracellular growth for some but not all donors. Two doses of 1 million human bone marrow MSCs reduced pulmonary counts of MAC in mice with chronic infection by 20% (p<0.05) but did not reduce bacterial dissemination to liver and spleen. <br><br>These findings warrant further investigation into the downstream mechanisms of MSCs in promoting macrophage activity against intracellular MAC.

I discuss the next steps required to prepare MSCs for human trials as a potential adjunct therapy for MAC pulmonary disease. <br> <br>

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Inferred from text
Disease 75%
Provenance · 4 source records, 21 field assertions
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Deakin Research Onlineoai:figshare.com:article/3263338213 d agoJSON v1
DMU Figshareoai:figshare.com:article/3263338213 d agoJSON v1
UCL Research Data Repositoryoai:figshare.com:article/3263338213 d agoJSON v1
FieldAssertionExtractorEvidence
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