# An insight into the characterization of L2 Beijing multi-drug resistant tuberculosis: Description of resistance-associated-variants and discovery of Modern 7 L2 sublineage

Marianne Antar Soutou, Camille Allam, Marianne Abifadel, Josette Najjar, Christophe Guyeux, Emmanuelle Cambau, Christophe Sola

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## ► To cite this version:

Marianne Antar Soutou, Camille Allam, Marianne Abifadel, Josette Najjar, Christophe Guyeux, et al.. An insight into the characterization of L2 Beijing multi-drug resistant tuberculosis: Description of resistance-associated-variants and discovery of Modern 7 L2 sublineage. Infection, Genetics and Evolution, 2025, 134, pp.105797. 10.1016/j.meegid.2025.105797. hal-05327907

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Submitted on 23 Oct 2025

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# An insight into the characterization of L2 Beijing multi-drug resistant tuberculosis: Description of resistance-associated-variants and discovery of Modern 7 L2 sublineage

Marianne Antar Soutou<sup>a,b,c</sup>, Camille Allam<sup>a,b</sup>, Marianne Abi Fadel<sup>c</sup>, Josette Najjar<sup>d</sup>, Christophe Guyeux<sup>e</sup>, Emmanuelle Cambau<sup>a,b</sup>, Christophe Sola<sup>a,b,f,*</sup>

## ARTICLE INFO

**Keywords:**

Mycobacterium tuberculosis complex
Lineage 2
Genomics
Drug-Resistance
Evolution
China

## ABSTRACT

Drug-resistant tuberculosis (TB) complicates global efforts toward TB elimination. However, the introduction of new and repurposed drugs—particularly the all-oral BPaL regimen (bedaquiline, pretomanid, and linezolid)—has raised hopes due to its favorable treatment outcomes for multidrug-resistant (MDR) and extensively drug-resistant (XDR) TB. Susceptibility to these new drugs may vary depending on the lineage of the *Mycobacterium tuberculosis* (MTB) strain. Within the framework of a research project investigating the association between potential resistance-associated nucleotide variants and MTB lineages, we used the proprietary pipeline *TB-Annotator* to analyze 125,000 publicly available Short Read Archive datasets from NCBI.

We identified 65 mutations across 65 clonal complexes of the lineage 2 (L2), that share at least one SNP within a list of 14 genes potentially involved in drug resistance to BPaL. During this large-scale genomic screening, we identified a previously uncharacterized clonal complex of 49 SRAs that did not belong to any previously described ancient or modern L2-sublineages (modern 1 to modern 6). We therefore performed a comparative genomic analysis on a representative set of L2 isolates to fully characterize this group. These 49 SRAs are found in an independent branch of the L2 phylogenetic tree. They share 4 SNPs, including an Ile-to-Leu substitution in the product of *fbiD*, and are organized into two subclusters, with an intra-sublineage SNP distance of around 150 ± 50 SNPs. We named this novel sublineage L2.2-M7. Further functional validation—through phenotypic drug susceptibility testing and gene replacement—is needed to determine whether this *fbiD* mutation confers resistance to pretomanid. Global genomic surveillance of this emerging sublineage is warranted to monitor its spread and clinical relevance in the era of new TB treatment regimens.

## 1. Introduction

Multidrug-resistant tuberculosis (MDR-TB)—defined as TB resistant to the two first-line drugs, isoniazid and rifampicin—and extensively drug-resistant TB (XDR-TB) -resistant to isoniazid, rifampicin, any

fluoroquinolone, and either bedaquiline (BDQ) or linezolid (LZD) (or both)—pose major challenges to global TB control, especially in high-burden settings (Viney et al., 2021). The introduction of the new all-oral BPaL regimen (the combination of BDQ, pretomanid (PRM), and LZD), and its variant BPaLM with moxifloxacin (MXF), has raised

<footnote><sup>a</sup> Université Paris Cité, IAME, INSERM, Université Sorbonne-Paris Nord, 16, rue Henri-Huchard, cedex 18, BP 419, 75870 Paris, France</footnote>

<footnote><sup>b</sup> Service de mycobactériologie spécialisée et de référence, Laboratoire associé du Centre national de référence des mycobactéries et résistance des mycobactéries aux antituberculeux, APHP GHU Nord Université Paris Cité, Hôpital Bichat, 46, rue Henri Huchard, 75018 Paris, France</footnote>

<footnote><sup>c</sup> Laboratoire Rodolphe Mérieux Liban, Faculté de Pharmacie, Université Saint-Joseph de Beyrouth, Beyrouth, Lebanon</footnote>

<footnote><sup>d</sup> Fondation Mérieux, Beyrouth, Lebanon</footnote>

<footnote><sup>e</sup> Université Marie et Louis Pasteur, Besançon, France</footnote>

<footnote><sup>f</sup> Université Paris Saclay, Gif-sur-Yvette 91190, France</footnote>

<footnote>* Corresponding author at: INSERM, IAME, UMR1137, Université Paris Cité-Université Sorbonne-Paris Nord, 16, rue Henri-Huchard, cedex 18, BP 419, 75870 Paris, France.</footnote>

<footnote>E-mail addresses: marianne.antar@usj.edu.lb (M.A. Soutou), camille.allam@aphp.fr (C. Allam), marianne.afibadel@usj.edu.lb (M. Abi Fadel), josette.najjar@fondation-merieux.org (J. Najjar), christophe.guyeux@univ-fcomte.fr (C. Guyeux), emmanuelle.cambau@aphp.fr (E. Cambau), christophe.sola@universite-paris-saclay.fr (C. Sola).</footnote>
considerable hope for a more effective and better-tolerated treatment (Wares et al., 2024).

Recent advances in whole-genome-sequencing (WGS) have provided new insights into the ecology and evolution of the *Mycobacterium tuberculosis* complex (MTBC). Currently, human-adapted MTBC strains are classified into ten phylogenetic lineages (L1 to L10), which are considered “ancestral” (L1 and L5 to L10) or “modern” (L2 to L4) based on the presence or absence of the Tbd1 genomic region (Brosch et al., 2002; Comas et al., 2013; Coscolla et al., 2021; Guyeux et al., 2024).

Recent data showed that the genetic diversity of MTBC might play a role in the emergence of drug resistance and in determining treatment outcomes (Cevik et al., 2024). Among the MTBlineages, the lineage 2 (L2), commonly known as the Beijing lineage, is particularly associated with high transmissibility, virulence, and an increased propensity for acquiring drug resistance (Merker et al., 2015; Merker et al., 2018). Its global spread and ability to evade treatment is a concern for TB control programs. Despite the insights offered by WGS, the analysis of genomic sequencing data remains challenging, limiting the routine application of WGS in clinical and public health settings. This is primarily due to requirement for specialized bioinformatics expertise and high-performance computing resources, which are often lacking in most clinical laboratories. To help bridge this gap, three years ago we initiated the development of *TB-Annotator*, a scalable web-based platform for large-scale WGS analysis and visualization (Senelle, 2024). Now at version (v2.5), TB-Annotator integrates 125,129 SRA datasets and is accessible at https://gnksoftware.synology.me:30002/. The platform supports both public health surveillance—such as monitoring resistance trends and identifying epidemic clones—and academic research on MTBC evolution (Senelle et al., 2023a; Senelle et al., 2023b).

In this study, we used *TB-Annotator* to analyze potential resistance-associated variants (RAVs) in 14 key genes (Table 1) across L2 isolates within a dataset of over 125,000 publicly available MTBC genomes. During this investigation, we identified a previously undescribed modern Beijing (L2.2) sublineage in China, Canada (British Columbia), and Vietnam, that was found to be multi-drug resistant in 38 % of cases. We propose this novel clonal complex—currently comprising more than 50 clinical isolates—represents a new modern sublineage, which we designate as L2.2-M7. While these isolates do not align with the established L2 sublineage taxonomy, they meet key genetic criteria consistent with modern L2.2 strains (Shitikov et al., 2017; Freschi et al., 2021; Thawornwattana et al., 2021).

## 2. Material and methods

### 2.1. *TB-Annotator* database version

We used TB-Annotator version 2.5, released in June 2024, which updates to the previous version 2.4 (Senelle, 2024). At the time of writing, the v2.5 database contained 125,129 SRA datasets, primarily

retrieved from the NCBI Short Read Archive. Detailed information on SRA comparisons and bioinformatics methods can be found in previous publications (Guyeux et al., 2022; Senelle et al., 2023b). For mutation analysis search, *TB-Annotator* uses either *position* or the *SPDI* notation (Sequence, Position, Deletion, Insertion) as published by (Holmes et al., 2020).

### 2.2. *List of candidate genes implicated in the resistance to new and repurposed drugs*

Candidate genes were selected based on their known or suspected involvement in resistance to these drugs, as reported in the literature and in the second edition of the WHO catalog of mutations in *Mycobacterium tuberculosis* complex (MTBC) (WHO, 2024). The list of candidate genes, presented in Table 1, includes information on gene name, locus tag, codon start, and codon stop.

For BDQ resistance, most clinical isolates harbor variants in the *mmpR* gene (*Rv0678*), which encodes a transcriptional repressor of the MmpS5-MmpL5 efflux pump, thereby implicating a drug efflux mechanism in BDQ resistance. These mutations are associated with increased minimal inhibitory concentrations (MICs) and cross-resistance with clofazimine (CFZ) (Hartkoorn et al., 2014). Additionally, mutations in the *atpE* gene (*Rv1305*), which encodes subunit c of the ATP synthase, BDQ's direct drug target, are also observed (Zimenkov et al., 2017). These *atpE* mutations lead to conformational changes in the protein, thus preventing BDQ binding and subsequent inhibition of ATP synthesis, and are associated with high-level resistance (Nguyen et al., 2018). Other candidate genes implicated in BDQ and CFZ resistance include *pepQ* (*Rv2535c*), encoding a putative cytoplasmic peptidase, and *Rv1979c*, encoding a putative permease (Almeida et al., 2016; Kadura et al., 2020). In addition, we included *Rv1453* gene, encoding the transcription factor *Rv1453* due to its association with CFZ resistance through regulation of *qor* gene expression (Li et al., 2021).

As for pretomanid (PTM) and delamanid (DLM), these nitro-imidazole prodrugs share the same activation pathway in MTBC through an F420H2-dependent reduction catalyzed by the deazaflavin-dependent nitroreductase (ddn) (Haver et al., 2015; Rifat et al., 2020). Consequently, mutations in the *ddn* gene or any of the genes involved in F420 cofactor biosynthesis and recycling (*fgd1*, *fbiA*, *fbiB*, *fbiC*, *fbiD*) could lead to drug resistance either by preventing DLM/PTM activation directly or indirectly by depleting F420.

For linezolid (LZD), mutations in genes encoding components of the 50S ribosomal subunit, particularly the *rplC* gene (encoding L3 ribosomal protein) or the *rrl* gene (encoding 23S rRNA) are primarily responsible for LZD resistance (Beckert et al., 2012; Pi et al., 2019; Zhang et al., 2014). These mutations lead to conformational changes in the rRNA at the LZD binding sites, thereby preventing LZD from binding to the peptidyl transferase center. Lastly, *Rv1830*, the recently described resilience regulator (*resR*) gene was also included. ResR is a ubiquitous

<table><caption>**Table 1**

List of the 14 studied candidate genes associated with bedaquiline, clofazimine, delamanid, pretomanid and linezolid resistance.</caption><thead><tr><th>Antituberculous drug</th><th>Gene name</th><th>Locus tag</th><th>Codon start</th><th>Codon stop</th><th>Reference</th></tr></thead><tbody><tr><td>Bedaquiline</td><td>atpE</td><td>Rv1305</td><td>1,461,045</td><td>1,461,290</td><td>Zimenkov et al., 2017; Nguyen et al., 2018</td></tr><tr><td>Bedaquiline/clofazimine</td><td>Rv0678</td><td>Rv0678</td><td>778,990</td><td>779,487</td><td>Zimenkov et al., 2017; Kadura et al., 2020</td></tr><tr><td>Bedaquiline/clofazimine</td><td>pepQ</td><td>Rv2535c</td><td>2,859,300</td><td>2,860,418</td><td>Almeida et al., 2016</td></tr><tr><td>Bedaquiline/clofazimine</td><td>Rv1979c</td><td>Rv1979c</td><td>2,221,719</td><td>2,223,164</td><td>Kadura et al., 2020</td></tr><tr><td>Clofazimine</td><td>Rv1453</td><td>Rv1453</td><td>1,638,381</td><td>1,639,646</td><td>Li et al., 2021</td></tr><tr><td>Delamanid/pretomanid</td><td>ddn</td><td>Rv3547</td><td>3,986,844</td><td>3,987,299</td><td>Haver et al., 2015</td></tr><tr><td>Delamanid/pretomanid</td><td>fgd1</td><td>Rv0407</td><td>490,783</td><td>491,793</td><td>Haver et al., 2015</td></tr><tr><td>Delamanid/pretomanid</td><td>fbiA</td><td>Rv3261</td><td>3,640,543</td><td>3,641,538</td><td>Haver et al., 2015</td></tr><tr><td>Delamanid/pretomanid</td><td>fbiB</td><td>Rv3262</td><td>3,641,535</td><td>3,642,881</td><td>Haver et al., 2015</td></tr><tr><td>Delamanid/pretomanid</td><td>fbiC</td><td>Rv1173</td><td>1,302,931</td><td>1,305,501</td><td>Haver et al., 2015</td></tr><tr><td>Delamanid/pretomanid</td><td>fbiD</td><td>Rv2983</td><td>3,339,118</td><td>3,339,762</td><td>Rifat et al., 2020</td></tr><tr><td>Linezolid</td><td>rrl</td><td>MTB000020</td><td>1,473,658</td><td>1,476,795</td><td>Zhang et al., 2014; Pi et al., 2019</td></tr><tr><td>Linezolid</td><td>rplC</td><td>Rv0701</td><td>800,809</td><td>801,462</td><td>Beckert et al., 2012</td></tr><tr><td>indirect effect on resistance</td><td>resR</td><td>Rv1830</td><td>2,074,841</td><td>2,075,518</td><td>Liu et al., 2022</td></tr></tbody></table>
transcription factor that plays a role in a cascade of other gene regulation processes and was shown to be a target of positive selection (Liu et al., 2022).

## 2.3. Data extraction methods in TB-annotator

A Python script was developed to extract potential Resistance-Associated Variants (RAVs) from genes listed in Table 1, using data from the TB-annotator v2.4, and ultimately v2.5 (125,129 SRA) databases. The raw results obtained for L2 lineages are provided in Supplementary Table 1. A flow-chart of the data extraction process is explained in the next paragraph and is summarized in Supplementary material 1.

## 2.4. Analysis of script results

Our script generated a CSV file containing a matrix of 9730 rows (SNPs) by 91 columns (lineages/sublineages). Each cell represents the number of SRAs in TB-annotator exhibiting these specific taxonomic characteristics (see Supplementary Table 1). The total number of L2 SRAs in TB-annotator v2.5 is 38,943 (filtered using SPDI 282891:C:T;

TB-annotator v2.5). 9730 variants were initially found in the 14 analyzed genes. Of these, 1917 had at least one SRA associated with the L2 lineages, comprising 12,530 SRAs in total. Some clusters were kept for future analysis. The final number of L2 isolates in the complex clusters selected for in-depth analysis was 8254 (Table 2), representing 65 clonal complexes (with a minimum cluster size of 17 SRAs) out of 90 clonal complexes with more than 16 isolates. We did not attempt a more precise identification of SRAs with potential resistance-associated variants in the *atpE* gene (*Rv1305*) as the number of such SRAs in the database was always low (one single mutation SPDI1461175:G:C was found in 13 SRAs in *TB-annotator*).

A precise taxonomic search was performed in *TB-annotator* for these clusters using a combination of diagnostic markers described in Supplementary Table 2.

## 2.5. In-depth taxonomic assignment of MDR and pre-XDR clusters and characterization of L2.2-M7

After automated diagnostic barcoding of MDR and pre-XDR isolates belonging to L2, L2.1, and L2.2 sublineages, we performed an *in silico*

<caption>**Table 2**</caption>

Characteristics of the SNPs of 65 MTBC L2 clonal complexes in genes related to BPALM drug-resistance; association to the most precise L2 taxonomy of either Ancient and/or Modern L2 sublineages. *, **, ***

<table><thead><tr><th>SPDI</th><th>Amino Acid Change</th><th>Position</th><th>L2 sublineage* or clonal complex name</th><th>L2 sub-lineage**</th><th>n° of SRA (in TB-annotator)***</th><th>Gene tag</th><th>Drug resistance</th><th>Gene Name/function</th><th>Ancient/Modern</th></tr></thead><tbody><tr><td>NC_009962.3:2221938.C.T</td><td>pArg409Gln</td><td>2221937</td><td>2.2.1/A1</td><td>2.2.1/A1</td><td>1224</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:3640876.C.T</td><td>Synonymous</td><td>3640877</td><td>2.2.1/A2</td><td>2.2.1/A2</td><td>748</td><td>Rv3261</td><td>DLM/PTM</td><td>fbiB</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:491289.G.A</td><td>p.Val170Met</td><td>49128</td><td>2.2.1/M2</td><td>2.2.1/M2</td><td>680</td><td>Rv4607</td><td>DLM/PTM</td><td>fdg1</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:2223013.A.T</td><td>p.Tyr51Asn</td><td>2223012</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>606</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2222188.C.T</td><td>p.Val51Gly</td><td>2222187</td><td>2.2.1/M1</td><td>2.2.1/M1</td><td>462</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1304442.G.A</td><td>p.Ala505Thr</td><td>1304441</td><td>2.1</td><td>(All)</td><td>406</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiB</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:3641809.G.C</td><td>Synonymous</td><td>3641808</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9</td><td>347</td><td>Rv3262</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641331.G.A</td><td>p.Gly264Arg</td><td>3641330</td><td>2.2.1/M6</td><td>2.2.1/M6</td><td>305</td><td>Rv3261</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1303131.A.G</td><td>p.Ile128Val</td><td>1303130</td><td>2.2.1/M3</td><td>2.2.1/M3</td><td>300</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:491555.G.A</td><td>Synonymous</td><td>491554</td><td>2.2.1/M5</td><td>2.2.1/M5</td><td>296</td><td>Rv4607</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641624.G.A</td><td>p.Ala31Thr</td><td>3641623</td><td>2.2.1/M5</td><td>2.2.1/M5</td><td>229</td><td>Rv3262</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2222111.G.A</td><td>frameshift variant</td><td>2222110</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9</td><td>198</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3981075.G.A</td><td>STOP gained p.Trp88*</td><td>3981704</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.5.1</td><td>148</td><td>Rv3547</td><td>DLM/PTM</td><td>dnB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2222356.T.C</td><td>p.Thr270Ala</td><td>2222355</td><td>2.2.1/M2</td><td>2.2.1/M2/M2.5</td><td>144</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2222309.A-C</td><td>p.Val52Gly</td><td>2222308</td><td>2.2.1/M6</td><td>2.2.1/M6</td><td>119</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1303896.C.T</td><td>Synonymous</td><td>1303896</td><td>2.2.1/M3</td><td>2.2.1/M3</td><td>111</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:779153.A.C</td><td>p.Glu55Asp</td><td>779152</td><td>2.2.1/A3.2</td><td>2.2.1/A3.2-C2</td><td>106</td><td>Rv0678</td><td>BDQ</td><td>repressor of mmpl5/mmps5 (efflux pumps)</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:3986930.C.A</td><td>p.Arg30Ser</td><td>3986929</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9</td><td>106</td><td>Rv3547</td><td>DLM/PTM</td><td>dnB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1303325.C.T</td><td>Synonymous</td><td>1303324</td><td>2.2.1/M2</td><td>2.2.1/M2</td><td>105</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:802033.C.T</td><td>Synonymous</td><td>802033</td><td>2.2.1/M3</td><td>2.2.1/M3</td><td>97</td><td>Rv7072</td><td>DLM/PTM</td><td>fbiC</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1304570.G.C</td><td>Synonymous</td><td>1304569</td><td>2.2.1/M4</td><td>2.2.1/M4</td><td>79</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2075496.T.C</td><td>Synonymous</td><td>2075495</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>72</td><td>Rv1830</td><td>(multi, resR)</td><td>resR</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3339503.C.G</td><td>p.Ile129Met</td><td>3339502</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9.2</td><td>62</td><td>Rv2983</td><td>DLM/PTM</td><td>fbiD</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3987083.G.A</td><td>p.Gly81Ser</td><td>3987082</td><td>2.1</td><td>2.1-A4</td><td>59</td><td>Rv3547</td><td>DLM/PTM</td><td>dnB</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:3986988.T.C</td><td>p.Leu49Pro</td><td>3986987</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>57</td><td>Rv3547</td><td>DLM/PTM</td><td>dnB</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:1304702.C.T</td><td>Synonymous</td><td>1304701</td><td>2.2.1/A3.1</td><td>2.2.1/A3.1-C</td><td>56</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiB</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:3339629.C.T</td><td>Synonymous</td><td>3339628</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9</td><td>50</td><td>Rv2983</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2075317.T.C</td><td>p.Cys160Arg</td><td>2075316</td><td>2.2.1/M4</td><td>2.2.1/M4</td><td>49</td><td>Rv1830</td><td>ND</td><td>resR</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3339291.A.C</td><td>p.Ile59Leu</td><td>3339290</td><td>2.2.1/2.2.1.1/F/newM7</td><td>2.2.1/2.2.1.1/F/newM7</td><td>49</td><td>Rv2983</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:779143.C.T</td><td>Synonymous</td><td>779143</td><td>2.2.1/M5</td><td>2.2.1/M5</td><td>47</td><td>Rv0678</td><td>BDQ</td><td>repressor of mmpl5/mmps5 (efflux pumps)</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1639258.T.A</td><td>Synonymous</td><td>1639257</td><td>2.2.1/M1</td><td>2.2.1/M1</td><td>43</td><td>Rv1453</td><td>transcription factor</td><td>repressor of mmpl5/mmps5 (efflux pumps)</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1304342.T.G</td><td>Synonymous</td><td>1304341</td><td>2.2.1/M2</td><td>2.2.1/M2</td><td>41</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641103.G.A</td><td>p.Ala242Thr</td><td>2856939</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>40</td><td>Rv2535c</td><td>BDQ?</td><td>pepQ</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1638648.A.G</td><td>p.Glu154Gly</td><td>1638839</td><td>2.2.1/M2</td><td>2.2.1/M2-R1</td><td>39</td><td>Rv1453</td><td>CFZ</td><td>transcription factor</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1639060.C.G</td><td>Synonymous</td><td>1639059</td><td>2.2.1/M3</td><td>2.2.1/M3</td><td>39</td><td>Rv1453</td><td>CFZ</td><td>transcription factor</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2858963.A.C</td><td>Synonymous</td><td>2858962</td><td>2.2.1/M5</td><td>2.2.1/M5</td><td>34</td><td>Rv2535c</td><td>BDQ</td><td>pepQ</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641136.G.A</td><td>p.Ala199Thr</td><td>3641135</td><td>2.2.1/A1</td><td>2.2.1/A1-CHN</td><td>34</td><td>Rv3261</td><td>DLM/PTM</td><td>fbiB</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:1638961.C.A</td><td>STOP gained p.Tyr194*</td><td>1638960</td><td>2.2.1/M3</td><td>2.2.1/M3</td><td>33</td><td>Rv1453</td><td>CFZ</td><td>transcription factor</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2859397.T.C</td><td>p.Thr341Ala</td><td>2859396</td><td>2.1</td><td>2.1-U</td><td>29</td><td>Rv2535c</td><td>BDQ/CFZ</td><td>pepQ</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1772625.T.C</td><td>p.Leu49Pro</td><td>77264</td><td>2.2.1/M4</td><td>2.2.1/M4</td><td>28</td><td>Rv0678</td><td>BDQ</td><td>repressor of mmpl5/mmps5 (efflux pumps)</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:491285.G.C</td><td>Synonymous</td><td>491284</td><td>2.2.1/M4</td><td>2.2.1/M4</td><td>27</td><td>Rv4607</td><td>DLM/PTM</td><td>fdg1</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1639551.C.T</td><td>STOP gained p.Gln378*</td><td>1639510</td><td>2.2.1/M1</td><td>2.2.1/M1</td><td>27</td><td>Rv1453</td><td>CFZ</td><td>transcription factor</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2075392.A.G</td><td>p.Met185Val</td><td>2075391</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9</td><td>26</td><td>Rv1830</td><td>ND</td><td>resR</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2075204.A.G</td><td>p.Asp122Gly</td><td>2075203</td><td>2.2.1/M1/M6</td><td>2.2.1/M1/M6</td><td>25</td><td>Rv1830</td><td>ND</td><td>resR</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2075356.G.A</td><td>p.Gly173Ser</td><td>2075355</td><td>2.2.1/A3.1</td><td>2.2.1/A3.1-D</td><td>25</td><td>Rv1830</td><td>ND</td><td>resR</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:779272.T:G.C</td><td>p.Leu95Trp</td><td>779271</td><td>2.2.1/A2</td><td>2.2.1/A2-B</td><td>24</td><td>Rv0678</td><td>BDQ</td><td>repressor of mmpl5/mmps5 (efflux pumps)</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1303124.G.A</td><td>Synonymous</td><td>1303123</td><td>2.2.1/A2</td><td>2.2.1/A2-A</td><td>24</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:1639199.G.C.T</td><td>frameshift and missense var pAla274fs</td><td>1639198</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>24</td><td>Rv1453</td><td>CFZ</td><td>transcription factor</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:801096.G.A</td><td>p.Val99Gly</td><td>801095</td><td>2.2.1/M2</td><td>2.2.1/M2</td><td>23</td><td>Rv0701</td><td>DLM/PTM</td><td>repressor of mmpl5/mmps5 (efflux pumps)</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1304787.G.A</td><td>p.Ala620Thr</td><td>1304786</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.8</td><td>23</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1304971.C.T</td><td>p.Thr681Ile</td><td>1304970</td><td>2.2.1/M1</td><td>2.2.1/M1</td><td>23</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641065.G.A</td><td>p.Arg175His</td><td>3641064</td><td>2.2.1/A3.2</td><td>2.2.1/A3.2-C3</td><td>23</td><td>Rv3261</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641144.C.T</td><td>Synonymous</td><td>3641143</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>23</td><td>Rv3261</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1638511.T.C</td><td>Synonymous</td><td>1638510</td><td>2.2.1/M3</td><td>2.2.1/M3</td><td>23</td><td>Rv1453</td><td>DLM/PTM</td><td>fdg1</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:491639.G.T</td><td>Synonymous</td><td>491638</td><td>2.2.1/M6</td><td>2.2.1/M6</td><td>21</td><td>Rv4607</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3339332.G.A</td><td>Synonymous</td><td>3339331</td><td>2.2.1/M6</td><td>2.2.1/M6</td><td>21</td><td>Rv2983</td><td>DLM/PTM</td><td>fbiD</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641156.C.T</td><td>Synonymous</td><td>3641155</td><td>2.2.1.1/M1</td><td>2.2.1.1/M1</td><td>21</td><td>Rv3261</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2221910.C.T</td><td>Synonymous</td><td>2221909</td><td>2.1/2.2.1.1.1/F/CC-1979-P418</td><td>2.1/2.2.1.1.1/F/CC-1979-P418</td><td>20</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2223100.C.T</td><td>Synonymous</td><td>2223100</td><td>2.2.1/M4</td><td>2.2.1/M4</td><td>20</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:3641845.G.C</td><td>Synonymous</td><td>3641844</td><td>2.2.1/M2.4</td><td>2.2.1/M2.4</td><td>20</td><td>Rv3262</td><td>DLM/PTM</td><td>fbiB</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1303228.C.A</td><td>p.Asp100Glu</td><td>1303228</td><td>2.2.1/A3.1</td><td>2.2.1/A3.1-A</td><td>19</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Ancient Beijing</td></tr><tr><td>NC_009962.3:1639312.C.T</td><td>Synonymous</td><td>1639311</td><td>2.2.1/A3.1</td><td>2.2.1/A3.1-B</td><td>19</td><td>Rv1453</td><td>CFZ</td><td>transcription factor</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:2222644.G.A</td><td>p.Leu174Phe</td><td>2222643</td><td>2.2.1/M6</td><td>2.2.1/M6</td><td>19</td><td>Rv1979c</td><td>CFZ/BDQ?</td><td>permease</td><td>Modern Beijing</td></tr><tr><td>NC_009962.3:1304643.G.T</td><td>p.Gly572Cys</td><td>1304642</td><td>2.2.1/M4</td><td>2.2.1/M4/M4.9</td><td>17</td><td>Rv1173</td><td>DLM/PTM</td><td>fbiC</td><td>Modern Beijing</td></tr></tbody></table>

In green colour: the new L2.2 M7, in salmon colour: Ancient L2.

* L2 Classification is done according to Thawornwattana et al., 2021 based on an automated Napier et al. 2020 nomenclature with one minor exception 2.2.1/2.2.1.1.1-F/CC-1979-P418P which was based on Freschi et al., 2021 and complemented by a new Clonal Complex (CC) name.

** Precise assignation done manually in *TB-annotator* using new specific markers (Supplementary Table 2).

*** Total n° of L2 in TB-annotator v2.5; n = 38,943 filtered using SPDI 282891:C.T.
analysis in *TB-Annotator* to achieve a more precise sublineage classification for each clonal complex. This was achieved using the *SPDI* screening tool, and a refined supplementary list of L2 diagnostic barcodes (Table 2, lane 61 to 101). All clonal complexes were successfully assigned to their specific sublineages as shown in Supplementary Table 2 (most precise known taxonomic status). However, one clonal complex could not be assigned using the available barcodes. We therefore built a phylogenetic tree to analyze these 49 SRAs.

## 2.6. BioProject list

We extracted the BioProject list of the SRAs (n = 49) of the new L2.2 modern sublineage, i.e. harbouring the NC_000962.3:3339291:A:C variant, using the NCBI Genome *Bioproject* query window as shown in Supplementary Table 3. Supplementary Table 4 shows the assignation of L2.2-M7 SRAs as compared to the other SRAs. Most samples, except two from Canada, and one from Vietnam (10 had unknown origins), originated from China.

## 2.7. Bioinformatic analysis of the L2.2-M7 sublineage using TB-Annotator

We assembled a randomly downsampled collection of 319 SRAs representative of all acknowledged L2 lineages and sublineages described to date, extracted from *TB-Annotator*. This collection included L2.1 (Proto-Beijing), as well as all ancient and modern L2.2 sublineages described so far (Shitikov et al., 2017; Thawornwattana et al., 2021; Shitikov and Bespiatykh, 2023). To this representative collection, we added the 49 SRAs identified earlier by the potential RAV defined by the SPDI: NC_000962.3:3339291:A:C. The 368 SRAs (Supplementary Table 4) were used to construct two phylogenetic trees using two genome alignment methods: (1) an alignment incorporating all detected polymorphic markers (including single nucleotide polymorphisms [SNPs], insertion sequences [IS], regions of difference [RD], polymorphic regions and other variants) and (2) an alignment restricted to single nucleotide polymorphisms (SNPs). The main SNP characteristics of all L2-M7 clusters are described in Supplementary Table 5.

## 2.8. Phylogenetic methods

*TB-Annotator* uses the BWA-MEM algorithm for reference genome alignment (Li and Durbin, 2009). H37Rv (GenBank accession number NC_000962.3) served as the reference genome (Camus et al., 2002; Chitale et al., 2022; Cole and Barell, 1998; Li and Durbin, 2009). The first approach uses all polymorphic markers, including Clustured Regularly Interspersed Short Palindromic Repeats (CRISPRs), Regions of differences (RDs), and SNPs in PE/PPE genes. In parallel, a second SNP-only alignment was also produced. The comparison between these two methods was motivated by the widely acknowledged concern that SNPs found in PE/PPE genes or other confounding factors, such as repetitive markers, may compromise the accuracy of genomic alignments in comparative genomics analyses.

When only variable SNP sites were used, we generated a four-state (A,T,C,G) characters string, whereas when all variants were included a two-state (binary) character string was produced. These files were imported in FASTA format file into RAxML-NG and processed using the BIN+G model for all markers, and the GTR + G model for SNPs only (Kozlov et al., 2019). The BIN+G model allows a combination of site partitioning (BIN) with rate variation across sites (G). This model enables the division of sequence data into different partitions, each modeled with its own rate matrix. This can improve the accuracy of the phylogenetic tree by accounting for heterogeneous evolutionary processes across different sites in the alignment. The second model (GTR + G) is a nucleotide substitution model that allows for different rates of substitution between any two nucleotides in the alignment (Kozlov et al., 2019). The GTR + G model highly flexible, accommodating

unequal rates of transitions and transversions and allowing for different equilibrium frequencies for each nucleotide. It is a good default choice when balancing model flexibility and computational efficiency, particularly when working with sequence data exhibiting rate variation across sites.

After computation and optimization, the generated phylogenetic trees were reimported into *TB-Annotator* and analyzed using the platform's graphical interface. This enabled detailed cluster analysis and the detection of specific markers through various selection functions (for more details on methods, see (Guyeux et al., 2022; Senelle et al., 2023a; Senelle et al., 2023b; Guyeux et al., 2024; Senelle, 2024).

## 2.9. Computation of most common recent ancestor (MRCA) for the L2.2-M7 sublineages

The MRCA divergence time for the L2.2-M7 sublineages was estimated using the coalescence principle, under the assumptions of a constant population size and a fixed mutation rate of 0.5 SNPs per genome per year (representing a fast mutation rate). This approach allowed us to approximate the divergence time of the sublineages, with the results summarized in Table 3. These estimates should, however, be interpreted with caution due to inherent uncertainties in mutation rate assumptions and coalescent modeling.

# 3. Results

By running a custom Python script, we generated a matrix extracting

<table><caption>**Table 3**

Characteristics of the main sublineages found in Modern 7.</caption><thead><tr><th>Lineage name</th><th>Number of SRAs in the sub-lineage</th><th>Intra-cluster distance</th><th>n° of 100 % specific SNP variants</th><th>n° of > 95 % and less than 100 % specific SNP variants</th><th>Mean date of MRCA*</th></tr></thead><tbody><tr><td>M7</td><td>49</td><td>D = 153<br/>±50</td><td>4</td><td>2</td><td>306 years<br/>before present<br/>(+/- 100 years)</td></tr><tr><td>M7.1</td><td>3</td><td>D = 118<br/>+/- 11</td><td>20</td><td>0</td><td>240 years<br/>b.p (+/- 22 years)</td></tr><tr><td>M7.2</td><td>46</td><td>D = 148<br/>+/- 50</td><td>3</td><td>15</td><td>296 years<br/>b.p (+/- 100 years)</td></tr><tr><td>M7.2.1</td><td>28</td><td>D = 137<br/>+/- 31</td><td>5</td><td>6</td><td>276 years<br/>b.p (+/- 62 years)</td></tr><tr><td>M7.2.2</td><td>17</td><td>D = 53<br/>+/- 42</td><td>13</td><td>0</td><td>106 years<br/>b.p (+/- 84 years)</td></tr><tr><td>M7.2.1.1</td><td>2</td><td>D = 34</td><td>68</td><td>0</td><td>68 years<br/>b.p</td></tr><tr><td>M7.2.1.2</td><td>26</td><td>D = 136<br/>+/- 31</td><td>3</td><td>1</td><td>272 years<br/>b.p (+/- 62 years)</td></tr><tr><td>M7.2.1.2.1</td><td>3</td><td>D = 90<br/>±50</td><td>33</td><td>0</td><td>180 years<br/>b.p (+/- 100 years)</td></tr><tr><td>M7.2.1.2.2</td><td>9</td><td>D = 82<br/>+/- 29</td><td>17</td><td>0</td><td>164 years<br/>b.p (+/- 58 years)</td></tr><tr><td>M7.2.1.2.2.1</td><td>2</td><td>D = 3<br/>D = 33+/-</td><td>54</td><td>0</td><td>6 years b.<br/>p</td></tr><tr><td>M7.2.2.1</td><td>15</td><td>17</td><td>42</td><td>0</td><td>66 years<br/>b.p (+/- 34 years)</td></tr></tbody></table>

<footnote>* Most Recent Common Ancestor; assuming a mean 0,5 SNP acquisition mutation rate per year (fast mutation rate) and constant population size.</footnote>
all potential resistance-associated variants identified in the list of 14 selected genes, based on SNPs detected in 125,000 SRAs (TB-Annotator v2.5). Our analysis was restricted to the L2 lineage and sublineages. The key findings are synthesized in Table 2. This table describes the characteristics of 65 L2 clonal complexes carrying mutations in the 14 candidate genes: 15 clonal complexes were found in ancient L2 and 50 in modern L2. Among the 65 mutations, 24 were synonymous SNPs, while the remaining 41 were either missense mutations or variants potentially affecting protein structure, such as those introducing premature stop codons or causing frameshifts. One mutation in the *Rv1830* gene (Asp122Gly, SPDI NC_000962.3:2075204:A:G) was found in both L2.2 M1 and M6 lineages, whereas all other mutations were restricted to specific -likely epidemic- clonal complexes.

All modern L2 clonal complexes were successfully assigned to known L2 sublineages (M1 to M6) with a single exception. This exception concerns a novel and potentially epidemic clonal complex of modern L2 which is further characterized (proposed designation: L2.2-M7). It could not be classified within the M1-M6 sublineages based on the latest L2 classification scheme, using TB-Annotator and the updated list of diagnostic SNPs (Shitikov et al., 2024) (see also Supplementary Table 2, lanes 61 to 101).

### 3.1. Characterizations of SNPs and sublineages in Proto-Beijing (L2.1) or in Ancient Beijing MDR-TB clonal complexes

In the Proto-Beijing sublineage (L2.1), all SRAs harbor an Ala-to-Thr mutation at position 505 in the *fbiC* gene; this marker can be considered a phylogenetic marker of L2.1. Additionally, within L2.1, there are two clonal complexes containing 33 and 59 SRAs, respectively harbouring mutations in the *pepQ* gene (Thr341Ala) and in *ddn* gene (Gly81Ser). The Thr341Ala mutation is found in an MDR-TB clonal complex designated here as L2.1-U, circulating in Thailand, Vietnam, China, Cambodia and Indonesia. The second L2.1 clonal complex is remarkable as it is a pre-XDR clone circulating exclusively in Thailand and Myanmar and is designated here as L2.1-A4 according to a new L2.1 unpublished nomenclature.

In the Asia Ancestral 1 sublineage (L2.2-AA1), we identified a major sublineage (n = 1225 SRAs) containing a specific mutation in the *Rv1979c* gene (Arg409Gln; 2,221,938:C:T). This mutation is always associated with the phylogenetic mutation at position 1,003,639 (G- > A) previously identified as a hallmark of the South-African sublineage of Ancestral 1 Beijing, which has been exclusively reported in South-Africa (Shitikov et al., 2024). A second L2-AA1 clonal complex of 34 SRAs, most of which originated in China (25 in China, 1 in Japan, 8 of unknown origin), comes from a total of 16 different bioprojects (see strains L2.2-AA1-CHN in Table 2). All isolates in this group are either MDR or Pre-XDR and share a common Ala199Thr (3,641,136:G:A) mutation in the *fbiB* gene.

In Asia Ancestral 2 (L2.2-AA2), we observed a perfect correlation between the phylogenetic marker described as specific of this sublineage (SPDI:NC_000962.3:3970978:A:C) (Shitikov et al., 2024) and a synonymous mutation in the *fbiB* gene, which represents a second neutral phylogenetic marker (SPDI: NC_000962.3:3640878:C:T). We identified another synonymous SNP found in *Rv1173*, in a subcluster of 24 SRAs exclusively found in China again (L2.2/AA2-A), and another one in *Rv0678* (Leu95Trp), originating from a single Bioproject (PRJNA766993) reported from Shenzhen hospital (L2.2/AA2-B). In the same gene, a Leu95Ser mutation of uncertain significance was reported in the second edition of the WHO mutation catalog (WHO, 2024).

In Asia Ancestral 3 (L2.2-AA3), we report seven clusters (Table 2) with four potential resistance-associated variants. Two are found in branch L2.2-AA3.1 (designated A and D) and two in branch L2.2-AA3.2 (CC1 and CC3), while other clonal complexes harbor only synonymous SNPs. In the L2.2-AA3.1 branch, the first cluster (AA3.1-A) consists of 19 SRAs sharing a mutation in *Rv1173* (Asp100Glu, 1303229:C:A), exclusively found in Chinese isolates from 4 Bioprojects. A second cluster

(AA3.1-B) is composed of 18 SRAs, harbouring a SNP in *Rv1453*, and is found in China, the USA and Australia from five Bioprojects. A third cluster (AA3.1-C) consists of 56 SRAs harbouring a SNP in *Rv1173*, and is found in Vietnam, Australia, Canada, the USA and Switzerland from approximately 20 Bioprojects. A fourth and last cluster comprises 25 SRAs, of which only have known geographical origin (one in the USA one from Liberia); the remaining SRAs are geographically but share a Gly173Ser (non snonymous SNP) in *ResR*.

In the L2.2-AA3.2 branch, we first found 106 SRAs (AA3.2-CC1), mainly from Nepal (half of the SRA), China (n = 13) and India (n = 11). This clonal complex harbors a Glu55Asp mutation in *Rv0678*. that is always correlated to resistance to INH, RIF, EMB, PZA, at least in Eastern India and Nepal (PRJNA896734 and 16 other bioprojects). A second cluster (AA3.2-CC2) in the same branch concerns 22 SRAs harbouring a synonymous SNP in *Rv1453* and is found in Vietnam, Australia and Thailand. The third one (AA3.2-CC3) concerns 23 SRAs harbouring a non-synonymous SNP (nsSNP) in *Rv3261* (*fbiB*; 3,641,065:G:A Arg175His). Among these 23 SRAs, 6 were from a single patient known to have developed XDR-TB in Switzerland by successive drug-resistance mutations acquisition (Bloemberg et al., 2015).

### 3.2. Analysis of other association between potential RAV and Lineage 2 Modern sublineages

We obtained a total of 31 nsSNPs potentially associated with resistance in the modern Lineage 2 sublineages, out of a total of 50 total variants detected (see Table 2).

The acquisition of a premature stop codon was observed in three potential RAVs: each linked to a specific sublineage:

* in the L2.2.1/M3 sublineage a Tyr194* mutation in *Rv1453* (associated with clofazimine resistance) was found in 33 SRAs;

* in the L2.2.1/M1 sublineage a Gln378* mutation in *Rv1453* was detected in 27 SRAs

* in the L2.2.1/M4.5.1 (Central Asian Outbreak) sublineage, a Trp88* mutation in *ddn* (associated with delamanid and pretomanid resistance) was present in 148 SRAs

Another potential RAV was identified in 24 SRAs belonging to a L2.2.1.1/M1 cluster: a frameshift mutation (p.Ala274fs) in the *Rv1453* gene, implicated in clofazimine (CFZ) resistance.

While Table 2 presents several other potential RAVs involving novel missense mutations, their functional consequences will not be explored in this study. Instead, we will focus on the SPDI 3339291:A:C mutation in the *fbiD* gene, which is responsible of the Ile59Leu change in the *fbiD* protein, due to its strinking evolutionary and taxonomic characteristics.

### 3.3. In-depth characterization of the new L2.2-M7 lineage not fitting within the current L2 Modern taxonomy

During our investigation, we identified two notable sets of SRAs carrying non-synonymous variants in the *fbiD* gene. One set consisted of 62 SRAs, found in Armenia and Georgia which was ultimately assigned to Clade A (L2 M4.9.2) (see Table 2). The second cluster comprised 49 SRAs that shared 4 SNPs including the SPDI 3339291:A:C mutation, which resulted in an Ile59Leu substitution in *fbiD* (Table 2). We then attempted to assign these SRAs to the current classification of Modern Beijing L2.2. All 49 SRAs — whose evolutionary study will be reconstructed in detail below— can initially be classified as L2.2 since they all possess the complete set of 25 mutations characteristic of the L2.2 lineage (Supplementary Table 2) (Thawornwattana et al., 2021; Shitikov et al., 2024) except for one isolate, (SRR6824304), which lacks only a single mutation (NC_000962.3:1849050:C:T). More precisely, they can be further assigned as L2.2.1 as they all share the 11 characteristic mutations defining this sublineage (Supplementary Table 2), except for one isolate (SRR15316313), which is missing only one mutation
(NC_000962.3:2825580:T:G).

Additionally, they can be further classified as L2.2.1 Modern since they all exhibit the eight characteristic mutations of this sublineage (Supplementary Table 2). Subsequently, they can also be assigned to the L2.2.1.1 sublineage, based on presence of three hallmark mutations specific to this group and finally, they can be assigned to L2.2.1.1.1 sublineage as they all harbor a final set of three mutations specific to this

modern L2 sublineage (Supplementary Table 2). However, it is not possible to assign a more precise clonal identification for these 49 SRAs, as none of the three SNPs allowing classification within either the L2.2.1.1.1-i1, -i2 or -i3 evolutionary branches described by Freschi et al., were present in this new taxon. Moreover, none of the specific SNPs defining any of the L2.2 M1 to M6 lineages were found in these clustered isolates (Thawornwattana et al., 2021; Shitikov et al., 2024).

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** RAxML phylogenetic trees constructed on 368 L2 SRAs representative of the global diversity of L2, with the display of the new L2.2-M7 branch, as opposed to all other modern or ancient branches described so far. 1A: phylogenetic tree build using the classical GTR + G model based on the SNPs matrix; 1B: phylogenetic tree build using all markers BIN+G model, as described in the Material and Methods section. The L2.2 M7 Chinese-Canadian branch is shown with pink dots and a red dotted line. The position of other lineages is also highlighted and named. The position of L2.1 (ProtoBeijing lineage) is not shown in Fig. 1B. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)</figcaption></figure>
Consequently, we found that the new L2.2-M7 sublineage includes 1,288,698 G/A, a marker described recently as diagnostic for L2.2 *ancient*. The same SRA cluster was, however, also presents the 1,477,596C/T variant, previously reported as characteristic of L2.2 modern, according to a recent L2 fine-scale taxonomic scheme (Shitikov et al., 2024). This discrepancy illustrates the difficulty of assigning a given marker to its evolutionary status within L2 modern sublineages. Based on this evidence, we propose that these 49 SRAs, from China (n = 36), from Canada (n = 2), from Vietnam (n = 1), and from unknown origin (n = 10), represent a new and emerging sublineage of a Beijing, which we designate as L2.2-M7.

### 3.4. Detailed description of the L2.2.1-M7 sublineage and of its defining SNPs

In addition to the previously described SNP markers, these 49 SRAs belonging to L2.2-M7 shared the following characteristics:

* in *Rv2983* (*fbiD*, 3339292:A:C; SPDI NC_000962.3:3339291:A:C) all share the missense mutation p.Ile59Leu which may be linked to PRM/DLM drug-resistance.

* in *Rv1859* (*modC*, 2106715:C:T; SPDI NC_000962.3:2106714:C:T), all carry the missense p.Leu48Phe. ModC encodes an ABC (ATP-binding cassette) transporter that could be associated to antimicrobial efflux.

* in *Rv3751* (4198938:C:T; SPDI NC_000962.3:4198937:C:T), all share a C to T variant located within a 216 bp gene fragment encoding a probable integrase (Mycob browser annotation, https://mycob browser.epfl.ch).

* in *Rv1862* (adhA, 2109907:C:G; SPDI NC_000962.3:2109906:C:G) all carry the missense mutation, p.Leu122Val in a putative alcohol dehydrogenase gene.

Two additional SNPs were present in all isolates except one: NC_000962.3:640416:C:T was found in all isolates but SRR6824691, whereas SPDI NC_000962.3:3871975:A:G was found in all but SRR6824304. Finally, all 49 isolates shared a synonymous T > C substitution in *Rv0407* (*fgd1*; 491,742:T:C or SPDI: NC_000962.3:491741:T:C), which can be seen as a marker observed across all MTBC lineages except Lineage 4 and Lineage 7.

### 3.5. Detailed analysis and phylogenetic structure of the L2.2-M7 sublineage

Fig. 1A and B present the respective phylogenetic trees constructed using two different models: the classical GTR + G model based on a SNPs-only pairwise distance matrix including all L2 isolates (Fig. 1A), and the BIN+G model incorporating all polymorphic markers (Fig. 1B). There is an excellent congruence between the two models and the resulting trees. Regardless of the alignment method used, the 49 SRAs do not cluster with any previously described modern L2 lineages.

A detailed close-up of the L2.2-M7 branch structure is provided in Fig. 2. It reveals two main branches: one comprising only three SRAs (designated M7.1), and another containing 46 SRAs (M7.2). Since L2.2-M7.1 is composed of only three SRAs and branches early in the tree, we hypothesize that this cluster may represent a non-epidemic remnant lineage undergoing extinction. The characteristic SNPs defining L2.2-M7 and its sublineages (M7.1, M7.2, and their respective sub-branches) are detailed in Supplementary Table 5.

A synthesis on the L2.2-M7 structure is presented in Table 3, with a total of 11 nested clusters. When comparing intra-cluster distances among all the M7 subclusters, characteristic features emerge. Assuming a mean mutation rate of 0.5 SNP per genome per year — a quite fast mutation rate—the emergence of L2.2-M7 could date back to the early 18th century (circa 1725 CE) though with uncertainty due to the time-dependence of mutation rates, as demonstrated in closely related

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Close-up of Fig. 1A showing the detailed structure of sublineages of L2.2-M7 with two main branches (M7–1 and M7–2) and other identified clonal complexes.</figcaption></figure>
bacterial genomes (Rocha et al., 2005).

A single subcluster (M7.2.1.2.2.1) composed of two SRAs displays a distance of only three SNPs, suggesting a recent epidemiological transmission event (Walker et al., 2013). The second most homogeneous cluster, M7.2.2.1, consists of 15 isolates with an intra-cluster distance of 33 +/− 17 SNPs — a low value, comparable to the intra-cluster distances observed in a recent study of an emerging hypervirulent cluster (14717–15 of the Asia Ancestral 3 Beijing sublineage in the Asian part of Russia; Mokrousov et al., 2023). M7.2.2.1 is part of a larger cluster, M7.2.2, which includes two additional isolates sharing a recent common ancestor, and may have emerged approximately 100 years ago (Table 3). M7.2.1 is a cluster of 28 clinical isolates estimated to have emerged earlier (approximately 276 years ago). The addition of new isolates in the future may help to elucidate the molecular evolution of L2.2-M7 sublineage.

## 4. Discussion

The introduction of new antituberculous drugs—BDQ, PRM/DLM, and LZD—has revolutionized the treatment paradigm of MDR-TB enabling effective oral regimens with treatment durations as short as six months (Haley et al., 2021). These regimens are especially recommended for TB cases caused by L2 strains, which are known for their resistance to first-line drugs (He et al., 2022). However, resistance to these new drugs is now also emerging (Hu et al., 2025). To improve our understanding of the genetic variability of 14 genes associated with resistance to these new and repurposed drugs in the treatment of MDR and XDR-TB, we systematically reviewed genetic variants potentially associated with resistance by interrogating the *TB-Annotator* database for associations between variants in 14 genes and the L2 lineage and its sublineages. Publicly available SRAs enabled the identification of a new sublineage—L2.2-M7—among 65 significant MDR/pre-XDR clonal complexes, based on a non-synonymous SNP in the *fbiD* gene. This sublineage comprises 49 SRAs that do not belong to any of the acknowledged ancient or modern (M1–M6) L2. All isolates of L2.2-M7 harbor a Ile59Leu amino-acid substitution in *fbiD* that could be involved in PRM/DLM resistance (Rifat et al., 2020). However, this hypothesis requires to be tested, either by predictive structural modeling methods or by laboratory phenotypic drug-susceptibility testing (Abramson et al., 2024a; The CRyPTIC Consortium, 2022). FbiD acts as a phosphoenol-pyruvyl-transferase, responsible of the synthesis of the F420 co-factor that is required for activation of nitro-imidazoles. A mutation in this gene could either decrease or even lead to the loss of the production of F420, thus conferring resistance to nitroimidazoles, such as PRM/DLM. Alternatively, it may induce increased oxidative stress without causing a significant loss of fitness *in vivo*.

A Leu48Phe missense SNP was also identified in *Rv1859*, encoding an ATP-binding cassette transporter of molybdate. This mutation could change the binding properties of ATP to the transporter, and this may act on MoO₄²⁻ transport and thus on Mo-dependent enzymes such as nitrate reductase, or other enzymes involved in hypoxic respiration. As such, its impact likely relates more to metabolic and redox adaptation than directly to drug resistance. Similarly, the Leu122Val change in ModC could modulate the activity of a Zn²⁺-class alcohol-dehydrogenase and of F420 dependent redox reactions. The two subbranches of L2.2-M7 show that many non-synonymous mutations appeared independently in each phylogenetical branch (17 in L2.2 M1 and 12 in L2.2 M7.2) (see also Supplementary Table 5). We do not know yet whether the emergence of these SNP in L2.2 M7.2 was responsible for a selective advantage and for their epidemic success (46 SRAs in L2.2 M7.2 against 3 SRAs in L2.2 M7.1), if this disquilibrium is due to different phylodynamics of equally fit clones, or is simply due to a recruitment bias.

We found in the *TB-Annotator* database that almost 10 % of the SRAs harbor mutations in the *Rv1830* gene, a ubiquitous regulator (Liu et al., 2022). ResR is a transcriptional merR type regulator that could act in cascade to regulate drug-related genes (Brown et al., 2003; Chiner-Oms

et al., 2022; Liu et al., 2022). Liu et al. described mutations affecting the structure of this regulator, and we confirm in a new unpublished study not only the presence of previously described *resR* variants but also the emergence of novel ones (*C. Sola*, unpublished results). We believe that the new L2.2-M7 taxon was worth describing for two main reasons. First, it underscores the necessity of regularly updating the L2 classification, as this taxon does not align with any existing scheme including the most recent one based on over 4000 SRAs from 34 countries (Thawornwattana et al., 2021; Shitikov et al., 2024). Second, this new taxon carries mutations in genes that could affect the efficacy of the new nitroimidazole derivatives. The *fbiD* gene is now acknowledged to be a major determinant of resistance to pretomanid and delamanid; loss of function mutations or substitutions in this gene disrupt F420 biosynthesis, thereby inhibiting prodrug activation (Rifat et al., 2020). The *modC* gene provides the molybdopterin cofactors essential for nitrate reductase activity. Under hypoxic conditions, such as those found in caseous lesions, MTBC relies on nitrate respiration for survival. A mutation in this gene (L48F) could alter the ATP-binding domain or alternatively create a fine-tuning of molybdate flux to compensate for the F420 deficit (since F420 is also used for nitrate metabolism); alternatively, it may create a metabolic bypass aimed at maintaining energy despite alterations in the cofactor. The *adhA* gene encodes a Zn²⁺ alcohol dehydrogenase, sometimes reported as secondary-F420-dependent. The L122V change, within the hydrophobic core, could adjust the enzyme's stereospecificity or compensate for the collateral effects of F420 deficiency by rebalancing NAD(P)H, or act on tolerance to *in situ* reactive compounds.

These isolates have been isolated so far in three regions of China, and in Canada. They do not seem to show geographical specificity, nor to be expanding. However more data need to be collected. It remains possible that other MDR or XDR-TB clones of public health concern could emerge in the future, especially as the fitness of certain new variants could be as fit as drug-susceptible ones, like it was shown in the past for some rifampicin-resistant clones (Gagneux et al., 2006). Molecular adaptation in compensatory genes as found in the L2 M4.9.1 sublineage, could also increase (Merker et al., 2018). Any potential RAV should be investigated through population genetics (Nimmo et al., 2024) and genome-wide association studies to search for phenotype/genotype correlation (The CRyPTIC Consortium, 2022). Nimmo et al. by compiling a large dataset of almost 4000 genomes, detected a large set (around 200) of mmpR5 promoter and adjacent mmpL5 gene variants. These variants have been shown to be associated to BDQ resistance. Nimmo et al. studied the occurrence of all non-synonymous mutations found in mmpR5 and they identified a number of cases where RAVs were likely to have been present in the genomes prior to the use of BDQ in TB treatment regimes. Some historical reservoirs of potentially BDQ resistant variants could antedate the introduction of BDQ and could be lineage-dependent (Nimmo et al., 2024). Epistatic interactions between genes could also hinder BDQ drug-susceptibility prediction using WGS data. Concerning the resistance to DLM and PTM, by applying a multistep computational pipeline, Chakraborty et al. ranked the mutations in F420 genes that are associated to resistance, and study both drug-binding regions and their relations to mutations on the conformational stability of the target protein (Chakraborty et al., 2025).

Since no study had tried to link L2 intra-lineage taxonomy to potential resistance-associated variants (RAV) emergence so far, we performed this systematic analysis in ancient and modern Beijing sublineages. During this study, we found a new clonal complex of MTBC that was detected thanks to the detection of these potential RAV. We describe a quite exhaustive set of >300 SNPs that allows a hierarchical assignation of these isolates. One limitation of this study is that we were unable to look further back and to detect a recent common ancestor between L2.2 M7 and the L2.2 M1-M6 sublineages, leaving this evolutionary question open.

The results reported in this study suggest that the L2 classification should be revised regularly to cope with the emergence of new MDR-TB
and pre-XDR or XDR-TB clones. It was indeed expected that the most recent genome-based taxonomy of L2 based on 4000 genomes could overlook certain genomes, particularly from China, where MTBC genomes were still scarce in public databases as of 2021 (Thawornwattana et al., 2021). Although over 4000 genomes were used to build the L2 taxonomy, this number was insufficient to fully capture the existing genetic diversity and global representation of L2 in terms of current population structure, especially when assessing drug-resistant clones. Our discovery was made possible through the use of *TB-Annotation* v2.5 (125,000 SRAs), a new interactive database that we created to improve public health and academic research to help in TB elimination and improve research on the genetics of resistance to new TB drugs (Senelle, 2024). *TB-Annotation* (https://gnksoftware.synology.me:30002/login) is currently freely available after registration and a new server is going to be launched. Given the increase in WGS data we hope to release regular updates of this database to allow researchers to perform various queries on SRA, on gene variants, and to build customized phylogenies on MTBC SRAs. This tool will help to identify new historical or epidemiological TB transmission cases using a very large database of published sequences (the NCBI SRA repository and the european EBI).

A last undiscussed issue concerns the phenotypic consequences of SNP variation, that could be assessed using drug-target structural studies using protein structure prediction (Abramson et al., 2024a, 2024b) and by protein-protein interactions network analysis (Szklarczyk et al., 2023). The four signature mutations in L2.2 M7 are all non-synonymous and converge on the same theme: metabolic redox adaptation in a context of recent antibiotic pressure from nitroimidazoles. The 159L substitution in *fbiD* could also be consistent with pre-existing resistance to BPAL treatments (also shown by the inference on intra-cluster SNPs divergence time), while variants in *modC* and *adhA* could compensate for redox imbalances and support survival in hypoxia. Taken together, our results create new phylogenetic barcodes and could also represent a therapeutic warning signal calling for the integration of these markers into monitoring tools and/or trigger drug-regimen changes in cases infected by this sublineage. With only 50 isolates, it is too early to try to reconstitute the spreading history of L2.2 M7. However, during the revision process of this article, we found in an updated *TB-Annotation* v3.1 (C. Le Carpentier, et al. personal communication) that there are indeed new cases of L2.2 M7 that were detected in Japan (3 cases), in United Kingdom (1) and in the United States of America (1).

## Author contribution

CG, EC and CS conceived the study. CG wrote the python scripts required for TB-Annotation RAV extraction. MAS, CS, performed the research and data analysis in *TB-Annotation*, phylogenetic building and complementary research. CA, MA, FM, ZA and CA provided support to MAS. CS wrote the first draft. MAS, EC, CG revised the draft. EC provided financial support and coordination. The final draft received approval from all authors.

## CRediT authorship contribution statement

**Marianne Antar Soutou:** Writing - review & editing, Methodology, Formal analysis.
**Camille Allam:** Project administration, Investigation.
**Marianne Abi Fadel:** Supervision.
**Josette Najjar:** Supervision, Christophe Guyeux: Writing - review & editing, Validation, Software, Methodology, Investigation, Formal analysis, Conceptualization.
**Emmanuelle Cambau:** Writing - review & editing, Supervision, Resources, Project administration, Funding acquisition, Conceptualization.
**Christophe Sola:** Writing - review & editing, Writing - original draft, Validation, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization.

## Declaration of competing interest

All authors declare that they have no conflict of interest.

This study was partly supported by Fondation Mérieux, Lyon, France, through a grant support to Mrs. Marianne Antar Soutou.

The authors declare that the founder did not have any influence in the investigation choices, nor on the management or on the decision to publish or not the results of this research, that only reflects the opinion of the authors.

## Acknowledgements

We are grateful to all the research teams, in particular from China, Vietnam and Canada, that submitted their SRAs to the NCBI, allowing such research to be done, and to Pr. Prasit Palittapongarnpim for very useful comments before submission. Marianne Antar-Soutou, PhD student supported by the Fondation Mérieux, is grateful to Dr. Laurent Raskine, Fondation Mérieux, Paris, France, for scientific, technical and financial support.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.meegid.2025.105797.

## Data availability

All data are either public or available within the paper as Tables or Figures or as Supplementary Tables.

TB-Annotation is accessible *via* the www at: http://gnksoftware.synology.me:30002/.

We also declare that this paper was not written with any help of any Artificial Intelligence software.

## References

Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A.J., Bambrick, J., Bodenstein, S.W., Evans, D.A., Hung, C.C., O'Neill, M., Reiman, D., Tunyasuvunakool, K., Wu, Z., Zemgulyte, A., Arvaniti, E., Beattie, C., Bertolli, O., Bridgland, A., Cherepanov, A., Congreve, M., Cowen-Rivers, A.I., Cowie, A., Figurnov, M., Fuchs, F.B., Gladman, H., Jain, R., Khan, Y.A., Low, C.M.R., Perlin, K., Potapenko, A., Savy, P., Singh, S., Stecula, A., Thillaisundaram, A., Tong, C., Yakneen, S., Zhong, E.D., Zielinski, M., Zidek, A., Bapst, V., Kohli, P., Jaderberg, M., Hassabis, D., Jumper, J.M., 2024a. Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 630, 493-500.

Abramson, J., Adler, J., Dunger, J., Evans, R., Green, T., Pritzel, A., Ronneberger, O., Willmore, L., Ballard, A.J., Bambrick, J., Bodenstein, S.W., Evans, D.A., Hung, C.C., O'Neill, M., Reiman, D., Tunyasuvunakool, K., Wu, Z., Zemgulyte, A., Arvaniti, E., Beattie, C., Bertolli, O., Bridgland, A., Cherepanov, A., Congreve, M., Cowen-Rivers, A.I., Cowie, A., Figurnov, M., Fuchs, F.B., Gladman, H., Jain, R., Khan, Y.A., Low, C.M.R., Perlin, K., Potapenko, A., Savy, P., Singh, S., Stecula, A., Thillaisundaram, A., Tong, C., Yakneen, S., Zhong, E.D., Zielinski, M., Zidek, A., Bapst, V., Kohli, P., Jaderberg, M., Hassabis, D., Jumper, J.M., 2024b. Addendum: accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature 636, E4.

Almeida, D., Ioerger, T., Tyagi, S., Li, S.Y., Mdluli, K., Andries, K., Grosset, J., Sacchettini, J., Nuermerberger, E., 2016. Mutations in pepQ confer low-level resistance to bedaquiline and clofazimine in *Mycobacterium tuberculosis*. Antimicrob. Agents Chemother. 60, 4590-4599.

Beckert, P., Hillemann, D., Kohl, T.A., Kalinowski, J., Richter, E., Niemann, S., Feuerriegel, S., 2012. rplC T460C identified as a dominant mutation in linezolid-resistant *Mycobacterium tuberculosis* strains. Antimicrob. Agents Chemother. 56, 2743-2745.

Bloemberg, G.V., Keller, P.M., Stucki, D., Trauner, A., Borrell, S., Latshang, T., Coscolla, M., Rothe, T., Homke, R., Ritter, C., Feldmann, J., Schulthess, B., Gagneux, S., Bottger, E.C., 2015. Acquired resistance to bedaquiline and delamanid in therapy for tuberculosis. N. Engl. J. Med. 373, 1986-1988.

Brosch, R., Gordon, S.V., Marmiesse, M., Brodin, P., Buchrieser, C., Eigelmeier, K., Garnier, T., Gutierrez, C., Hewinson, G., Kremer, K., Parsons, L.M., Pym, A.S., Samper, S., van Soolingen, D., Cole, S.T., 2002. A new evolutionary scenario for the *Mycobacterium tuberculosis* complex. Proc. Natl. Acad. Sci. USA 99, 3684-3689.

Brown, N.L., Stoyanov, J.V., Kidd, S.P., Hobman, J.L., 2003. The MerR family of transcriptional regulators. FEMS Microbiol. Rev. 27, 145-163.
Camus, J.C., Pryor, M.J., Medigue, C., Cole, S.T., 2002. Re-annotation of the genome sequence of *Mycobacterium tuberculosis* H37Rv. *Microbiology* 148, 2967-2973.

Cevik, M., Thompson, L.C., Upton, C., Rolla, V.C., Malahleha, M., Mmbaga, B., Ngubane, N., Abu Bakar, Z., Rassool, M., Variava, E., Dawson, R., Staples, S., Lalloo, U., Louw, C., Conradie, F., Eristavi, M., Samoiloa, A., Skornyakov, S.N., Ntinginya, N.E., Haraka, F., Praygod, G., Mayanja-Kizza, H., Caoili, J., Balanag, V., Dalcolmo, M.P., McHugh, T., Hunt, R., Solanki, P., Bateson, A., Crook, A.M., Fabiane, S., Timm, J., Sun, E., Spigelman, M., Sloan, D.J., Gillespie, S.H., Simplici, T. B.C., 2024. Bedaquiline-pretomanid-moxifloxacin-pyrazinamide for drug-sensitive and drug-resistant pulmonary tuberculosis treatment: a phase 2c open-label, multicentre, partially randomised controlled trial. *Lancet Infect. Dis.* 24, 1003-1014.

Chakraborty, G., Kolpe, M.S., Nath, I.V.A., Tiwari, A., Jayaswal, P., Patra, N., 2025. Computational structure-guided approach to simulate delamidation and pretomanid binding to mycobacterial F420 redox cycling proteins: identification of key determinants of resistance. *J. Biomol. Struct. Dyn.* 1-21.

Chiner-Oms, A., López, M.G., Moreno-Molina, M., Furió, V., Comas, I., 2022. Gene evolutionary trajectories in *Mycobacterium tuberculosis* reveal temporal signs of selection. *Proc. Natl. Acad. Sci. USA* 119, e2113600119.

Chitale, P., Lemenze, A.D., Fogarty, E.C., Shah, A., Grady, C., Odom-Mabey, A.R., Johnson, W.E., Yang, J.H., Eren, A.M., Brosch, R., Kumar, P., Alland, D., 2022. A comprehensive update to the *Mycobacterium tuberculosis* H37Rv reference genome. *Nat. Genet.* 13, 7068.

Cole, S.T., Barell, B.G., 1998. Analysis of the genome of *Mycobacterium tuberculosis* H37Rv. In: *Wiley (Ed.), Genetics and Tuberculosis*. Novartis Foundation Symposium, Chichester, pp. 160-177.

Comas, I., Coscolla, M., Luo, T., Borrell, S., Holt, K.E., Kato-Maeda, M., Parkhill, J., Malla, B., Berg, S., Thwaites, G., Yeboah-Manu, D., Bothamley, G., Mei, J., Wei, L., Bentley, S., Harris, S.R., Niemann, S., Diel, R., Aseffa, A., Gao, Q., Young, D., Gagneux, S., 2013. Out-of-Africa migration and neolithic coexpenditure of *Mycobacterium tuberculosis* with modern humans. *Nat. Genet.* 45, 1176-1182.

Coscolla, M., Gagneux, S., Menardo, F., Loiseau, C., Ruiz-Rodriguez, S., Borrell, S., Otchere, I.D., Asante-Poku, A., Asare, P., Sanchez-Buso, L., Gehre, F., Sanoussi, C.N., Antonio, M., Affolabi, D., Fyfe, J., Beckert, P., Niemann, S., Alabi, A.S., Grobusch, M. P., Kobbe, R., Parkhill, J., Beisel, C., Fenner, L., Bottger, E.C., Meehan, C.J., Harris, S. R., de Jong, B.C., Yeboah-Manu, D., Brites, D., 2021. Phylogenomics of *Mycobacterium africanum* reveals a new lineage and a complex evolutionary history. *Microb. Genom.* 7, 000477.

Freschi, L., Vargas Jr., R., Husain, A., Kamal, S.M.M., Skrahina, S., Ismail, N., Barbova, A., Niemann, S., Cirillo, D.M., Dean, A.S., Zignol, M., Farhat, M. M., 2021. Population structure, biogeography and transmissibility of *Mycobacterium tuberculosis*. *Nat. Commun.* 12, 6099.

Gagneux, S., Long, C.D., Small, P.M., Van, T., Schoolnik, G.K., Bohannan, B.J., 2006. The competitive cost of antibiotic resistance in *Mycobacterium tuberculosis*. *Science* 312, 1944-1946.

Guyeux, C., Senelle, G., Refrégier, G., Bretelle-Establet, F., Cambau, E., Sola, C., 2022. Connection between two historical tuberculosis outbreak sites in Japan, Honshu, by a new ancestral *Mycobacterium tuberculosis* L2 sublineage. *Epidemiol. Infect.* 150, 1-10.

Guyeux, C., Senelle, G., Le Meur, A., Supply, P., Gaudin, C., Phelan, J.E., Clark, T.G., Rigouts, L., de Jong, B., Sola, C., Refregier, G., 2024. Newly identified *Mycobacterium africanum* lineage 10, Central Africa. *Emerg. Infect. Dis.* 30, 560-563.

Haley, C.A., Macias, P., Jasuja, S., Jones, B.A., Rowlinson, M.C., Jaimon, R., Onderko, P., Darnall, E., Gomez, M.E., Peloquin, C., Ashkin, D., Goswami, N.D., 2021. Novel 6-month treatment for drug-resistant tuberculosis, United States. *Emerg. Infect. Dis.* 27, 332-334.

Hartkoorn, R.C., Uplekar, S., Cole, S.T., 2014. Cross-resistance between clofazimine and bedaquiline through upregulation of Mml5 in *Mycobacterium tuberculosis*. *Antimicrob. Agents Chemother.* 58, 2979-2981.

Haver, H.L., Chua, A., Ghode, P., Lakshminarayana, S.B., Singhal, A., Mathema, B., Wintjens, R., Bifani, P., 2015. Mutations in genes for the F420 biosynthetic pathway and a nitroreductase enzyme are the primary resistance determinants in spontaneous in vitro-selected PA-824-resistant mutants of *Mycobacterium tuberculosis*. *Antimicrob. Agents Chemother.* 59, 5316-5323.

He, W., Tan, Y., Liu, C., Wang, Y., He, P., Song, Z., Liu, D., Zheng, H., Ma, A., Zhao, B., Ou, X., Xia, H., Wang, S., Zhao, Y., 2022. Drug-resistant characteristics, genetic diversity, and transmission dynamics of rifampicin-resistant *Mycobacterium tuberculosis* in Hunan, China, revealed by whole-genome sequencing. *Microbiol. Spectr.* 10, e0154321.

Holmes, J.B., Moyer, E., Phan, L., Maglott, D., Kattman, B., 2020. SPDI: data model for variants and applications at NCBI. *Bioinformatics* 36, 1902-1907.

Hu, X., Wu, Z., Lei, J., Zhu, Y., Gao, J., 2025. Prevalence of bedaquiline resistance in patients with drug-resistant tuberculosis: a systematic review and meta-analysis. *BMC Infect. Dis.* 25, 689.

Kadura, S., King, N., Nakhoul, M., Zhu, H., Theron, G., Koser, C.U., Farhat, M., 2020. Systematic review of mutations associated with resistance to the new and repurposed *Mycobacterium tuberculosis* drugs bedaquiline, clofazimine, linezolid, delamidan and pretomanid. *J. Antimicrob. Chemother.* 75, 2031-2043.

Kozlov, A.M., Darriba, D., Flouri, T., Morel, B., Stamatakis, A., 2019. RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. *Bioinformatics* 35, 4453-4455.

Li, H., Durbin, R., 2009. Fast and accurate short read alignment with burrows-wheeler transform. *Bioinformatics* 25, 1754-1760.

Li, Y., Fu, L., Zhang, W., Chen, X., Lu, Y., 2021. The transcription factor Rv1453 regulates the expression of qor and confers resistant to Clofazimine in *Mycobacterium tuberculosis*. *Infect. Drug Resist.* 14, 3973-3948.

Liu, Q., Zhu, J., Dulberger, C.L., Stanley, S., Wilson, S., Chung, E.S., Wang, X., Culviner, P., Liu, Y.J., Hicks, N.D., Babunovic, G.H., Giffen, S.R., Aldridge, B.B., Garner, E.C., Rubin, E.J., Chao, M.C., Fortune, S.M., 2022. Tuberculosis treatment failure associated with evolution of antibiotic resilience. *Science* 378, 1111-1118.

Merker, M., Blin, C., Mona, S., Dufolet-Frebourg, N., Lecher, S., Willery, E., Blum, M.G., Rusch-Gerdes, S., Mokrousov, I., Aleksic, E., Allix-Beguec, C., Antierens, A., Augustnowicz-Kopec, E., Ballif, M., Barletta, F., Beck, H.P., Barry 3rd, C.E., Bonnet, M., Borroni, E., Campos-Herrero, I., Cirillo, D., Cox, H., Crowe, S., Crudu, V., Diel, R., Drobnowielski, F., Fauville-Dufaux, M., Gagneux, S., Ghebremichael, S., Hanekom, M., Hoffner, S., Jiao, W.W., Kalon, S., Kohl, T.A., Kontsevaya, I., Lillebaek, T., Maeda, S., Nikolayevskyy, V., Rasmussen, M., Rastogi, N., Samper, S., Sanchez-Padilla, E., Savic, B., Shamputa, I.C., Shen, A., Sng, L.H., Stakenas, P., Toit, K., Varaine, F., Vukovic, D., Wahl, C., Warren, R., Supply, P., Niemann, S., Wirth, T., 2015. Evolutionary history and global spread of the *Mycobacterium tuberculosis* Beijing lineage. *Nat. Genet.* 47, 242-249.

Merker, M., Barbier, M., Cox, H., Rasigade, J.P., Feuerriegel, S., Kohl, T.A., Diel, R., Borrell, S., Gagneux, S., Nikolayevskyy, V., Andres, S., Nubel, U., Supply, P., Wirth, T., Niemann, S., 2018. Compensatory evolution drives multidrug-resistant tuberculosis in Central Asia. *eLife* 7, e38200.

Mokrousov, I., Vyazovaya, A., Shitikov, E., Badleeva, M., Belopolskaya, O., Bespiatykh, D., Gerasimova, A., Ioanidisid, P., Jiao, W., Khromova, M., Masharsky, A., Naizabayeva, D., Papaventsis, D., Pasechensky, O., Perdigao, J., Rastogi, N., Shen, A., Sinkov, V., Skiba, Y., Solovieva, N., Tafaj, S., Valcheva, V., Kostyukova, I., Zhdanova, S., Zhuravlev, V., Ogarkov, O., 2023. Insight into pathogenomics and phylogeography of hypervirulent and highly-lethal *Mycobacterium tuberculosis* strain cluster. *BMC Infect. Dis.* 23, 426.

Napier, G., Campino, S., Merid, Y., Abebe, M., Woldeamanuel, Y., Aseffa, A, Hibberd, M. L., Phelan, J., Clark, T.G., 2020. Robust barcoding and identification of *Mycobacterium tuberculosis* lineages for epidemiological and clinical studies. *Genome medicine* 12, 114.

Nguyen, T.V.A., Anthony, R.M., Banuls, A.L., Nguyen, T.V.A., Vu, D.H., Alffenaar, J.C., 2018. Bedaquiline resistance: its emergence, mechanism, and prevention. *Clin. Infect. Dis.* 66, 1625-1630.

Nimmo, C., Ortiz, A.T., Tan, C.C.S., Pang, J., Acman, M., Millard, J., Padayatchi, N., Grant, A.D., O'Donnell, M., Pym, A., Brynildsrud, O.B., Eldholm, V., Grandjean, L., Didelot, X., Balloux, F., van Dorp, L., 2024. Detection of a historic reservoir of bedaquiline/clofazimine resistance-associated variants in *Mycobacterium tuberculosis*. *Genome Med.* 16, 34.

Pi, R., Liu, Q., Jiang, Q., Gao, Q., 2019. Characterization of linezolid-resistance-associated mutations in *Mycobacterium tuberculosis* through WGS. *J. Antimicrob. Chemother.* 74, 1795-1798.

Rifat, D., Li, S.Y., Ioerger, T., Shah, K., Lanoix, J.P., Lee, J., Bashiri, G., Sacchettini, J., Nuermberger, E., 2020. Mutations in fbiD (Rv2983) as a novel determinant of resistance to pretomanid and delamidan in *Mycobacterium tuberculosis*. *Antimicrob. Agents Chemother.* 65, 10-1128.

Rocha, E.P., Smith, J.M., Hurst, L.D., Holden, M.T., Cooper, J.E., Smith, N.H., Feil, E.J., 2005. Comparisons of dn/dS are time dependent for closely related bacterial genomes. *J. Theor. Biol.* 239, 226-235.

Senelle, G., 2024. Exploiter l'intégralité des données de séquénçage de *Mycobacterium tuberculosis*: une plateforme pour l'analyse génomique in-silico à grande échelle. *Département d'Informatique, Université de Franche-Comté, Besançon*, p. 177.

Senelle, G., Guyeux, C., Refregier, G., Sola, C., 2023a. Towards a better understanding of the long-lasting evolutionary history of *Mycobacterium tuberculosis*. *Tuberculosis* (Edinb.) 143, 102374.

Senelle, G., Guyeux, C., Refrégier, G., Sola, C., 2023b. TB-annotator: A Scalable Web Application that Allows in-Depth Analysis of Very Large Datasets of Publicly Available *Mycobacterium tuberculosis* Complex Genomes.

Shitikov, E., Bespiatykh, D., 2023. A revised SNP-based barcoding scheme for typing *Mycobacterium tuberculosis* complex isolates. *mSphere* 8 (e4), 00016923.

Shitikov, E., Kolchenko, S., Mokrousov, I., Bespiatykh, J., Ischenko, D., Iilina, E., Gorovin, V., 2017. Evolutionary pathway analysis and unified classification of East Asian lineage of *Mycobacterium tuberculosis*. *Sci. Rep.* 7, 9227.

Shitikov, E., Mokrousov, I., Bespiatykh, D., 2024. Phylogenomics of the East Asian lineage of *Mycobacterium tuberculosis*. In: *Igor Mokrousov, E.S. (Ed.), Phylogenomics. Academic Press*, pp. 323-343.

Szklarczyk, D., Kirsch, R., Koutrouli, M., Nastou, K., Mehryary, F., Hachilif, R., Gable, A. L., Fang, T., Doncheva, N.T., Pyysalo, S., Bork, P., Jensen, L.J., von Mering, C., 2023. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. *Nucleic Acids Res.* 51, D638-D646.

Thawornwattana, Y., Mahasirimongkol, S., Yanai, H., Myat Win Maung, H., Cui, Z., Chongsuvivatvong, V., Palittapongarnpim, P., 2021. Revised nomenclature and SNP barcode for *Mycobacterium tuberculosis* lineage 2. *Microb. Genom.* 7, 000697.

The CRyPTIC Consortium, 2022. Genome-wide association studies of global *Mycobacterium tuberculosis* resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms. *PLoS Biol.* 20, e3001755.

Viney, K., Linh, N.N., Gegia, M., Zignol, M., Glaziou, P., Ismail, N., Kasaeva, T., Mirzayev, F., 2021. New definitions of pre-extensively and extensively drug-resistant tuberculosis: update from the World Health Organization. *Eur. Respir. J.* 57.

Walker, T.M., Ip, C.L., Harrell, R.H., Evans, J.T., Kapatai, G., Dedicoa, M.J., Eyre, D.W., Wilson, D.J., Hawkey, P.M., Crook, D.W., Parkhill, J., Harris, D., Walker, A.S., Bowden, R., Monk, P., Smith, E.G., Peto, T.E., 2013. Whole-genome sequencing to delineate *Mycobacterium tuberculosis* outbreaks: a retrospective observational study. *Lancet Infect. Dis.* 13, 137-146.

Wares, D.F., Mbenga, M., Mirtskhulava, V., Quelapio, M., Slyzkyi, A., Koppelaar, I., Cho, S.N., Go, U., Lee, J.S., Jung, J.K., Everitt, D., Foraida, S., Diachenko, M.,
Juneja, S., Burhan, E., Totkogonova, A., Myint, Z., Flores, I., Lytvynenko, N.A., Parpieva, N., Nhung, N.V., Gebhard, A., 2024. Introducing BPaL: experiences from countries supported under the LIFT-TB project. PLoS One 19, e0310773.

WHO, 2024. Catalogue of Mutations in *Mycobacterium tuberculosis* Complex and their Association with Drug Resistance, second edition. WHO, Geneva, p. 129.

Zhang, Z., Pang, Y., Wang, Y., Liu, C., Zhao, Y., 2014. Beijing genotype of *Mycobacterium tuberculosis* is significantly associated with linezolid resistance in multidrug-resistant

and extensively drug-resistant tuberculosis in China. Int. J. Antimicrob. Agents 43, 231–235.

Zimenkov, D.V., Nosova, E.Y., Kulagina, E.V., Antonova, O.V., Arslanbaeva, L.R., Isakova, A.I., Krylova, L.Y., Peretokina, I.V., Makarova, M.V., Safonova, S.G., Borisov, S.E., Gryadunov, D.A., 2017. Examination of bedaquiline- and linezolid-resistant *Mycobacterium tuberculosis* isolates from the Moscow region. J. Antimicrob. Chemother. 72, 1901–1906.