Investigating Metabolic and Molecular Ecological Evolution of Opportunistic Pulmonary Fungal Coinfections: Protocol for a Laboratory-Based Cross-Sectional Study (Preprint)

• DOI: 10.2196/preprints.48014
• Publication Date: 2023-05-03T22:02:52Z
• Authors: Israel Kiiza Njovu; Pauline Petra Nal...; Lucas Ampaire; Edwin Nuwagira; James Mwesigye; Benson Musinguzi; Kennedy Kassaza; Kabanda Taseera; James Kiguli Mukasa; Joel Bazira; Jacob Stanley Ira...; Andrew Baguma; Felix Bongomin; Richard Kwizera; Beatrice Achan; Michael J Cox; Jason S King; Robin May; Elizabeth R Ballou; Herbert Itabangi
• Keywords: 16. Peace & justice; 3. Good health

<sec> <title>BACKGROUND</title> Fungal-bacterial cocolonization and coinfections pose an emerging challenge among patients suspected of having pulmonary tuberculosis (PTB); however, the underlying pathogenic mechanisms microbiome interactions are poorly understood. Understanding how environmental microbes, such as fungi bacteria, coevolve develop traits to evade host immune responses resist treatment is critical controlling opportunistic fungal coinfections. In this project, we propose study coexistence bacterial microbial communities during chronic diseases, with a keen interest in underpinning etiological evolution predominating that may exist between bacteria. </sec> <title>OBJECTIVE</title> This protocol for aimed at investigating metabolic molecular ecological through determining characterizing burden, profiles, communities, established bacteria implicated presumptive PTB. <title>METHODS</title> will be laboratory-based cross-sectional study, sample size 406 participants. From each participant, 2 sputa samples (one on-spot one early morning) collected. These then analyzed both etiology using conventional (intergenic transcribed spacer 16S ribosomal DNA–based polymerase chain reaction) approaches. We also attempt design genome-scale model analyze composition entire (ie, bacteria) investigate host-microbial under different patient conditions. analysis based on interplays genes (identified by metagenomics) inferred from amplicon data metabolites metabolomics) analyzing full set specific computational tools. collect baseline data, including demographic clinical history, patient-reported questionnaire. Altogether, approach contribute diagnostic-based observational study. The primary outcome overall diagnostic profile Other factors associated profile, incidence prevalence, univariate multivariate schemes. Odds ratios 95% CIs presented statistical significance &lt;i&gt;P&lt;/i&gt;&amp;lt;.05. <title>RESULTS</title> has been approved Mbarara University Research Ethic Committee (MUREC1/7-07/09/20) Uganda National Council Science Technology (HS1233ES). Following careful scrutiny, was designed enable enrollment, which began March 2022 Teaching Hospital. Data collection ongoing expected completed August 2023, manuscripts submitted publication thereafter. <title>CONCLUSIONS</title> Through protocol, explore Establishing key fungal-bacterial cross-kingdom synergistic relationships crucial instituting coinfecting etiology. <title>CLINICALTRIAL</title> ISRCTN Registry ISRCTN33572982; https://tinyurl.com/caa2nw69 <title>INTERNATIONAL REGISTERED REPORT</title> DERR1-10.2196/48014