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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiomes</journal-id>
<journal-title>Frontiers in Microbiomes</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiomes</abbrev-journal-title>
<issn pub-type="epub">2813-4338</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/frmbi.2023.1123064</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Microbiomes</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Gut microbiome variation in pulmonary TB patients with diabetes or HIV comorbidities</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Morgan</surname><given-names>Portia Abena</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1516025"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Parbie</surname><given-names>Prince Kofi</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/469010"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Ntiamoah</surname><given-names>Desmond Opoku</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2219423"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Boadu</surname><given-names>Augustine Asare</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Asare</surname><given-names>Prince</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/884714"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lamptey</surname><given-names>Ivy Naa Koshie</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Gorman</surname><given-names>Cecilia Nancy</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Afreh</surname><given-names>Emmanuel</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Asante-Poku</surname><given-names>Adwoa</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/891085"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Otchere</surname><given-names>Isaac Darko</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn001"><sup>*</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/637753"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Aboagye</surname><given-names>Sammy Yaw</given-names>
</name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1145947"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Yeboah-Manu</surname><given-names>Dorothy</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/479427"/>
</contrib>
</contrib-group>
<aff id="aff1"><sup>1</sup><institution>Department of Bacteriology, Noguchi Memorial Institute for Medical Research, University of Ghana</institution>, <addr-line>Accra</addr-line>, <country>Ghana</country></aff>
<aff id="aff2"><sup>2</sup><institution>West African Center for Cell Biology of Infectious Pathogens, University of Ghana</institution>, <addr-line>Accra</addr-line>, <country>Ghana</country></aff>
<aff id="aff3"><sup>3</sup><institution>AIDS Research Center, National Institute of Infectious Diseases</institution>, <addr-line>Tokyo</addr-line>, <country>Japan</country></aff>
<aff id="aff4"><sup>4</sup><institution>Rush University Medical Center, Department of Microbial Pathogens and Immunity</institution>, <addr-line>Chicago, IL</addr-line>, <country>United States</country></aff>
<aff id="aff5"><sup>5</sup><institution>Institute for Environment and Sanitation Studies, University of Ghana</institution>, <addr-line>Accra</addr-line>, <country>Ghana</country></aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Vineet K. Sharma, Indian Institute of Science Education and Research, India</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Abhijit Maji, University of Texas Southwestern Medical Center, United States; Tarini Shankar Ghosh, University College Cork, Ireland</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Isaac Darko Otchere, <email xlink:href="mailto:idotchere@gmail.com">idotchere@gmail.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Host and Microbe Associations, a section of the journal Frontiers in Microbiomes</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>15</day>
<month>03</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>2</volume>
<elocation-id>1123064</elocation-id>
<history>
<date date-type="received">
<day>13</day>
<month>12</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>28</day>
<month>02</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Morgan, Parbie, Ntiamoah, Boadu, Asare, Lamptey, Gorman, Afreh, Asante-Poku, Otchere, Aboagye and Yeboah-Manu</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Morgan, Parbie, Ntiamoah, Boadu, Asare, Lamptey, Gorman, Afreh, Asante-Poku, Otchere, Aboagye and Yeboah-Manu</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>The gut microbiota is known to play a critical role in shaping the host immunity, and metabolism and influences the onset and progression of both communicable and non-communicable diseases. This study assessed the gut microbiome of tuberculosis (TB) cases with diabetes mellitus (DM) or HIV comorbidities before anti-TB therapy and after the intensive phase anti-TB therapy.</p>
</sec>
<sec>
<title>Methods</title>
<p>Ninety cases comprising 60 TB-only, 23 TB-DM, 7 TB-HIV were recruited, among which 35 TB-only, 10 TB-DM, 5 TB-HIV were also sampled after 2 months of anti-TB treatment. Total gut microbiome was detected by 16S rRNA gene sequencing of DNA extracted from collected stool specimen. The taxonomic and functional diversity of the different groups were compared in addition to changes that could occur after 2 months antibiotics use.</p>
</sec>
<sec>
<title>Results</title>
<p>Compared to the healthy controls, the gut microbiome of all the TB cohorts was characterized by a significant decreased alpha diversity and significant compositional changes. All the three TB cohorts were enriched with inflammatory related microorganisms of the genera <italic>Escherichia-shigella</italic>, <italic>Streptococcus</italic>, <italic>Enterococcus</italic> and <italic>Erysipelatoclostridium</italic> with depletion in beneficial taxa of the genera <italic>Faecalibacterium</italic>, <italic>Bifidobacterium</italic> and <italic>Clostridium</italic>. In pairwise comparison with the healthy controls, the TB-only cohort were enriched with <italic>Streptococcus</italic> and <italic>Erysipelatoclostridium</italic>, the TB-DM enriched with <italic>Bacteroides</italic>, and TB-HIV enriched with <italic>Escherichia-shigella, Dialister</italic> and <italic>Erysipelatoclostridium</italic>. After the intensive phase anti-TB therapy, there was general enrichment of the genera <italic>Erysipelotrichaceae_</italic>UCG 003<italic>, Veillonella</italic> and <italic>Fusobacterium</italic>.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Our findings show a dysbiotic gut microbiome and associated upregulation of inflammation related microorganism in gut microbiome of TB individuals with or without comorbidity.</p>
</sec>
</abstract>
<kwd-group>
<kwd>tuberculosis</kwd>
<kwd>diabetes</kwd>
<kwd>HIV/AIDS (acquired immunodeficiency syndrome)</kwd>
<kwd>comorbidity</kwd>
<kwd>coinfection</kwd>
<kwd>microbiome</kwd>
</kwd-group>
<counts>
<fig-count count="9"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="78"/>
<page-count count="13"/>
<word-count count="4850"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Tuberculosis (TB), caused by the <italic>Mycobacterium tuberculosis</italic> complex (MTBC) is an ancient disease and the 13<sup>th</sup> cause of death globally (<xref ref-type="bibr" rid="B72">WHO, 2021</xref>). Only about 5 -10% of infected individuals progress to active TB disease in their lifetime; identified risk factors that may hasten progression to diseases (<xref ref-type="bibr" rid="B22">Flynn and Chan, 2001</xref>) include malnutrition, excessive alcohol consumption, smoking, HIV- coinfection, and diabetes mellitus (DM) (<xref ref-type="bibr" rid="B50">Narasimhan et&#xa0;al., 2013</xref>). According to the 2021 global TB report, among the 10 million new infections recorded, 8.2% were coinfected with HIV whereas 16% were comorbid with DM (<xref ref-type="bibr" rid="B72">WHO, 2021</xref>).</p>
<p>The gut microbiome, described as the last organ of the human body due to specific biochemical interaction and systemic integration with the host, comprises all microbial community and their genes inhabitant in the gut (<xref ref-type="bibr" rid="B16">Dumas et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B35">Kim and Benayoun, 2020</xref>). Gut microbes perform immunomodulatory role by sending out signals that promote immune cell maturation, influencing infection risks and disease progression (<xref ref-type="bibr" rid="B42">Maji et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B30">Hu et&#xa0;al., 2019</xref>). Short chain fatty acids (SCFA) produced by some of the normal flora of the gut (<xref ref-type="bibr" rid="B43">Makki et&#xa0;al., 2018</xref>) supports maintenance of intestinal barrier integrity and guard the host against infection and colorectal cancer (<xref ref-type="bibr" rid="B55">Peng et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B38">Lewis et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B3">Besten et&#xa0;al., 2013</xref>). The interaction between the gut microbes and the immune system is extremely homeostatic and carefully regulated such that in a disturbed and dysbiotic state the host immunity is negatively impacted (<xref ref-type="bibr" rid="B28">Honda and Littman, 2016</xref>).</p>
<p>The gut microbiota also influences distal organs such as the lungs through the gut-lung axis; early life gut depletion in <italic>Faecalibacterium</italic>, <italic>Lachnospira</italic>, and <italic>Rothia</italic> has been linked to asthma in humans (<xref ref-type="bibr" rid="B2">Barcik et&#xa0;al., 2020</xref>). Also, the gut microbiota has been shown to boost respiratory defenses through signaling granulocyte-macrophage colony-stimulating factor (GM-CSF), which accelerates pathogen clearance by alveolar macrophages <italic>via</italic> extracellular signal-regulated kinase signaling (<xref ref-type="bibr" rid="B7">Brown et&#xa0;al., 2017</xref>). Gut dysbiosis due to infections and/or use of antimicrobials damages this gut related host response predisposing the host to illness (<xref ref-type="bibr" rid="B65">Sood et&#xa0;al., 2018</xref>). Drug susceptible TB treatment includes narrow acting Isoniazid (H), Pyrazinamide (Z), Ethambutol (E) and broad-spectrum Rifampicin (R), (collectively termed (HZRE)), acts against a wide range of gram positive and negative organisms (<xref ref-type="bibr" rid="B13">Diallo et&#xa0;al., 2021</xref>). TB treatment is considered one of the longest antibiotic regimen globally taking a minimum of six months comprising an intensive 2-months (HRZE) phase and a continuous 4-months phase of H and R (<xref ref-type="bibr" rid="B9">CDC, 2016</xref>). The interplay between TB and other comorbidities such as DM and HIV infection and their impact of the gut microbiome remains unclear, also the specific effects of multiple antimicrobials in both comorbid and non-comorbid.</p>
<p>In this study, we analyzed the variation in gut microbiome of TB patients with and without comorbidities of either HIV or DM before the start of anti-TB therapy and after the month-2 intensive phase of TB therapy. The taxonomic and functional diversity of gut microbiome of the analyzed groups were compared in addition to changes that could occur after 2 months antibiotic use in TB patients.</p>
</sec>
<sec id="s2">
<title>Methods</title>
<sec id="s2_1">
<title>Ethics</title>
<p>Ethical clearance for the study and its protocols was obtained from the Institutional Review Board (IRB) of the Noguchi Memorial Institute for Medical Research (NMIMR), University of Ghana (Federal wide assurance number: FWA00001824) and the Ethics Review Committee of the Korle-Bu Teaching Hospital. Informed written consent was obtained from all participants and their respective families.</p>
</sec>
<sec id="s2_2">
<title>Study participants and sample collection</title>
<p>Gene Xpert MTB-RIF (Cepheid, USA) and chest X-ray confirmed pulmonary TB patients from a tertiary facility and a Regional Hospital in Ghana were recruited for the study. Demographic and clinical data including age, sex, history of TB, TB bacterial load, alcohol and cigarette use, previous medication and other underlining conditions were recorded using a structured questionnaire. Healthy close household contacts for healthy controls (HC) included non-active TB, non-HIV infected, and non-diabetic adults from the same household of the cases. TB confirmed participants were screened at baseline for diabetes (fasting blood sugar above 7mmol/L and HbA1c confirmatory test above 6%) and HIV ((positive rapid First Response HIV1-2.0 card test, Premier Medical Cooperation Limited, India) &amp; positive confirmatory OraQuick rapid test (OraSure Technologies, USA)) after which stool samples were collected following standard procedures (<xref ref-type="bibr" rid="B68">Thomas et&#xa0;al., 2015</xref>). A second sample was collected 2 months after the intensive phase of anti-TB therapy (follow-up) from the case participants, whereas a one-time point sample was collected from the HC. At month 2 follow-up, sputum conversion was examined by microscopy. Only pulmonary TB patients above 18 years were enrolled in this study. Extrapulmonary TB cases and treatment defaulters were excluded from the study.</p>
</sec>
<sec id="s2_3">
<title>Amplification and 16SrRNA gene sequencing</title>
<p>Fresh stool samples (2.0 ml/aliquot) were frozen and stored at -80&#xb0;C prior to extraction. Microbial DNA from fecal samples was extracted using QIAGEN DNeasy PowerLyzer Power Soil kit (QIAGEN, USA) per manufacturer&#x2019;s instructions. The captured DNA was then washed and eluted from the membrane and stored at 4&#xb0;C for downstream analysis.</p>
<p>The V3 and V4 region of the bacterial 16S ribosomal RNA (rRNA) gene was amplified by PCR using the primers (16S rRNA_V3. V4-F 5&#x2019;- ACACGACGCTCTTCCGATCT CCTACGGNGGWG -3&#x2019; and V3. V4-R 5&#x2019;- GACGTGTGCTCTTCCGATCT GACTACHVGGTATCTAATCC -3&#x2019;). PCR reactions were performed using Roche&#xae; (Roche Sequencing Solutions, USA). Amplicons with the desired 450bp size after gel electrophoresis were purified and sequenced by the Illumina Miseq (<xref ref-type="bibr" rid="B31">Illumina, n.d</xref>). Using MiSeq reagents V3 &amp; V4, 16S library preparation was performed based on Nextera XT DNA library Preparation kits (Illumina Inc, Hayward, CA, USA) (<xref ref-type="bibr" rid="B31">Illumina, n.d</xref>). Amplification of variable region 3 &amp; 4 (V3&amp;V4) of the 16S rRNA, barcoding, and pulling of amplicons were performed per manufacturer&#x2019;s instructions (<xref ref-type="bibr" rid="B48">Muinck et&#xa0;al., 2017</xref>).</p>
</sec>
<sec id="s2_4">
<title>Data analysis</title>
<p>The Quantitative Insights into Microbial Ecology 2 (QIIME 2 version 2021.8) (<xref ref-type="bibr" rid="B5">Bolyen et&#xa0;al., 2019</xref>) was used to quality filter, denoise and analyze the sequences (available at the NCBI Sequence Read Archive (SRA) with study ID PRJNA876282). Demultiplexed paired-end sequence reads were denoised with DADA2 into amplicon sequence variants (ASV). Samples with &lt; 10,000 total reads were excluded from downstream analyses. Feature table and feature data summaries were generated to determine the sequence distribution per sample as well as &#x3b1;-diversity (abundance of ASV within a sample) and &#x3b2;-diversity (microbial composition between samples) analysis of the samples. Taxonomic classifications were performed using Na&#xef;ve Bayesian classifier (<xref ref-type="bibr" rid="B77">Ziemski et&#xa0;al., 2021</xref>) against the SILVA database release 138 (<xref ref-type="bibr" rid="B46">McLaren, 2020</xref>) trimmed to the V3-V4 region of the 16S rRNA gene.</p>
<p>Differentially abundant taxa were identified using the linear discriminant analysis (LDA) effect size (LEfSe) (<xref ref-type="bibr" rid="B60">Segata et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B45">Mandal et&#xa0;al., 2015</xref>). To study the predictive functions of the gut microbiome, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) (<xref ref-type="bibr" rid="B36">Langille et&#xa0;al., 2013</xref>) was used to determine the predictive microbial metagenome functional abundance from 16S rRNA sequences. Subsequently predicted functional abundance were analyzed with ANOVA-like Differential Expression tool for high throughput sequencing data version 2 (ALDEx2) (<xref ref-type="bibr" rid="B19">Fernandes et&#xa0;al., 2013</xref>) to determine differentially abundant functional pathways. For all differential abundance analyses, rare features were removed by, as previously described (ANCOM II) (<xref ref-type="bibr" rid="B39">Lin and Peddada, 2020</xref>).</p>
<p>Statistical analysis was performed using R 3.6.0 packages and GraphPad Prism version 9.1.1. For categorical variable comparison between groups, Fisher exact test was used and Wilcoxon rank-sum test or Kruskal Wallis test used for continuous variable. Multiple test correction was performed with Benjamini, Krieger and Yekutieli FDR correction. Statistical significance was determined at a <italic>p</italic> value less than 0.05.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Clinical characteristics of participants</title>
<p>Ninety participants made up of 60 TB-only, 23 TB-DM, 7 TB-HIV and 10 healthy controls were recruited into the study, while month-2 samples were collected from only 50 (35 TB-only, 10 TB-DM and 5 TB-HIV) of the primary cases (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>). Seven of the cases died by 2 months after diagnosis with remaining lost to follow-up. The median age of all recruited participants was 42 years (IQR, 28.5-54.5) which was same as that for males, while the median age for females was 43.5 (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). Out of the total baseline cases 83.3% experienced weight loss, 70% had night sweats and chest pain, and 65.5% had extreme cough (<xref ref-type="supplementary-material" rid="ST1"><bold>Supplementary Table&#xa0;1</bold></xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Profile of study population. Stool samples were collected from confirmed TB cases from different cohorts at baseline (60 TB-Only (without HIV/diabetes comorbidities), 23 TB-DM comorbidity, 7 TB-HIV comorbidity). After month 2 HRZE therapy cases included (52 TB-Only, 8 TB-DM, 5 TB-HIV) and 10 Healthy control.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="frmbi-02-1123064-g001.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Biographical and Clinical data of participants.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Parameter</th>
<th valign="top" align="center">Number of Patients</th>
<th valign="top" align="center">Male</th>
<th valign="top" align="center">Female</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Median age</td>
<td valign="top" align="center"/>
<td valign="top" align="center">42</td>
<td valign="top" align="center">43.5</td>
</tr>
<tr>
<td valign="top" align="left">Diabetics<break/>HIV positive</td>
<td valign="top" align="center">23<break/>7</td>
<td valign="top" align="center">18 (78.3%)<break/>5 (71.4%)</td>
<td valign="top" align="center">5 (21.7%)<break/>2 (28.6%)</td>
</tr>
<tr>
<td valign="top" align="left">Total Primary cases<break/>TB &#x2013; Only<break/>TB &#x2013; Diabetes<break/>TB &#x2013; HIV</td>
<td valign="top" align="center">90<break/>60<break/>23<break/>7</td>
<td valign="top" align="center">70 (77.8%)<break/>47 (78.3%)<break/>18 (78.3%)<break/>5 (71.4%)</td>
<td valign="top" align="center">20 (22.2%)<break/>13 (21.7%)<break/>5 (21.7%)<break/>2 (28.6%)</td>
</tr>
<tr>
<td valign="top" align="left">Follow-up cases<break/>TB &#x2013; Only<break/>TB &#x2013; Diabetes<break/>TB &#x2013; HIV<break/>Deceased</td>
<td valign="top" align="center">50<break/>35<break/>10<break/>5<break/>7</td>
<td valign="top" align="center">38 (76%)<break/>27 (77.1%)<break/>8 (80%)<break/>3 (60%)<break/>4 (57%)</td>
<td valign="top" align="center">12 (24%)<break/>8 (22.9%)<break/>2 (20%)<break/>2 (40%)<break/>3 (43%)</td>
</tr>
<tr>
<td valign="top" align="left">Bacterial load (GeneXpert)<break/>High<break/>Medium<break/>Low</td>
<td valign="top" align="center">55<break/>17<break/>18</td>
<td valign="top" align="center">40 (72.7%)<break/>13 (76.5%)<break/>17 (94.4%)</td>
<td valign="top" align="center">15 (27.3%)<break/>4 (23.5%)<break/>1 (5.6%)</td>
</tr>
<tr>
<td valign="top" align="left">Healthy controls<break/>Median age<break/>FBS (below 7mmol/L)</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">3 (30%)<break/>38<break/>3 (100%)</td>
<td valign="top" align="center">7 (70%)<break/>42<break/>7 (100%)</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_2">
<title>Overview of the gut microbiome composition of study participant</title>
<p>In both cases and healthy controls, <italic>Firmicutes</italic> was the most abundant phylum. Among the healthy controls, <italic>Firmicutes</italic> (76.4%) was driven mostly by the class <italic>Clostridia</italic>, and families <italic>Lachinospiraceae</italic> (21%) and <italic>Ruminococcaceae</italic> (16%) (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure 1</bold></xref>, <xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table&#xa0;2</bold></xref>). The most abundant genera in the controls were <italic>Faecalibacterium</italic> (6%), and <italic>Subdoligranulum</italic> (3.6%) of the <italic>Ruminococcaceae</italic> family, <italic>Blautia</italic> (4.8%), and <italic>Agathobacter</italic> (4%) of the family <italic>Lachinospiraceae</italic>, <italic>Bifidobacterium</italic> (4.2%) of the <italic>Actinobacteriota</italic> phylum and <italic>Bifidobacteriaceae</italic> family (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref> and <xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table&#xa0;2</bold></xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Overview of abundant gut microbial taxa in the study. <bold>(A)</bold> Heatmap showing top 20 predominant genera in healthy controls compared to TB patients. Each bar represents the frequencies of abundant genera for each participant in the different groups. Taxa labels are formatted as &#x201c;Family.Genus&#x201d;. <bold>(B)</bold> Taxa bar plot showing top 10 abundant genera in all three TB groups to healthy controls. TB-Only (n=56), TB-DM (n=23), TB-HIV individuals (n=7) and healthy controls (n=10).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="frmbi-02-1123064-g002.tif"/>
</fig>
<p>Among all the three TB cohorts, abundance in the <italic>Firmicutes</italic> was driven by genera <italic>Streptococcus</italic> (&gt;5%), and <italic>Enterococcus</italic> (&gt;5.3%) of the class <italic>Bacilli</italic> whilst abundance in the <italic>Proteobacteria</italic> phylum was driven by <italic>Escherichia-Shigella</italic> (&gt;8.7%) and <italic>Klebsiella</italic> (&gt; 19%) genera of the class <italic>Gammaproteobacteria</italic> and family <italic>Enterobacteriaceae</italic> (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2B</bold></xref> and <xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table&#xa0;2</bold></xref>). Comparison of the 20 most abundant genera revealed great disparity among the TB cohorts and the healthy controls with the genera <italic>Clostridia</italic> UCG-014, <italic>Romboutsia</italic>, <italic>Oscillospiraceae-</italic>UCG-002, <italic>Ruminococcaceae</italic>-CAG-352, <italic>Dorea</italic>, <italic>Collinsella</italic>, <italic>Holdermanella</italic>, and <italic>Lachnospiraceae torques</italic> depleted in all the TB cohorts compared to the healthy controls (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref>).</p>
</sec>
<sec id="s3_3">
<title>Diversity of gut microbiome among the TB cohorts and healthy controls</title>
<p>Analysis of richness using observed features to determine the number of features present within the microbial community showed significantly lower richness (P &lt; 0.01) in all TB cohorts (TB-only, TB-DM, TB-HIV) at baseline than the healthy controls (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3A</bold></xref>). The Shannon index and Faith phylogenetic diversity showed significant reduction (P &lt; 0.01) in alpha diversity in all three baseline study TB cohorts compared to the healthy controls (<xref ref-type="fig" rid="f3"><bold>Figures&#xa0;3B, C</bold></xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Reduced Gut microbiome diversity among TB patients at baseline. <bold>(A)</bold> Observed features <bold>(B)</bold> Shannon diversity <bold>(C)</bold> Faith phylogenetic diversity between all TB cohorts. * = (0.05 - 0.01), ** = (0.001 &#x2013; 0.001), *** = (0.001 &#x2013; 0.0001), **** = (&lt; 0.0001). <bold>(D)</bold> Comparing weighted unifrac distances within groups <bold>(E)</bold> PCoA of weighted Unifrac between all TB cohorts where larger distance between groups indicate great variation between the groups.</p>
</caption>
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</fig>
<p>Assessment of &#x3b2;-diversity by weighted Unifrac revealed significant differences (P &lt; 0.0001) between TB groups and controls (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3D</bold></xref>). Further corroborated by gut microbiome compositional segregation as shown in Principal coordinates of analysis (PCoA) of weighted Unifrac distances (<xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3E</bold></xref>). Among the healthy controls there was no significant difference in diversity and abundance between the males and females using both alpha and beta diversities.</p>
<p>We observed a trend of decreasing alpha diversity after 2 months of HRZE intervention in TB-DM and TB-HIV patient groups compared to baseline respectively, though no significance was detected (<xref ref-type="fig" rid="f4"><bold>Figures&#xa0;4A, B</bold></xref>). Also, Beta diversity analysis showed no significant observable distinction in microbial composition between the groups (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4C</bold></xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Changes in diversity in TB cohorts after 2 months HRZE. <bold>(A)</bold> &#x3b1;-diversity based on Faith phylogenetic diversity and <bold>(B)</bold> Shannon entropy for all TB cohorts at 2-month follow-up after HRZE compared to baseline <bold>(C)</bold> PCoA of weighted Unifrac at month 2.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="frmbi-02-1123064-g004.tif"/>
</fig>
</sec>
<sec id="s3_4">
<title>Gut microbiome composition of specific TB cohorts</title>
<p>In the TB-only cohort, the class <italic>Bacilli</italic> (26.92%) of the phylum <italic>Firmicutes</italic> was significantly abundant, and this was driven by the order <italic>Lactobacillales</italic> (17.4%), family <italic>Stretococcaceae</italic> and genus <italic>Streptococcus</italic> (9.5%) (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5A</bold></xref>). In addition, the genera <italic>Erysipelatoclostridium</italic> and <italic>Gamella</italic> of class <italic>Bacilli</italic> was also abundant (<xref ref-type="fig" rid="f5"><bold>Figures&#xa0;5A, B</bold></xref> and <xref ref-type="supplementary-material" rid="SM2"><bold>Supplementary Figure&#xa0;2</bold></xref>). Among the TB-DM cohort compared to the healthy controls, the family <italic>Bacteriodaceae</italic> and genus <italic>Bacteriodes</italic> (7.5%) was significantly abundant in addition to the genera <italic>Erysipelatoclostridium</italic> and <italic>Lachnoclostridium</italic> of the firmicutes phylum (<xref ref-type="fig" rid="f6"><bold>Figures&#xa0;6A, B</bold></xref>). In the TB-HIV cohort, there was significant abundance of the phylum <italic>Proteobacteria</italic> (28.9%) driven by the class <italic>Gammaproteobacteria</italic> (28.1%), family <italic>Enterobacteriaceae</italic> and genus <italic>Escherichia-Shigella</italic> (8.7%), and <italic>Klebsiella</italic> (19.1%) (<xref ref-type="fig" rid="f7"><bold>Figure&#xa0;7</bold></xref> and <xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table 2</bold></xref>). Also abundant was the <italic>Butyriccoccus</italic>, <italic>Clostridium sensu stricto</italic> and <italic>Romboutsia</italic> genera (<xref ref-type="supplementary-material" rid="SM2"><bold>Supplementary Figure&#xa0;2</bold></xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Difference in abundant taxa at baseline between TB-only and healthy controls determined by Linear discriminate analysis (LDA) effect size (LEfSe) <bold>(A)</bold> Discriminative features detected at 3.6 threshold and alpha of 0.01. P_Phylum, C_Class, O_Order, F_Family, G_Genus <bold>(B)</bold> Cladogram of all TB-only and healthy controls. Features in red and green are differentially abundant in controls and TB-Only patients respectively.</p>
</caption>
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</fig>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Difference in abundant taxa at baseline between TB-DM and healthy controls determined by Linear discriminate analysis (LDA) effect size (LEfSe). <bold>(A)</bold> Discriminative features detected at 3.6 threshold and alpha of 0.01. P_Phylum, C_Class, O_Order, F_Family, G_Genus <bold>(B)</bold> Cladogram of all TB-DM and healthy controls. Features in red and green are differentially abundant in controls and TB-DM patients respectively.</p>
</caption>
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</fig>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Difference in abundant taxa at baseline between TB-HIV and healthy controls determined by Linear discriminate analysis (LDA) effect size (LEfSe). <bold>(A)</bold> Discriminative features detected at 3.6 threshold and alpha of 0.01. P_Phylum, C_Class, O_Order, F_Family, G_Genus <bold>(B)</bold> Cladogram of all TB-DM and healthy controls. Features in red and green are differentially abundant in controls and TB-HIV patients respectively.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="frmbi-02-1123064-g007.tif"/>
</fig>
</sec>
<sec id="s3_5">
<title>Difference in microbial composition after intensive phase anti-TB therapy</title>
<p>Comparison of all the three TB cohorts before the start of TB therapy and after the 2-months intensive phase anti-TB therapy identified abundance of the phylum <italic>Fusobacteriota</italic> driven by the genera <italic>Fusobacterium</italic> of the family <italic>Fusobacteriaceae</italic> (<xref ref-type="fig" rid="f8"><bold>Figure&#xa0;8</bold></xref>). In addition, the genera <italic>Veillonella</italic> and <italic>Erysipelotrichaceae</italic>_UCG 003 were significantly enriched after HRZE intervention (<xref ref-type="fig" rid="f8"><bold>Figure&#xa0;8</bold></xref>). However, within group follow-up analysis did not reveal any significant changes in gut microbial taxa.</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Difference in abundant taxa at baseline and month 2 HRZE treatment follow-up for all TB groups, determined by Linear discriminate analysis (LDA) effect size (LEfSe). <bold>(A)</bold> Discriminative features detected at 3.6 threshold and alpha of 0.01. P_Phylum, C_Class, O_Order, F_Family, G_Genus <bold>(B)</bold> Cladogram of baseline and follow-up. Features in red and green are differentially abundant in baseline and follow-up samples respectively.</p>
</caption>
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</fig>
</sec>
<sec id="s3_6">
<title>Gut microbial functional prediction in TB cohorts and healthy controls</title>
<p>Functional profiling was performed on baseline 16S rRNA sequences using PICRUSt2. A total of 4479 genes with 1350 enzyme classification numbers were predicted and mapped into 252 metabolic pathways. Discriminating functional features were detected by ALDEx2. No functional feature was detected to be significantly enriched or depleted when all TB patients were compared to controls (<xref ref-type="supplementary-material" rid="SM4"><bold>Supplementary Figure&#xa0;4</bold></xref>). However, when stratified by comorbidity groups, 37 KEGG ortholog features and 1 MetaCyc features were detected to be differentially abundant in TB-DM patients compared to controls (<xref ref-type="supplementary-material" rid="SM3"><bold>Supplementary Figure&#xa0;3</bold></xref>). Enriched KEGG features included features mapped methylmalonyl-coA-mutase, phosphoribosyl,1-2 cyclic phosphate phosphodiesterase, tRNA(fMet)-specific endonuclease Vap C, NADP-dependent-alcohol dehydrogenase (<xref ref-type="fig" rid="f9"><bold>Figure&#xa0;9</bold></xref>). Metabolic function involved in isopropanol biosynthesis was detected to be significantly depleted in TB-DM patients.</p>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Significant differentially abundant predictive KEGG ortholog functional pathways. PICRUSt2 was used to determine the predictive microbial metagenome functional abundances from 16S rRNA sequences. Predicted functional abundances were analyzed with ALDEx2 to determine differentially abundant functional pathways.</p>
</caption>
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</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>The human gut microbiome is critical for the development of the host immune system and tissue homeostasis (<xref ref-type="bibr" rid="B10">Chunxi et&#xa0;al., 2020</xref>). Aside from the numerous beneficial roles of the microbiome within an individual, its role in the development of metabolic and infectious diseases in an altered (dysbiotic) state has been documented (<xref ref-type="bibr" rid="B26">Guinane and Cotter, 2013</xref>). In this study we explored the gut microbiome dynamics in TB patients with or without HIV or diabetes comorbidities before and after intensive phase anti-TB therapy. We found that the microbiome of the TB patients was enriched with inflammatory related microbial organisms with a general increase in these organisms after at 2 months HRZE intervention.</p>
<p>Several studies have reported a decreased gut microbiome diversity in TB patients (<xref ref-type="bibr" rid="B41">Luo et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B29">Hu et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B8">Cao et&#xa0;al., 2021</xref>; <xref ref-type="bibr" rid="B71">Wang et&#xa0;al., 2022</xref>), similar to findings in our study which shows a significantly lower gut microbial diversity in TB patients before HRZE intervention compared to healthy controls (<xref ref-type="fig" rid="f3"><bold>Figures&#xa0;3A&#x2013;C</bold></xref>). This reduced alpha diversity persisted after 2 months of HRZE intervention especially in the comorbid cases (<xref ref-type="fig" rid="f4"><bold>Figures&#xa0;4A, B</bold></xref>). This could be indicative that in addition to TB, compositional shifts could be occurring in a TB-comorbidity specific manner.</p>
<p>Firmicutes are known to be a predominant phylum in the human gut (<xref ref-type="bibr" rid="B58">Qin et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B1">Arumugam et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B47">Morton et&#xa0;al., 2015</xref>). Likewise in this study, the most abundant phylum in both healthy controls (76.3%) and all TB patients (&gt; 65.8%) was the phylum <italic>Firmicutes</italic> (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;1</bold></xref>). Several bacteria groups belonging to <italic>Firmicutes</italic> could utilize carbohydrates through anerobic fiber fermentation to produce short-chain fatty acids (SCFAs), such as acetates, propionate, and butyrate. These exert immunomodulatory effects including anti-inflammatory and regulation of gut&#x2019;s pH to improve the availability of calcium (<xref ref-type="bibr" rid="B67">TeitelbaumAllan Walker, 2002</xref>; <xref ref-type="bibr" rid="B6">Broekaert et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B69">Venegas et&#xa0;al., 2019</xref>). Consistent with their beneficial role in the human gut, we detected an abundance of <italic>Firmicutes</italic> driven mostly by the genera <italic>Clostridium, Faecalibacterium, Blautia</italic> and <italic>Agathobacter</italic> in the gut of the healthy individuals (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref> and <xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table&#xa0;2</bold></xref>). Additionally, other genera such as <italic>Romboutsia</italic>, CAG-352, <italic>Subdoligranulum</italic>, and <italic>Dialister</italic> (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref>) were also among the top 20 abundant genera in the healthy individuals. Several bacteria groups belonging to the <italic>Ruminococcaceae</italic> and <italic>Lachnospiraceae</italic> families (<xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2A</bold></xref>) which includes major human butyrate producing gut bacterial species (<xref ref-type="bibr" rid="B69">Venegas et&#xa0;al., 2019</xref>) were conspicuously low in TB patients. However, there was an abundance in other <italic>Firmicutes</italic> of the genera <italic>Streptococcus</italic>, <italic>Enterococcus</italic>, <italic>Bacteriodes</italic> and <italic>Erysipelatoclostridium</italic> in all the TB patients (<xref ref-type="fig" rid="f1"><bold>Figures&#xa0;1A, B</bold></xref>).</p>
<p>In the TB-DM cohort, the genus <italic>Bacteroides</italic> was significantly abundant (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6</bold></xref>), comparable to studies which reported a positive association of <italic>Bacteroides</italic> with diabetic individuals (<xref ref-type="bibr" rid="B63">Sircana et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B61">Sharma and Tripathi, 2019</xref>; <xref ref-type="bibr" rid="B27">Gurung et&#xa0;al., 2020</xref>). The <italic>Bacteroides</italic> genera are beneficial for glucose metabolism as well as regulating the expression of tight junction genes in the colon to reduce gut permeability (<xref ref-type="bibr" rid="B75">Yoshida et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B27">Gurung et&#xa0;al., 2020</xref>). In the TB-Only cohort, the <italic>Streptococcus</italic> and <italic>Erysipelatoclostridium</italic> (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5</bold></xref>) which have been associated with high inflammatory conditions (<xref ref-type="bibr" rid="B76">Zeng et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B70">Wang et&#xa0;al., 2020</xref>), was abundant while in the TB-HIV in addition to <italic>Erysipelatoclostridium</italic>, <italic>Escherchia-Shigella</italic>, <italic>Dialister</italic> and <italic>Corynebacterium</italic> were abundant (<xref ref-type="fig" rid="f7"><bold>Figure&#xa0;7</bold></xref>). Even though most of these bacteria are beneficial in maintaining a healthy gut microbiome, their association with inflammatory conditions could pose some health risk when it is overly abundant in the gut (<xref ref-type="bibr" rid="B70">Wang et&#xa0;al., 2020</xref>).</p>
<p>Contradictory to other studies in Africa which reported reduced abundance in the <italic>Actinobacteriota</italic> phylum (<xref ref-type="bibr" rid="B78">Zoetendal et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B21">Filippo et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B11">Costea et&#xa0;al., 2018</xref>), interestingly, in this study, we observed an abundance in the <italic>Actinobacteriota</italic> phylum (9.5%) in the healthy individuals, making it the second most abundant phylum in healthy individuals in this study (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure 1</bold></xref>). The abundance of <italic>Actinobacteriota</italic> was driven mainly by the <italic>Bifidobacterium</italic> genera (<xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1A</bold></xref> and <xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table 2</bold></xref>) which has been shown to be among the first microbes to colonize the human gut and very beneficial in gut homeostasis and digestion of fiber to produce SCFAs (<xref ref-type="bibr" rid="B52">O&#x2019;Callaghan and Sinderen, 2016</xref>). Contrarily, in all the TB cohorts, <italic>Actinobacteria</italic> was significantly decreased compared to the controls (<xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;1</bold></xref>).</p>
<p>Similar to other studies which associated <italic>Prevotella</italic> with high fiber-carbohydrate diet mostly in rural areas in sub-Saharan (<xref ref-type="bibr" rid="B20">Filippo et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B53">Parbie et&#xa0;al., 2021a</xref>), we observed an abundance in the genera <italic>Prevotella</italic> as the dominant group of phylum <italic>Bacteriodota</italic> in healthy individuals. Among the TB cohorts, <italic>Prevotella</italic> was more abundant in the TB-DM cohorts (3.4%) (<xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table 2</bold></xref>) allowing for some association with studies that recorded enrichment of this genera in metabolic disorders such as type 2 diabetes (<xref ref-type="bibr" rid="B57">Precup and Vodnar, 2019</xref>; <xref ref-type="bibr" rid="B14">Ding et&#xa0;al., 2022</xref>). Also, in addition to <italic>Prevotella</italic>, in the TB-DM cohort, the <italic>Bacteriodes</italic> which has been reported to be positively associated with diabetes (<xref ref-type="bibr" rid="B49">Murphy et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B74">Wu et&#xa0;al., 2017</xref>), was significantly differentially abundant in the TB-DM cohort (<xref ref-type="fig" rid="f6"><bold>Figure&#xa0;6</bold></xref>).</p>
<p>Irrespective of the overall decrease in microorganism of the <italic>Firmicutes</italic>, <italic>Bacteroidetes</italic> and <italic>Actinobacteria</italic> phyla in all TB cohorts compared to healthy individuals, an enrichment of diverse commensal bacteria of the phylum <italic>Proteobacteria</italic> containing potential pathogenic bacteria and inflammatory related organisms and other pathobionts was observed. Specifically, the genera <italic>Escherichia</italic>- <italic>Shigella</italic>, documented to be abundant in a Ghanaian cohort (<xref ref-type="bibr" rid="B53">Parbie et&#xa0;al., 2021a</xref>), as well as other African populations (de <xref ref-type="bibr" rid="B21">Filippo et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B44">Mancabelli et&#xa0;al., 2017</xref>). Interestingly, in this study, <italic>Escherichia</italic>- <italic>Shigella</italic> was not detected as a predominant bacterium in the gut of healthy individuals (<xref ref-type="fig" rid="f1"><bold>Figures&#xa0;1A, B</bold></xref> and <xref ref-type="supplementary-material" rid="SM1"><bold>Supplementary Figure&#xa0;1</bold></xref>). This may be attributable to difference in population dynamics including socioeconomic status and dietary habits; the participants in the present study were from urban communities in Accra, the capital city of Ghana, compared to participants from &#x201c;peri-urban&#x201d; communities in the previous study (<xref ref-type="bibr" rid="B53">Parbie et&#xa0;al., 2021a</xref>). Also, a study in Korea reported an abundance of the <italic>Proteobacteria</italic> phylum in type 2 diabetes individuals (<xref ref-type="bibr" rid="B62">Shin et&#xa0;al., 2015</xref>) but no such association was found in this study. We however observed a high abundance of <italic>Proteobacteria</italic> in TB-HIV individuals (<xref ref-type="supplementary-material" rid="ST2"><bold>Supplementary Table 2</bold></xref>) driven mostly by the <italic>Escherichia</italic>- <italic>Shigella</italic> family. This genera have been associated with high inflammatory activities as seen in tuberculosis allowing for proliferation of inflammatory-related microorganisms (<xref ref-type="bibr" rid="B17">Eribo et&#xa0;al., 2020</xref>) which may not cause disease itself but rather serve to increase susceptibility to intestinal inflammation (<xref ref-type="bibr" rid="B76">Zeng et&#xa0;al., 2017</xref>). Additionally, abundances of <italic>Protobacteria</italic> have been associated with translocation and inflammation of HIV infected individuals (<xref ref-type="bibr" rid="B54">Parbie et&#xa0;al., 2021b</xref>).</p>
<p>Intensive phase anti-TB therapy comprises drugs with specific TB targets (HZE) and a broad-spectrum antibiotics (R) (<xref ref-type="bibr" rid="B32">Jnawali and Ryoo, 2013</xref>). Broad spectrum antibiotics such as RIF, which are active against most bacterial pathogens, could be responsible for the antibiotic associated perturbations (<xref ref-type="bibr" rid="B12">Dethlefsen and Relman, 2011</xref>).</p>
<p>After HRZE treatment, there was a higher abundance of bacteria groups in all the follow-up groups, especially in the TB-HIV cohort (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4B</bold></xref>). There was an overall enrichment in the genera <italic>Veillonella</italic>, <italic>Erysipelatoclostridium</italic>, and <italic>Fusobacterium</italic> at follow-up compared to the baseline (<xref ref-type="fig" rid="f8"><bold>Figure&#xa0;8</bold></xref>), like findings from a study reporting abundance of <italic>Erysipelatoclostridium</italic> in a United States population after HRZE treatment (<xref ref-type="bibr" rid="B73">Wipperman et&#xa0;al., 2017</xref>). The genera <italic>Erysipelatoclostridium</italic> and <italic>Fusobacterium</italic> are known to be abundant during inflammatory and immune reducing conditions as in TB patients as well as in HIV infection and diabetes (<xref ref-type="bibr" rid="B51">Neuhaus et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B18">Etna et&#xa0;al., 2014</xref>). While <italic>Erysipelatoclostridium</italic> possess the ability to flourish during broad-spectrum antibiotic treatment (<xref ref-type="bibr" rid="B15">Dinh et&#xa0;al., 2014</xref>), <italic>Fusobacterium</italic> produces chemical signals that can induce apoptosis in monocytes and macrophages through activation of free fatty acid receptors (<xref ref-type="bibr" rid="B37">Lee et&#xa0;al., 2018</xref>; <xref ref-type="bibr" rid="B25">Gu et&#xa0;al., 2020</xref>), which is also observed in gut mucosa of colorectal cancer patients (<xref ref-type="bibr" rid="B33">Kelly et&#xa0;al., 2018</xref>). Even though the significance of HRZE induced taxonomic perturbations is not well-understood, the majority of these bacteria have been associated with immune-inducing phenotypes relevant for TB immunity (<xref ref-type="bibr" rid="B73">Wipperman et&#xa0;al., 2017</xref>).</p>
<p>Contrary, to previous reports which identified vitamin B12 deficiency as a serious problem in diabetics (<xref ref-type="bibr" rid="B40">Liu et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B56">Pflipsen et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B34">Kibirige and Mwebaze, 2013</xref>) due to a negative relationship with metformin, this was not observed in our study population. We found a significant abundance of methylmalonyl-CoA mutase in the gut of TB-DM patients compared to controls. This enzyme is involved in Vitamin B12 synthesis, and degradation of amino acids, short-chain fatty acids and cholesterol (<xref ref-type="bibr" rid="B4">Blum et&#xa0;al., 2021</xref>). Thus, the abundance of this enzyme and MTB&#x2019;s capacity for <italic>de novo</italic> biosynthesis of vitamin B12 (<xref ref-type="bibr" rid="B24">Gopinath et&#xa0;al., 2013</xref>), resulting in reports of elevated B12 vitamin in TB patients (<xref ref-type="bibr" rid="B23">Gebremicael et&#xa0;al., 2019</xref>), could account for our observation. The abundance of methylmalonyl-CoA mutase in only TB-DM group is intriguing and could be the body&#x2019;s homeostasis activity (<xref ref-type="bibr" rid="B66">Takahashi et&#xa0;al., 1994</xref>). Also, a significant abundance of organisms involved in isopropanol biosynthesis in the TB-DM cohort was intriguing, since the metabolite produced is known to inhibit growth of <italic>Mycobacterium tuberculosis</italic>. However, this abundance was only detected in TB-DM cohort and not in the other TB groups. Additionally, an increase of L-rhamnose mutarotase which is involved in the L-rhamnose metabolism pathway for carbohydrate metabolism (<xref ref-type="bibr" rid="B59">Ryu et&#xa0;al., 2005</xref>), and very crucial in the diabetes control (<xref ref-type="bibr" rid="B64">Solis-Herrera et&#xa0;al., 2021</xref>), was abundant in the TB-DM cohorts.</p>
<p>We acknowledge some limitations especially in the sample size of our control and TB-HIV cohort. However due to the nature of our study, we believe the best representation of healthy controls would be those individuals that live in the same household as the test subjects to rule out any bias. But this number was fewer than expected and we were unable to use previously published gut microbiome data from Ghana as reference gut microbiome due to difference in population dynamics including socioeconomic status, dietary habits, and geographical location. Nevertheless our study reveals a profound impact of TB on the gut microbiome.</p>
</sec>
<sec id="s5" sec-type="conclusion">
<title>Conclusion</title>
<p>This study describes a profound gut dysbiosis in TB patients with or without diabetes or HIV comorbidities compared to the healthy controls. Several opportunistic pathogens of the bacteria groups including <italic>Escherichia-shigella</italic>, <italic>Streptococcus</italic> and <italic>Enterococcus</italic> were enriched in all TB cohorts, whereas beneficial bacteria groups such as SCFA-producing bacteria were depleted. Notably, there was significant alteration in microbial population in TB-DM individuals driven mainly by <italic>Bacteriodes</italic>, <italic>Blautia</italic> and <italic>Escherichia-shigella.</italic> Further studies focused at understanding the long-term changes in the gut microbiome of comorbid groups during the entire TB treatment, and its potential impact on the treatment outcome will provide further insight on the role of gut microbiome on progression of TB.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The data presented in the study are deposited in the NCBI repository, accession number PRJNA876282.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving human participants were reviewed and approved by Institutional Review Board of the Noguchi Memorial Institute for Medical Research with Federal wide Assurance number FWA00001824. The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>PM, AB, IL, and EA contributed to sample collection and possessing. PM, AA-P, IO, SA, and DY-M contributed to the methodology. PM, DN, IL, CG, EA, SA contributed to the investigation. PM, PP, and IO did formal analysis. PM, DN, and CG performed all laboratory experiments. PM prepared the original draft of the manuscript. PM, PP, AB, PA, AA-P, IO, SA, and DN contributed to reviewing and editing manuscript. IO, AA-P, and DY-M supervised the work. DY-M provided recourses and conceptualized the study. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>European and Developing Countries Clinical Trials Partnership (EDCTP) Senior Fellowship to DY-M (TMA-2017-GSF-1942).</p>
</sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s12" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/frmbi.2023.1123064/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/frmbi.2023.1123064/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="DataSheet_1.pdf" id="SM1" mimetype="application/pdf"/>
<supplementary-material xlink:href="DataSheet_2.pdf" id="SM2" mimetype="application/pdf"/>
<supplementary-material xlink:href="DataSheet_3.pdf" id="SM3" mimetype="application/pdf"/>
<supplementary-material xlink:href="DataSheet_4.pdf" id="SM4" mimetype="application/pdf"/>
<supplementary-material xlink:href="DataSheet_5.pdf" id="SM5" mimetype="application/pdf"/>
<supplementary-material xlink:href="Table_1.docx" id="ST1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
<supplementary-material xlink:href="Table_2.docx" id="ST2" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document"/>
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