Insights into Mycobacteriome Composition in Mycobacterium bovis-Infected African Buffalo (Syncerus caffer) Tissue Samples: A Culture-Independent Approach

Insights into Mycobacteriome Composition in Mycobacterium bovis-Infected African Buffalo (Syncerus caffer) Tissue Samples: A Culture-Independent Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Insights into Mycobacteriome Composition in Mycobacterium bovis-Infected African Buffalo (Syncerus caffer) Tissue Samples: A Culture-Independent Approach Giovanni Ghielmetti, Tanya J. Kerr, Netanya Bernitz, Sinegugu K. Mhlophe, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4329505/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Jul, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Animal tuberculosis significantly challenges global health, agriculture, and wildlife conservation efforts. Mycobacterial cultures necessitate stringent biosafety measures due to the risk of laboratory-acquired infections. In this study, we employed a culture-independent approach, using targeted long-read-based next-generation sequencing (tNGS), to investigate the mycobacterial composition in DNA extracted from Mycobacterium bovis infected culture-confirmed African buffalo tissue. We detected mycobacterial DNA in 93.3% of the samples and the sensitivity for detecting Mycobacterium tuberculosis complex (MTBC) was 91.7%, demonstrating a high concordance of our culture-independent tNGS approach with mycobacterial culture results. We identified heterogenous mycobacterial populations with various non-tuberculous mycobacteria, including members of the Mycobacterium avium complex, M. smegmatis , and M. komaniense . The latter Mycobacterium species was described in South Africa from bovine nasal swabs and environmental samples from the Hluhluwe-iMfolozi Park, which was the origin of the buffalo samples in the present study. This finding suggests that mycobacterial DNA found in the environment may confound detection of MTBC in wildlife. In conclusion, our approach represents an alternative to conventional methods for detecting mycobacterial DNA. This high-throughput technique enables the differentiation of heterogeneous mycobacterial populations and facilitates relative quantification, which will contribute valuable insights into the epidemiology, pathogenesis, and microbial synergy during mycobacterial infections. Biological sciences/Microbiology/Infectious disease diagnostics Biological sciences/Microbiology/Pathogens African buffaloes culture-independent mycobacteriome Mycobacterium bovis Oxford nanopore technology targeted next-generation sequencing Figures Figure 1 Figure 2 Figure 3 Introduction Animal tuberculosis (TB), caused by Mycobacterium bovis ( M. bovis ) and other members of the Mycobacterium tuberculosis complex (MTBC), is a threat to livestock and wildlife populations 1 , 2 . Among the diverse mycobacterial species, M. bovis is a significant pathogen capable of causing severe chronic infectious disease, particularly in animals such as African buffaloes ( Syncerus caffer ) 3 . African buffaloes are well-known wildlife maintenance hosts for M. bovis , contributing to the potential direct and indirect transmission of the pathogen to domestic livestock, other susceptible wildlife species like African lions ( Panthera leo ), rhinoceros ( Ceratotherium simum , Diceros bicornis ), African elephants ( Loxodonta africana ), and humans 4 – 7 . In African buffaloes, ante-mortem detection of infection is based on the in vivo or in vitro measurement of M. bovis antigen-specific cell-mediated immunological (CMI) responses, using the tuberculin skin test (TST) or the interferon-γ (IFN-γ) release assay (IGRA), respectively 8 , 9 . Although conventional TST uses purified protein derivatives (PPDs) from M. bovis and M. avium , in vitro cytokine stimulation assays have employed PPDs or mycobacterial peptides, such as early secretory antigen target 6 kDa (ESAT -6 ) and culture filtrate protein 10 kDa (CFP-10), for identifying infected individuals. Unfortunately, cross-reactive host responses to non-tuberculous mycobacteria (NTMs), especially when using PPDs to stimulate antigen-specific cell-mediated immunity (CMI) responses, lead to diagnostic interference 10 . Non-tuberculous mycobacteria, once considered benign environmental organisms prevalent in soil and water, are now recognized as potential pathogens with implications for human and animal health 11 . Infection with NTMs can cause diseases collectively referred to as mycobacteriosis, affecting not only humans but also various livestock and wildlife species 10 , 12 , 13 . Currently, the gold standard for definitive diagnosis and characterisation of M. bovis and other mycobacteria relies on culture-based methods, where bacterial isolates obtained from infected animals undergo phenotypic and genotypic analyses 14 . However, the application of mycobacterial culture may not be feasible, especially if samples originate from Foot-and-Mouth Disease (FMD) endemic areas. In South Africa, most of the FMD-endemic areas coincide with well-known M. bovis -endemic wildlife parks such as Hluhluwe-iMfolozi Park (HiP; KwaZulu-Natal Province) and Kruger National Park (KNP; Mpumalanga and Limpopo Provinces). In these regions, the movement of cloven-hooved animals including samples is subjected to regulatory restrictions. Consequently, the inability to transport samples from these FMD-endemic regions poses a significant obstacle to employing mycobacterial culture for M. bovis detection. As a result, there is a need for DNA-based culture-independent M. bovis diagnostic techniques as well as an unbiased approach to investigate complex host-mycobacterial interactions. To date, a few commercially available PCR assays have been reported to detect MTBC members and NTMs directly from animal specimens, including oronasal swabs, tissue homogenates, and respiratory secretions, including bronchoalveolar lavage samples. However, these assays cannot differentiate between the different members of the MTBC. Assays include but are not limited to the Xpert® MTB/RIF Ultra (Cepheid, Sunnyvale, California, USA) 15 , artus® M. tuberculosis PCR Kit (Qiagen, Venlo, Limburg, Netherlands) 16 , 17 , COBAS® TaqMan® MTB Test kit (Roche Diagnostics, Indianapolis, Indiana, United States) 18 , BactoReal® kit (Ingenetix, Vienna, Austria) 19 , and VetMAX™ M. tuberculosis Complex PCR Kit (Thermo Fisher Scientific, Waltham, Massachusetts, United States) 20 , 21 for MTBC DNA detection, and the Hain Geno-Type CM direct VER 1.0-line probe assay 5 for MTBC/NTM DNA detection and identification of commonly found NTM species in human clinical samples. The latter test, however, has been reported to be less successful when applied to samples that had not undergone prior culture 5 . In contrast, PCR amplification of housekeeping genes such as the beta subunit of RNA polymerase ( rpoB) , partial heat-shock protein ( hsp65) , and the Ku genes, in conjunction with amplicon sequencing, have successfully detected Mycobacterium genus DNA and provided species identification in ante-mortem samples from wildlife species, circumventing the need for culture-based methods 5 . However, these targets are unable to differentiate specific MTBC members and require an additional region-of-difference PCR (RD-PCR) for speciation 22 . Unfortunately, RD-PCRs were initially tailored for the identification of MTBC in mycobacterial cultures, posing significant challenges in adapting them for use with DNA extracted directly from samples 22 . Sequencing of selected genomic targets has shown promise as an alternative tool for discerning phylogenetically related slow-growing mycobacteria by interrogating DNA sequence polymorphisms 23 . Genes encoding DNA gyrase subunits gyrA and gyrB have demonstrated satisfactory discriminatory power, facilitating precise taxonomic resolution and classification of distinct MTBC members 24 , 25 . Despite being a sub-optimal gene target for Mycobacterium genus speciation, studies have demonstrated the advantages of using full-length 16S rRNA amplicon sequencing for taxonomic classification, as opposed to short-read amplicon sequencing 26 – 28 . Nonetheless, previous methods for high-throughput full-length 16S rRNA gene amplicon sequencing using Oxford Nanopore Technologies (ONT) technology often relied solely on reference database alignment 29 , 30 rather than employing de novo generation of sequence features, such as amplicon sequence variants (ASV) or operational taxonomic units (OTU). Currently, the generation of whole-genome sequences for epidemiological investigations of animal TB relies on mycobacterial culture; however, analyses can be impeded by the presence of other microorganisms that outcompete MTBC growth in culture 31 – 33 . Co-infections can also modulate immune response, particularly in infections with closely related microorganisms that share antigenic properties 34 . This study describes the use of a three- housekeeping-gene ( hsp65 , rpoB and 16S rRNA) in a culture-independent in-house multiplex PCR method, followed by single-nucleotide polymorphism (SNP) level MTBC confirmation ( gyrA and gyrB ), to identify and characterize all Mycobacteria spp . directly from culture-confirmed M. bovis infected tissue. Using a novel culture-independent targeted next-generation sequencing (tNGS) approach, we aimed to characterize the mycobacteriome, which refers to the community of mycobacteria present in a sample, of M. bovis infected tissue from African buffaloes. For this purpose, we applied a novel reference-free sorting tool 35 on ONT-sequenced amplicons and based on their similarity in sequence and length, we were able to build consensus sequences revealing the mycobacteriome present in each sample 36 . This approach contributes to the refinement of diagnostic strategies, enhancing our ability to comprehensively study the mycobacterial landscape in wildlife and ensuring the effective surveillance of M. bovis in regions where it poses a significant threat to both animal health and conservation efforts. Results A total of 60 tissue samples from 57 individual African buffaloes from the Hluhluwe-iMfolozi Park (HiP), South Africa (SA), were selected in the present study and included pooled head lymph nodes (n = 5), pooled thoracic lymph nodes (n = 7), lung tissue (n = 7), tonsil (n = 5), tracheobronchial lymp nodes (n = 12), mediastinal lymph nodes (n = 8), parotid (n = 4), retropharyngeal lymph nodes (n = 6), prescapular lymph nodes (n = 3), two mandibular lymph nodes, and one subiliac lymph node. All buffalo samples had previously been confirmed as infected using the aforementioned culture methods, and the presence of the M. bovis region of difference 4 (RD4) signature was confirmed from culture-positive crude DNA extracts 22 . Spacer oligonucleotide typing hybridization assay (spoligotyping) revealed that all samples fit one of two profiles, SB0130 (n=39) and SB1474 (n=21) (Suppl. Table 1). ONT targeted amplicon sequencing All samples showing amplification of >1 target gene were included for amplicon sequencing, whereas four samples (2 tonsils, one lung, and one parotid) for which none of the targets could be visualized after electrophoresis were excluded from downstream analysis. The hsp65, rpoB , and 16S rRNA gene regions were successfully amplified from 55 samples (Figure 1). One pooled head lymph nodes sample did not amplify the rpoB target. The number of reads per specimen with Q12 or greater ranged from 63,705 to 897,809 (Mean ( M ) = 320,985 reads, Standard Deviation (SD) = 154,129), and the total number of bases sequenced ranged from 38,921,972 to 554,606,081 ( M = 199,128,119 bases, SD = 95,521,803). The N50 read length (median read length of the longest contigs) varied from 558 to 781 bases. The mean read length for the samples ranged from 576 to 658 bases. The mean read quality, as indicated by the Phred score, ranged between 14.2 and 14.5. A total of 200,000 reads with >Q12 were randomly selected from each sample for downstream analysis (Figure 2). Since amplification of the three main targets occurred in a single tube, PCR products amplified were not normalized, and therefore shorter sequences were predominant. The distribution of reads for each target varied, with hsp65 ranging from 31-79%, rpoB 2-30%, and 16S rRNA 1-8% of the selected reads (Table 1, Figure 3a). Table 1. Distribution of read counts for the seven African buffalo tissue samples (identification number in first row) where the presence of non-tuberculous mycobacteria or heterogeneous mycobacterial communities was identified. Reference-free sorting and assembly of consensus sequences were performed on a maximum of 200,000 randomly selected reads (>Q12) for each sample. For tissue samples with fewer reads, the entire available dataset was included. Reads were generated using Oxford Nanopore Technologies (ONT) on targeted amplified housekeeping genes shown in the first column. Reads that could not be assigned to any of the three targets were grouped as unclassified and excluded from downstream analysis. NB17057 parotid; NB17074 and KS19028 pooled head lymph nodes; NB17050 retropharyngeal lymph node; NB18206 subiliac lymph node; NB18261 mediastinal lymph node; NB18258 lung. NB17057 NB17074 NB17050 NB18206 NB18261 NB18258 KS19028 hsp65 38771 153928 101257 90572 119897 62228 159430 rpoB 1644 NA # 49733 49978 56224 53955 10135 16S rRNA 4791 9471 2876 3010 4725 2186 9757 unclassified 18499 36601 46134 33795 19154 81631 20678 Included for analysis 63705 200000 200000 177355 200000 200000 200000 Total number reads 63705 204856 230365 177355 351470 271981 249582 # For sample NB17074 no amplification was observed for rpoB . Mycobacteriome composition Evidence of Mycobacterium spp. DNA presence was detected in 93.3% (56/60) of the DNA samples extracted directly from tissue homogenates. Among the 56 samples subjected to amplicon generation and subsequent deep sequencing for the three targets, the rpoB PCR exhibited the highest sensitivity for MTBC detection (98.2%), followed by hsp65 (94.6%), and 16S rRNA (92.8%). The shorter target PCR ( hsp65 ) demonstrated the highest efficacy in detecting NTM and heterogeneous mycobacterial populations compared to alternative targets (Table 2), as well as closely related microorganisms such as Streptomyces sp. (Figure 3b). Table 2. Synopsis of the reference-free sorting and assembly outcomes of consensus sequences for the three Mycobacterium spp. target genes ( hsp65, rpoB , 16S rRNA) included in the culture-independent next-generation sequencing approach. The composition of the mycobacteriome varied depending on the three independent targets. Notably, the shorter target PCR ( hsp65 ) demonstrated the ability to identify the highest proportion of mycobacteria, with amplification and Mycobacterium spp. sequences detected in 93.3% of the samples tested (56/60). The rpoB PCR displayed the highest sensitivity for MTBC detection, identifying MTBC in 91.7% of all samples included (55/60). hsp65 rpoB 16S rRNA Mycobacterium tuberculosis complex (MTBC) 49 54 52 Non-tuberculous mycobacteria (NTM) 3 0 2 MTBC + NTM 4 1 0 Total 56 55 # 54 § # One sample could not be amplified using the rpoB target § For two samples (NB18154 and KS19028), the 16S rRNA consensus sequences were classified as organisms not belonging to the Mycobacterium genus. Further analysis using NCBI Basic Local Alignment Search Tool (BLAST) identified the presence of Niallia sp. in NB18154 and Streptomyces sp. in KS19028. Based on previous molecular analyses, which involved RD-PCRs and spoligotyping used to confirm the presence of M. bovis within the selected samples, our goal was to assess the ability of the novel culture-independent methodology to detect and speciate MTBC members. Using a subset of eleven tissue DNA samples, the g yrA and g yrB genes were amplified and sequenced on a single Flongle flow cell (ONT). The number of reads with Q12 or greater ranged from 118 to 1,918 ( M = 1,157 reads, SD = 489), and the total number of bases sequenced ranged from 20,411 to 328,224 ( M = 200,948 bases, SD = 85,764). The mean read quality, as indicated by the Phred score, was consistently above 13 (11/11). All reads with >Q12 quality scores were selected from each sample for downstream analysis. The three additional targets employed for confirming the presence of M. bovis DNA ( gyrA , gyrB1 , and gyrB2 ) were successfully amplified in all 11 selected samples. Specifically, the gyrA gene target amplicon sequences confirmed the presence of MTBC DNA in approximately three-quarters of the samples (8 out of 11), while gyrB1 and gyrB2 confirmed the RD and spoligotyping speciation results obtained from culture-derived DNA in all samples. For two samples (NB17057 and KS19028), however, the total number of reads (656 and 118) and the number of consensus sequences identified as MTBC in one or more targets (92 and 43) were lower compared to the corresponding mean values generated for the other samples (total number of reads 10,149). In addition to the detection of MTBC DNA, tNGS of the hsp65 gene successfully identified diverse mycobacterial species in different tissue specimens, including two pooled head lymph nodes, one lung, one mediastinal lymph node, one parotid, one retropharyngeal lymph node, and one subiliac lymph node. Mycobacterium avium complex (MAC) was detected in four samples (7.1%), M. smegmatis in two (3.6%), M. komaniense and an unclassified Mycobacterium sp. in one sample each (1.8%). Additionally, DNA of mycobacteria’s closely related organisms such as Streptomyces sp. were amplified and further identified using the hsp65 target gene (Figure 3b). In the DNA sample NB17074, originating from lung tissue, M. smegmatis was identified using hsp65 and 16S rRNA targets, but no amplification was observed using rpoB PCR. Conversely, in one retropharyngeal lymph node (sample NB17057), M. komaniense was detected using hsp65 and 16S rRNA PCRs, while MTBC DNA was detected using rpoB . At least two distinct strains of MAC were detected, exhibiting 15 genomic modifications, including single nucleotide variations and indels. These strains displayed the highest hsp65 sequence homology to M. avium and M. colombiense . The MAC sequences were exclusively detected in tissue samples exhibiting heterogeneous bacterial populations (4/4), including MTBC in three samples, and a combination of Streptomyces sp. and Mycobacterial sp. in one sample (Table 3). The samples originated from various locations including lung tissue, mediastinal lymph nodes, head lymph nodes, and subiliac lymph nodes. Finally, the relative abundance of reads classified as MAC varied between 0.3 and 17% for the hsp65 target in the above-mentioned samples (Figure 3b). Table 3. Percentage of hsp65 PCR target reads (%) indicating the presence of non-tuberculous mycobacteria or heterogeneous mycobacterial communities in each African buffalo tissue sample where the DNA of these organisms was detected. NB17057 parotid; NB17074 and KS19028 pooled head lymph nodes; NB17050 retropharyngeal lymph node; NB18206 subiliac lymph node; NB18261 mediastinal lymph node; NB18258 lung. NB17057 NB17074 NB17050 NB18206 NB18261 NB18258 KS19028 M. komaniense 100 0 0 0 0 0 0 M. smegmatis 0 100 0.86 0 0 0 0 MTBC 0 0 99.14 99.68 95.7 83.01 0 MAC 0 0 0 0.32 4.3 16.99 10.9 Mycobacterium sp. 0 0 0 0 0 0 6.13 Streptomyces sp. 0 0 0 0 0 0 82.97 Discussion While M. bovis culture is regarded as the gold standard technique for detecting animal TB, it necessitates a substantial bacterial load and is time-intensive, often taking eight weeks or more to confirm a diagnosis definitively. To overcome these challenges, various direct molecular techniques, such as real-time PCR, have been developed for rapid and specific identification of MTBC DNA 37 . The advantages of this approach include high diagnostic sensitivity (Se), specificity (Sp), and shorter turnaround time for a definitive diagnosis. Additionally, modern molecular methods enable the testing of large numbers of samples at low cost and with limited laboratory equipment, without the need for a biosafety level 3 (BSL3) facility, which is required for culturing this zoonotic agent. For instance, recent studies reported Se varying between 87.70–100% 20,38–40 and Sp of 93.66–100% 40–43 for targeted PCR detection of M. bovis in tissue samples from infected cattle herds compared to mycobacterial culture. However, while direct molecular techniques enable rapid and accurate diagnosis, they require careful standardization to avoid false positive results due to imperfect specificity. Cross-reactivity of IS 6110 -based real-time PCRs has been reported for non-MTBC mycobacterial isolates, such as M. marinum and M. avium 40 . Therefore, despite their advantages, the potential for cross-reactivity and the need for standardization are important considerations when direct molecular techniques are applied for M. bovis DNA detection and animal TB surveillance. At the same time, MTBC strains lacking commonly used real-time PCR target genes such as IS 6110 have been described from human clinical samples, leading to false negative outcomes 44 , 45 . Our culture-independent detection method applied to 60 samples, independently confirmed to harbour M. bovis through culture and molecular characterisation (RD-PCRs and spoligotyping), showed a Se of 91.7%, which was comparable to previous observations using different molecular means. The advantage of the approach reported in this study is the ability to distinguish between various mycobacterial species and estimate the relative abundance of each population present, facilitating characterisation of the mycobacteriome. This approach targets a wide range of mycobacterial species, which may lead to interference in culture or in vivo diagnostic test results. Furthermore, the single-tube amplification of multiple targets allows the user to obtain a more comprehensive understanding of the sample composition. However, caution is advised when interpreting the distribution abundances of amplicons obtained for the three target genes, as the affinity of the primer pairs used may vary significantly. Finally, the inclusion of discriminatory genes, such as gyrA and gyrB , provides additional information, especially for complex clinical settings, where mixed pathogens may occur in various hosts and the environment 46 – 52 . Mycobacterial species differentiation can have significant implications for antimicrobial treatment in humans, since most M. bovis strains are naturally resistant to pyrazinamide, an essential first-line antibiotic used to treat TB patients 53 . A comprehensive characterisation of bacterial communities found in infected patients is crucial for understanding their immunomodulatory role and potential involvement in pathogenesis, facilitating the identification of unique microbial biomarkers that appear enriched or depleted in specific cohorts 54 . This study explores the capabilities of long-read Nanopore-based sequencing to provide high-throughput and high-accuracy profiles of housekeeping genes for the genus Mycobacterium , alongside de novo generated consensus sequences utilizing full-length 16S rRNA gene amplicon sequencing. The presence of NTM in animals and people infected with MTBC carries significant medical consequences. Firstly, their presence may hinder the detection of MTBC through culture methods, potentially resulting in false negative outcomes. Secondly, NTM could impact immune responses to MTBC, influence the progression of infection, and modulate host response to existing live attenuated vaccines such as the Bacillus Calmette–Guérin (BCG) strain 55 – 57 . The most common NTM found in this study through targeted deep sequencing were members of the MAC, followed by M. smegmatis , M. komaniense , and an uncharacterized Mycobacterium sp. This finding aligns with previous observations in wild and domestic ungulates such as cattle 13 , 58 , pigs 59 , wild boar 60 , and African buffalo 12 , suggesting a high presence of M. avium and M. colombiense in tissue samples due to transient colonisation or co-infection with MTBC. In this study, M. komaniense , a rapidly growing NTM closely related to M. moriokaense , was identified in a single parotid showing a lesion score of 2. Notably, this newly described mycobacterial species was initially documented in bovine nasal swabs, soil, and water samples collected from 2010 to 2012 in South Africa 61 . One of the four isolates previously reported by Gcebe et al. was obtained from a soil sample taken in the same geographic region (HiP, KwaZulu Natal Province) where the buffaloes in the current study were sampled 61 . These findings suggest potential geographic adaptation of certain mycobacterial species and temporal persistence. However, the clinical significance of M. komaniense is unknown. The concurrent detection of M. bovis and M. komaniense in a retropharyngeal lymph node exhibiting a small focal lesion with a diameter < 10 mm (lesion score 1) does not necessarily preclude the possibility of an incidental finding. With the rising incidence of NTM infections, particularly those caused by MAC, among both immunocompromised and immunocompetent human patients globally, there is a need for further investigation of the clinical implications posed by these emerging pathogens. A One Health approach, that includes mycobacterial strains from human, animal, and environmental origins, is required to investigate common etiological determinants of infection, comorbidities, and virulence factors influencing clinical outcomes. In this study, a targeted PCR deep-sequencing culture-independent approach, using DNA from tissues confirmed to contain M. bovis , was used to explore the composition of the mycobacteriome. The shorter target PCR ( hsp65 ) demonstrated superior capability in detecting NTM and heterogeneous populations of mycobacteria compared to alternative targets. However, since none of the three targets amplified simultaneously in the multiplex PCR could distinguish between M. bovis and other members of the MTBC using amplicon sequencing, the incorporation of additional ecotype-specific markers (g yrA and g yrB genes) was imperative for the diagnostic pipeline 62 . Implementing the outlined method in future studies, particularly those involving samples containing multiple mycobacterial species and from microbially complex sites, such as the upper respiratory tract, will enhance understanding of the diverse interactions and within-host coexistence of mycobacterial species. Similar to prior research reports 63 – 65 , our findings indicate that Nanopore-based targeted amplicon sequencing can generate comparable results to existing high-throughput assays for the detection and characterisation of MTBC organisms. However, it is important to note that Nanopore costs may fluctuate significantly based on batch sizes and the utilization of flow cells. Moreover, because of the frequent updates in chemistry and base calling algorithms, constant validation of new kits and pipelines might pose a hurdle for clinical applications. One of the main drawbacks is the short longevity of flow cells, which may impede progress in longer-term projects. Finally, transitioning entirely from mycobacterial cultures, which usually enhance DNA yield and indicate viability, poses a challenge in demonstrating the transmission and actual infection potential of the mycobacteria detected via a culture-independent approach. Both culturing and PCR may introduce bias, leading to findings that might not faithfully reflect the original mycobacteriome 66 , 67 . Therefore, innovative research efforts should focus on refining RNA-based detection methods to differentiate viable bacilli and remnant DNA draining through the lymph system in clinical samples 68 . Conclusion By applying a culture-independent targeted next-generation sequencing approach to DNA extracted from previously culture-confirmed M. bovis infected African buffalo tissues, we were able to detect mycobacterial DNA in 93.3% of the samples. Of these, 98.2% were positive for MTBC DNA. Mycobacterial-specific amplicons were sequenced and identified positive tissue samples using a one-tube multiplex amplicon sequencing approach. This technique provided rapid, portable, and comparable results to previously published molecular methods. This study presents an alternative to culture-based detection methods for the detection of animal TB and for characterisation of mycobacterial communities in wildlife tissue samples. Materials and Methods Study Population Between 2017 and 2019, a routine veterinary annual test-and-slaughter program was conducted in Hluhluwe-iMfolozi Park (HiP), South Africa (SA), on different herds of African buffaloes 3 , 69 . All animals were captured, immobilized, and whole blood collected, as previously described 9 . Positive animals were euthanized by gunshot based on the detection of cell-mediated immunity (CMI) responses toward M. bovis- specific antigens (n = 67). All buffaloes were handled by the Enzemvelo Wildlife Services and KZN state veterinarians. Various tissue samples (lymph nodes from the head, thorax, and lung) were collected during necropsies, and lesion scores were assigned as previously described (Suppl. Table 1) 8 . For each sample, tissue homogenate aliquots were split for mycobacterial culture and culture-independent analyses, with processing occurring in a BSL-3 laboratory up to the step of DNA extraction. Briefly, approximately 10 g of tissue was homogenized in 50-mL skirted tubes (Becton Dickinson, Franklin Lakes, New Jersey, USA) containing eight 4.8-mm metal beads and 4 mL of sterile phosphate-buffered saline (PBS) using a blender (Bullet Blender 50; Next Advance, Averill Park, NY, USA) for 15 min at maximum speed, as previously described 70 . After decontamination, performed with BD MycoPrep™ (N-acetyl L-cysteine sodium hydroxide) and PBS following the manufacturer’s instructions, all samples were centrifuged for 15 min at 1500 × g and the supernatant was decanted. Each pellet was resuspended in 1 ml PBS and 500 µl of this suspension was transferred to a Mycobacteria Growth Indicator Tube (MGIT™) supplemented with PANTA and incubated in a BACTEC™ MGIT™ 960 Mycobacterial Detection System (both Becton Dickinson). An additional aliquot of tissue homogenate was subsequently preserved (− 80°C) for DNA extractions, repeat culturing, and/or future sequencing. All Mycobacteria Growth Indicator Tubes (MGIT™) were incubated for 56 days and culture-positive crude extracts were subjected to speciation using a PCR targeting genetic regions of difference to confirm M. bovis infections, as previously described 22 . Further genetic speciation using spoligotyping was performed 71 . Sample selection and processing A total of 60 frozen native tissue homogenates from 57 different African buffaloes were retrospectively selected from the cohort mentioned above and included for downstream analysis (Fig. 1 ) based on M. bovis culture and PCR confirmation. Previously frozen tissue homogenates (1 mL aliquot) were subjected to genomic DNA extraction using the DNeasy Blood and Tissue kit (Qiagen) with modifications, as previously described 72 . Briefly, tissue homogenates were heat-inactivated (98°C for 45 minutes), then centrifuged (1,500 x g for 10 minutes), after which 300 µL of Buffer ATL (Qiagen) was added to the cell pellet. Subsequently, 25 µL of Proteinase K (Qiagen) was added and allowed to digest overnight at 56°C with agitation at 600 rpm. The sample was centrifuged at 5,500 x g for 5 minutes, after which 500 µL of supernatant was collected and transferred to a 1.5 mL tube. An additional 400 µL of buffer AL and 400 µL of ethanol was mixed with the supernatant and then transferred to a Mini Spin Column (Qiagen). Finally, DNA purification was conducted using wash buffers AW1 and AW2 (Qiagen), followed by elution in 60 µL of buffer AE (Qiagen) pre-warmed to 54°C. Concentrations of DNA were quantified using the Qubit 1x dsDNA High Sensitivity Assay kit (Thermo Fisher Scientific), following the manufacturer's instructions. Subsequently, DNA integrity and presence of PCR inhibitors were assessed by amplification of the variable regions V3-V4 within the 16S gene, using previously published primers (prbac1/prbac2) and PCR conditions 73 . Finally, the PCR products were visualized by 1% agarose gel electrophoresis. Targeted amplicon sequencing using Oxford Nanopore Technologies (ONT) A multiplex PCR-based amplification targeting three housekeeping genes, namely hsp65 (441 bp), rpoB (680 bp) and the full-length 16S rRNA gene (~ 1,500 bp), was performed culture-independently using DNA extracted from buffalo tissue homogenates, as previously described 72 . Presence of the amplified products was confirmed by 1% agarose gel electrophoresis. All samples showing amplification of > 1 target were included for amplicon sequencing. Using the Native Barcoding Kit 96 V14 kit (ONT), amplicons were end-repaired, individually barcoded, pooled into a single library, native adapter-ligated, loaded onto a single R10.4.1 flow cell (> 1,250 pores), and sequenced on a MinION mk1C device (ONT). Building upon prior molecular analyses, which encompassed RD-PCRs and spoligotyping, confirming the presence of M. bovis within the selected tissues, we aimed to verify the efficacy of the novel culture-independent methodology on a subset of samples. Therefore, eleven DNA samples were randomly selected to confirm the presence of M. bovis using gyrA and gyrB targeted amplicon sequencing. Three independent 25 µL reactions containing 14 µL Q5 High-Fidelity 2X Master Mix (New England Biolabs Inc., Ipswich, Massachusetts, United States ), 0.5 µL of each 50 µM primer stock solution 24 , 6 µL sterile, nuclease free water, and 2 µL undiluted extracted DNA. The PCR cycling conditions were as follows: 1 cycle initial denaturation at 98°C for 15 min, followed by 40 cycles of denaturation (98°C for 30 s), annealing (62.5°C for 30 s) and elongation (72°C for 2 min). Final elongation took place at 72°C for 5 min. The presence of the amplified products was confirmed by 1% agarose gel electrophoresis. Amplicons were end-repaired, individually barcoded, and native adapter-ligated using the Native Barcoding Kit 96 V14 kit (ONT). Finally, the pooled library was loaded onto a single Flongle R10.4.1 flow cell (> 60 pores) and sequenced using the MinION mk1C device (both ONT). Data analyses For the targeted amplicon sequencing datasets, base-calling, demultiplexing, and trimming of the barcodes were performed in real-time using Guppy [v6.4.6] (260 bps – High-Accuracy) 74 . Data acquisition and base-calling were stopped after 72 h for the three targets run using an R10.4.1 flow cell and after 22 h for the gyrA and gyrB run using a Flongle flow cell (Supplementary Material 1 and 2). Quality control, filtering, and summary reports for Nanopore reads were generated using nanoq v0.10.0 75 and reads with a Q score of < 12 were discarded. Thereafter, reference-free reads sorting, based on similarity and length, was performed using the amplicon sorter tool [v2023-06-19] 35 . A total of 200,000 randomly chosen reads with minimum and maximum lengths of 300 bp and 2000 bp, respectively, were selected for each barcode generated, using the three target amplicon approach ( hsp65 , rpoB , and 16S rRNA). Finally, ABRicate ( https://github.com/tseemann/abricate ) and custom databases, generated as previously described 72 , were used for the screening of consensus sequences and summarizing the report files. For the analysis, the following interpretation criteria were established: Coverage ≥ 90% and identity ≤ 90%, the sequence was reported as unclassified. Coverage ≥ 90% and identity fell within the range of 90–98%, the sequence was classified as Mycobacterium sp. Coverage ≥ 90% and identity ≥ 98%, the sequence was reported according to the results table. Since the database only contained mycobacterial sequences and to characterise bacterial contaminants, all consensus sequences with a corresponding length to 16S rRNA and showing an identity lower than 98% were manually searched using the NCBI Basic Local Alignment Search Tool (BLAST). Reads generated from the gyrB and gyrA amplicons were selected based on lengths with a minimum of 50 bp to a maximum of 200 bp. Consensus sequences were then generated for each species amplified and target gene. Relative abundances were determined by analyzing the representative pool of reads. Sequence comparison with a custom database, generated with gyrB and gyrA sequences for all members of the MTBC, was performed as above. For all bioinformatics tools, default settings were used unless stated otherwise. The distribution of consensus sequences generated per target gene and relative abundance of Mycobacterium sp. identified across different samples was visualized using the R package ggplot2. Ethics South African Veterinary Council (SAVC)-registered wildlife veterinarians were responsible for all procedures, including immobilization of animals, blood collection, euthanasia, and tissue sampling. No animal was specifically immobilized, sampled, or sacrificed for this study. Ethical approval for this study was granted by Stellenbosch University Animal Care and Use Research Ethics Committee (SU-ACUD16-00072; SU-ACU-2019-9081) and the Stellenbosch University Biological and Environmental Safety Research Ethics Committee (SU-BEE-2021-22561). Section 20 approval was granted by the South African Department of Agriculture, Land Reform and Rural Development (DALRRD 12/11/1/7/6 and 12/11/1/7/2). The study was conducted following the local legislation and institutional requirements and the authors complied with the ARRIVE guidelines. Declarations Additional Information The authors declare that they have no competing interests. Author Contribution GG: Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – original draft, Writing – review & editing. TK: Data curation, Writing – review & editing. SKM: Methodology, Writing – review & editing. ES: Investigation, Methodology, Writing – review & editing. AGL: Funding acquisition, Resources, Writing – review & editing. RMW: Funding acquisition, Resources, Writing – review & editing. NB: Investigation, Methodology, Writing – review & editing. MAM: Conceptualization, Methodology, Resources, Supervision, Writing – review & editing. WG: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing – original draft, Writing – review & editing. Acknowledgement We thank Dr David Cooper, Alicia and Warren McCall, Debbie Cooke, Dr Rowan Leeming, Dumisani Zwane, JP van Heerden, and the Game Capture staff from KwaZulu-Natal Ezemvelo Wildlife for the capture and sampling of buffaloes, and their support of this study. This work was supported by funding from the South African government through the South African Medical Research Council and the National Research Foundation South African Research Chair Initiative (Grant #86949), Wellcome Trust Foundation (222941/Z/21/Z), European Union supported by the Global Health EDCTP3 Joint Undertaking and its members [Project 101103171], and American Association of Zoo Veterinarians Wild Animal Health Fund (S005651). The content is the sole responsibility of the authors and does not necessarily represent the official views of the funders. Data Availability The datasets presented in this study were submitted to the European Nucleotide Archive (ENA) under project reference number PRJEB75236, https://www.ebi.ac.uk/ena/browser/view/PRJEB75236. References Meiring, C., van Helden, P. D. & Goosen, W. J. TB control in humans and animals in South Africa: A perspective on problems and successes. Front Vet Sci 5, 298, doi:10.3389/fvets.2018.00298 (2018). Muller, B. et al. Zoonotic Mycobacterium bovis -induced tuberculosis in humans. Emerg. Infect. Dis. 19, 899-908, doi:10.3201/eid1906.120543 (2013). Bernitz, N. et al. Test characteristics of assays to detect Mycobacterium bovis infection in high-prevalence African buffalo ( Syncerus caffer ) herds. J. Wildl. Dis. 56, 462-465 (2020). Dwyer, R. A., Witte, C., Buss, P., Goosen, W. J. & Miller, M. Epidemiology of tuberculosis in multi-host wildlife systems: implications for black ( Diceros bicornis ) and white ( Ceratotherium simum ) rhinoceros. Front Vet Sci 7, 580476, doi:10.3389/fvets.2020.580476 (2020). Goosen, W. J. et al. Culture-independent PCR detection and differentiation of Mycobacteria spp. in antemortem respiratory samples from African elephants ( Loxodonta africana ) and rhinoceros ( Ceratotherium simum , Diceros bicornis ) in South Africa. Pathogens 11, doi:10.3390/pathogens11060709 (2022). Goosen, W. J. et al. Identification and molecular characterization of Mycobacterium bovis DNA in GeneXpert(R) MTB/RIF ultra-positive, culture-negative sputum from a rural community in South Africa. One Health 18, 100702, doi:10.1016/j.onehlt.2024.100702 (2024). Miller, M. et al. Detection of antibodies to tuberculosis antigens in free-ranging lions ( Panthera leo ) infected with Mycobacterium bovis in Kruger National Park, South Africa. J. Zoo Wildl. Med. 43, 317-323, doi:10.1638/2011-0171.1 (2012). Bernitz, N. et al. Impact of Mycobacterium bovis -induced pathology on interpretation of QuantiFERON(R)-TB Gold assay results in African buffaloes ( Syncerus caffer ). Vet. Immunol. Immunopathol. 217, 109923, doi:10.1016/j.vetimm.2019.109923 (2019). Parsons, S. D. et al. Modification of the QuantiFERON-TB Gold (In-Tube) assay for the diagnosis of Mycobacterium bovis infection in African buffaloes ( Syncerus caffer ). Vet. Immunol. Immunopathol. 142, 113-118, doi:10.1016/j.vetimm.2011.04.006 (2011). Biet, F. & Boschiroli, M. L. Non-tuberculous mycobacterial infections of veterinary relevance. Res. Vet. Sci. 97 Suppl, S69-77, doi:10.1016/j.rvsc.2014.08.007 (2014). Augustynowicz-Kopec, E. et al. Interferon gamma release assays in patients with respiratory isolates of non-tuberculous mycobacteria - a preliminary study. Pol. J. Microbiol. 68, 15-19, doi:10.21307/pjm-2019-002 (2019). Gcebe, N., Rutten, V., Gey van Pittius, N. C. & Michel, A. Prevalence and distribution of Non-Tuberculous Mycobacteria (NTM) in cattle, African buffaloes ( Syncerus caffer ) and their environments in South Africa. Transbound. Emerg. Dis. 60, 74-84, doi:10.1111/tbed.12133 (2013). Ghielmetti, G. et al. Non-tuberculous mycobacteria isolated from lymph nodes and faecal samples of healthy slaughtered cattle and the abattoir environment. Transbound. Emerg. Dis. 65, 711-718, doi:10.1111/tbed.12793 (2018). WHOA. Bovine Tuberculosis. Terrestrial Manual , doi:https://www.woah.org/app/uploads/2021/03/3-04-06-bovine-tb.pdf (2018). Goosen, W. J. et al. The Xpert MTB/RIF Ultra assay detects Mycobacterium tuberculosis complex DNA in white rhinoceros ( Ceratotherium simum ) and African elephants ( Loxodonta africana ). Sci. Rep. 10, 14482, doi:10.1038/s41598-020-71568-9 (2020). Ghielmetti, G. et al. Tuberculosis in Swiss captive Asian elephants: microevolution of Mycobacterium tuberculosis characterized by multilocus variable-number tandem-repeat analysis and whole-genome sequencing. Sci. Rep. 7, 14647, doi:10.1038/s41598-017-15278-9 (2017). Ghielmetti, G. et al. Epidemiological tracing of bovine tuberculosis in Switzerland, multilocus variable number of tandem repeat analysis of Mycobacterium bovis and Mycobacterium caprae . PLoS One 12, e0172474, doi:10.1371/journal.pone.0172474 (2017). Schoning, J. M. et al. Surveillance of bovine tuberculosis and risk estimation of a future reservoir formation in wildlife in Switzerland and Liechtenstein. PLoS One 8, e54253, doi:10.1371/journal.pone.0054253 (2013). Dorn-In, S. et al. Shedding of Mycobacterium caprae by wild red deer ( Cervus elaphus ) in the Bavarian alpine regions, Germany. Transbound. Emerg. Dis. 67, 308-317, doi:10.1111/tbed.13353 (2020). Courcoul, A. et al. Estimation of sensitivity and specificity of bacteriology, histopathology and PCR for the confirmatory diagnosis of bovine tuberculosis using latent class analysis. PLoS One 9, e90334, doi:10.1371/journal.pone.0090334 (2014). Goosen, W. J. et al. The VetMAX M. tuberculosis complex PCR kit detects MTBC DNA in antemortem and postmortem samples from white rhinoceros ( Ceratotherium simum ), African elephants ( Loxodonta africana ) and African buffaloes ( Syncerus caffer ). BMC Vet. Res. 16, 220, doi:10.1186/s12917-020-02438-9 (2020). Warren, R. M. et al. Differentiation of Mycobacterium tuberculosis complex by PCR amplification of genomic regions of difference. Int. J. Tuberc. Lung Dis. 10, 818-822 (2006). Kasai, H., Ezaki, T. & Harayama, S. Differentiation of phylogenetically related slowly growing mycobacteria by their gyrB sequences. J. Clin. Microbiol. 38, 301-308 (2000). Landolt, P., Stephan, R., Stevens, M. J. A. & Scherrer, S. Three-reaction high-resolution melting assay for rapid differentiation of Mycobacterium tuberculosis complex members. Microbiologyopen 8, doi:ARTN e91910.1002/mbo3.919 (2019). Niemann, S., Harmsen, D., Rüsch-Gerdes, S. & Richter, E. Differentiation of clinical Mycobacterium tuberculosis complex isolates by gyrB DNA sequence polymorphism analysis. J. Clin. Microbiol. 38, 3231-3234, doi:Doi 10.1128/Jcm.38.9.3231-3234.2000 (2000). Callahan, B. J. et al. High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. Nucleic Acids Res. 47, e103, doi:10.1093/nar/gkz569 (2019). Earl, J. P. et al. Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes. Microbiome 6, 190, doi:10.1186/s40168-018-0569-2 (2018). Johnson, J. S. et al. Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. Nat Commun 10, 5029, doi:10.1038/s41467-019-13036-1 (2019). Curry, K. D. et al. Emu: species-level microbial community profiling of full-length 16S rRNA Oxford Nanopore sequencing data. Nat Methods 19, 845-853, doi:10.1038/s41592-022-01520-4 (2022). Zorz, J. et al. SituSeq: an offline protocol for rapid and remote Nanopore 16S rRNA amplicon sequence analysis. ISME Commun 3, 33, doi:10.1038/s43705-023-00239-3 (2023). Gopalaswamy, R., Shanmugam, S., Mondal, R. & Subbian, S. Of tuberculosis and non-tuberculous mycobacterial infections - a comparative analysis of epidemiology, diagnosis and treatment. J. Biomed. Sci. 27, 74, doi:10.1186/s12929-020-00667-6 (2020). Maiga, M. et al. Failure to recognize nontuberculous mycobacteria leads to misdiagnosis of chronic pulmonary tuberculosis. PLoS One 7, e36902, doi:10.1371/journal.pone.0036902 (2012). Riello, F. N. et al. Diagnosis of mycobacterial infections based on acid-fast bacilli test and bacterial growth time and implications on treatment and disease outcome. BMC Infect. Dis. 16, 142, doi:10.1186/s12879-016-1474-6 (2016). Gorsich, E. E. et al. Opposite outcomes of coinfection at individual and population scales. P Natl Acad Sci USA 115, 7545-7550, doi:10.1073/pnas.1801095115 (2018). Vierstraete, A. R. & Braeckman, B. P. Amplicon_sorter: A tool for reference-free amplicon sorting based on sequence similarity and for building consensus sequences. Ecol. Evol. 12, e8603, doi:10.1002/ece3.8603 (2022). Macovei, L. et al. The hidden 'mycobacteriome' of the human healthy oral cavity and upper respiratory tract. J. Oral Microbiol. 7, 26094, doi:10.3402/jom.v7.26094 (2015). Zeineldin, M. M., Lehman, K., Camp, P., Farrell, D. & Thacker, T. C. Diagnostic evaluation of the IS 1081 -targeted real-time PCR for detection of Mycobacterium bovis DNA in bovine milk samples. Pathogens 12, doi:10.3390/pathogens12080972 (2023). Costa, P. et al. Enhanced detection of tuberculous mycobacteria in animal tissues using a semi-nested probe-based real-time PCR. PLoS One 8, e81337, doi:10.1371/journal.pone.0081337 (2013). Lorente-Leal, V. et al. Validation of a real-time PCR for the detection of Mycobacterium tuberculosis complex members in bovine tissue samples. Front Vet Sci 6, 61, doi:10.3389/fvets.2019.00061 (2019). Lorente-Leal, V. et al. Direct PCR on tissue samples to detect Mycobacterium tuberculosis complex: an alternative to the bacteriological culture. J. Clin. Microbiol. 59, doi:10.1128/JCM.01404-20 (2021). Araujo, C. P. et al. Detection of Mycobacterium bovis in bovine and bubaline tissues using nested-PCR for TbD1. PLoS One 9, e91023, doi:10.1371/journal.pone.0091023 (2014). Parra, A. et al. Development of a molecular diagnostic test applied to experimental abattoir surveillance on bovine tuberculosis. Vet. Microbiol. 127, 315-324, doi:10.1016/j.vetmic.2007.09.001 (2008). Thacker, T. C., Harris, B., Palmer, M. V. & Waters, W. R. Improved specificity for detection of Mycobacterium bovis in fresh tissues using IS 6110 real-time PCR. BMC Vet. Res. 7, 50, doi:10.1186/1746-6148-7-50 (2011). Lok, K. H. et al. Molecular differentiation of Mycobacterium tuberculosis strains without IS 6110 insertions. Emerg. Infect. Dis. 8, 1310-1313, doi:10.3201/eid0811.020291 (2002). Steensels, D., Fauville-Dufaux, M., Boie, J. & De Beenhouwer, H. Failure of PCR-based IS 6110 analysis to detect vertebral spondylodiscitis caused by Mycobacterium bovis . J. Clin. Microbiol. 51, 366-368, doi:10.1128/JCM.02524-12 (2013). Baker, M. G., Lopez, L. D., Cannon, M. C., De Lisle, G. W. & Collins, D. M. Continuing Mycobacterium bovis transmission from animals to humans in New Zealand. Epidemiol. Infect. 134, 1068-1073, doi:10.1017/S0950268806005930 (2006). Gibson, A. L. et al. Molecular epidemiology of disease due to Mycobacterium bovis in humans in the United Kingdom. J. Clin. Microbiol. 42, 431-434, doi:10.1128/JCM.42.1.431-434.2004 (2004). Guven Gokmen, T. et al. Molecular characterization of Mycobacterium bovis strains isolated from cattle and humans by spoligotyping and 24-locus MIRU-VNTR, and prevalence of positive IGRA in slaughterhouse workers in Southern Turkey. Iran J Vet Res 23, 210-218, doi:10.22099/IJVR.2022.42580.6186 (2022). Lari, N., Rindi, L., Bonanni, D., Tortoli, E. & Garzelli, C. Molecular analysis of clinical isolates of Mycobacterium bovis recovered from humans in Italy. J. Clin. Microbiol. 44, 4218-4221, doi:10.1128/JCM.01216-06 (2006). Ortiz, A. P. et al. Whole genome sequencing links Mycobacterium bovis from cattle, cheese and humans in Baja California, Mexico. Front Vet Sci 8, 674307, doi:10.3389/fvets.2021.674307 (2021). Palaniyandi, K. et al. Isolation and comparative genomics of Mycobacterium tuberculosis isolates from cattle and their attendants in South India. Sci. Rep. 9, 17892, doi:10.1038/s41598-019-54268-x (2019). Wahdan, A., Riad, E. M. & Enany, S. Genetic differentiation of Mycobacterium bovis and Mycobacterium tuberculosis isolated from cattle and human sources in, Egypt (Suez Canal area). Comp. Immunol. Microbiol. Infect. Dis. 73, 101553, doi:10.1016/j.cimid.2020.101553 (2020). Allix-Beguec, C. et al. Importance of identifying Mycobacterium bovis as a causative agent of human tuberculosis. Eur. Respir. J. 35, 692-694, doi:10.1183/09031936.00137309 (2010). Duvallet, C., Gibbons, S. M., Gurry, T., Irizarry, R. A. & Alm, E. J. Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. Nat Commun 8, 1784, doi:10.1038/s41467-017-01973-8 (2017). Poyntz, H. C. et al. Non-tuberculous mycobacteria have diverse effects on BCG efficacy against Mycobacterium tuberculosis . Tuberculosis (Edinb) 94, 226-237, doi:10.1016/j.tube.2013.12.006 (2014). Tanner, R., Villarreal-Ramos, B., Vordermeier, H. M. & McShane, H. The humoral immune response to BCG vaccination. Front. Immunol. 10, 1317, doi:10.3389/fimmu.2019.01317 (2019). Verma, D., Chan, E. D. & Ordway, D. J. Non-tuberculous mycobacteria interference with BCG-current controversies and future directions. Vaccines (Basel) 8, doi:10.3390/vaccines8040688 (2020). Mareledwane, V., Adesiyun, A. A. & Hlokwe, T. M. Absence of tuberculosis-causing cycobacteria from slaughtered livestock tissues and environmental samples, Gauteng Province, South Africa. Int. J. Microbiol. 2024, 4636652, doi:10.1155/2024/4636652 (2024). Komijn, R. E. et al. Prevalence of Mycobacterium avium in slaughter pigs in The Netherlands and comparison of IS1245 restriction fragment length polymorphism patterns of porcine and human isolates. J. Clin. Microbiol. 37, 1254-1259, doi:10.1128/JCM.37.5.1254-1259.1999 (1999). Ghielmetti, G. et al. Mycobacterial infections in wild boars ( Sus scrofa ) from Southern Switzerland: Diagnostic improvements, epidemiological situation and zoonotic potential. Transbound. Emerg. Dis. 68, 573-586, doi:10.1111/tbed.13717 (2021). Gcebe, N., Rutten, V. P. M. G., van Pittius, N. G., Naicker, B. & Michel, A. L. Mycobacterium komaniense sp. nov., a rapidly growing non-tuberculous Mycobacterium species detected in South Africa. Int. J. Syst. Evol. Microbiol. 68, 1526-1532, doi:10.1099/ijsem.0.002707 (2018). Smith, N. H. et al. Ecotypes of the Mycobacterium tuberculosis complex. J. Theor. Biol. 239, 220-225, doi:10.1016/j.jtbi.2005.08.036 (2006). Murphy, S. G. et al. Direct detection of drug-resistant Mycobacterium tuberculosis using targeted next generation sequencing. Front Public Health 11, 1206056, doi:10.3389/fpubh.2023.1206056 (2023). Szoboszlay, M. et al. Nanopore is preferable over Illumina for 16S amplicon sequencing of the gut microbiota when species-level taxonomic classification, accurate estimation of richness, or focus on rare taxa is required. Microorganisms 11, doi:10.3390/microorganisms11030804 (2023). Tafess, K. et al. Targeted-sequencing workflows for comprehensive drug resistance profiling of Mycobacterium tuberculosis cultures using two commercial sequencing platforms: comparison of analytical and diagnostic performance, turnaround time, and cost. Clin. Chem. 66, 809-820, doi:10.1093/clinchem/hvaa092 (2020). Damene, H. et al. Broad diversity of Mycobacterium tuberculosis complex strains isolated from humans and cattle in Northern Algeria suggests a zoonotic transmission cycle. PLoS Negl. Trop. Dis. 14, e0008894, doi:10.1371/journal.pntd.0008894 (2020). Sanoussi, C. N., Affolabi, D., Rigouts, L., Anagonou, S. & de Jong, B. Genotypic characterization directly applied to sputum improves the detection of Mycobacterium africanum West African 1, under-represented in positive cultures. PLoS Negl. Trop. Dis. 11, e0005900, doi:10.1371/journal.pntd.0005900 (2017). Beissner, M., Phillips, R. O. & Bretzel, G. Determining Viability of M. ulcerans by 16S rRNA RT Reverse Transcriptase Real-Time PCR. Methods Mol. Biol. 2387, 81-86, doi:10.1007/978-1-0716-1779-3_9 (2022). Smith, K. et al. Optimisation of the tuberculin skin test for detection of Mycobacterium bovis in African buffaloes ( Syncerus caffer ). Prev. Vet. Med. 188, 105254, doi:10.1016/j.prevetmed.2020.105254 (2021). Goosen, W. J. et al. Improved detection of Mycobacterium tuberculosis and M. bovis in African wildlife samples using cationic peptide decontamination and mycobacterial culture supplementation. J. Vet. Diagn. Invest. 34, 61-67, doi:10.1177/10406387211044192 (2022). Belakehal, F. et al. Evaluation of the discriminatory power of spoligotyping and 19-locus mycobacterial interspersed repetitive unit-variable number of tandem repeat analysis (MIRU-VNTR) of Mycobacterium bovis strains isolated from cattle in Algeria. PLoS One 17, e0262390, doi:10.1371/journal.pone.0262390 (2022). Ghielmetti, G. et al. Advancing animal tuberculosis surveillance using culture-independent long-read whole-genome sequencing. Front. Microbiol. 14, doi:ARTN 1307440 10.3389/fmicb.2023.1307440 (2023). Rupf, S., Merte, K. & Eschrich, K. Quantification of bacteria in oral samples by competitive polymerase chain reaction. J. Dent. Res. 78, 850-856, doi:10.1177/00220345990780040501 (1999). Wick, R. R., Judd, L. M. & Holt, K. E. Performance of neural network basecalling tools for Oxford Nanopore sequencing. Genome Biol. 20, 129, doi:10.1186/s13059-019-1727-y (2019). Steinig, E. & Coin, L. Nanoq: ultra-fast quality control for nanopore reads. JOSS 7 (2022). Additional Declarations No competing interests reported. Supplementary Files Suppl.Material1.pdf Suppl.Material2.pdf Suppl.Table1.xlsx Cite Share Download PDF Status: Published Journal Publication published 30 Jul, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 19 Jun, 2024 Reviews received at journal 18 Jun, 2024 Reviews received at journal 10 Jun, 2024 Reviewers agreed at journal 04 Jun, 2024 Reviewers agreed at journal 04 Jun, 2024 Reviewers invited by journal 04 Jun, 2024 Editor assigned by journal 04 Jun, 2024 Editor invited by journal 29 May, 2024 Submission checks completed at journal 23 May, 2024 First submitted to journal 26 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4329505","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":310602437,"identity":"b35b5fc1-2039-41a3-85d9-b4a2793b6695","order_by":0,"name":"Giovanni Ghielmetti","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Giovanni","middleName":"","lastName":"Ghielmetti","suffix":""},{"id":310602439,"identity":"51f06986-4b07-46ff-b161-13aa052f2e56","order_by":1,"name":"Tanya J. Kerr","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Tanya","middleName":"J.","lastName":"Kerr","suffix":""},{"id":310602441,"identity":"5dd746b0-9a03-4bdf-b715-42b36d18d7bd","order_by":2,"name":"Netanya Bernitz","email":"","orcid":"","institution":"The Francis Crick Institute","correspondingAuthor":false,"prefix":"","firstName":"Netanya","middleName":"","lastName":"Bernitz","suffix":""},{"id":310602442,"identity":"48eca07f-fe40-42b3-8f74-be86942ee1fb","order_by":3,"name":"Sinegugu K. Mhlophe","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Sinegugu","middleName":"K.","lastName":"Mhlophe","suffix":""},{"id":310602444,"identity":"af401f44-3bc9-40b6-878e-4c56225e14db","order_by":4,"name":"Elizma Streicher","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Elizma","middleName":"","lastName":"Streicher","suffix":""},{"id":310602445,"identity":"8fe7b297-8e14-477a-8ec0-97ce62314648","order_by":5,"name":"Andre G. Loxton","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Andre","middleName":"G.","lastName":"Loxton","suffix":""},{"id":310602446,"identity":"546ad272-7648-4fda-ae12-264efad00696","order_by":6,"name":"Robin M. Warren","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Robin","middleName":"M.","lastName":"Warren","suffix":""},{"id":310602447,"identity":"b5d9f7df-1773-4b2d-b822-7aa643e4b774","order_by":7,"name":"Michele A. Miller","email":"","orcid":"","institution":"Stellenbosch University","correspondingAuthor":false,"prefix":"","firstName":"Michele","middleName":"A.","lastName":"Miller","suffix":""},{"id":310602448,"identity":"15bfce7f-af48-4b6f-9650-0af56d50b79a","order_by":8,"name":"Wynand J. Goosen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0UlEQVRIiWNgGAWjYFCCAxCKn3Qtkg0kW2ZwgGiVB49ffPDhj02e8fkzZg8YauwY5NsJaDY4cKbYcGZbWrHZjRxzA4ZjyQyMPQn4tZgdOJMmzdtwOHHbDR4zCQa2AwzMDMRo4fnzP3Fz/xmgln8HGNj4HxDScvyYNA/bgcQNDDlmEoxtBxh4JAjYYn/gDDPQL8mJM26klUkk9iXzSEgQsEVyxvGHwBCzS+zvP7xN4sM3Ozn5fgK2MEicMUBwgIp5CKgHAv52Au4YBaNgFIyCUQAA+4tFnfVA1AcAAAAASUVORK5CYII=","orcid":"","institution":"Stellenbosch University","correspondingAuthor":true,"prefix":"","firstName":"Wynand","middleName":"J.","lastName":"Goosen","suffix":""}],"badges":[],"createdAt":"2024-04-26 12:18:47","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4329505/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4329505/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-68189-x","type":"published","date":"2024-07-30T15:58:08+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":57759077,"identity":"16d4cc19-595f-4602-897f-2b6072593c35","added_by":"auto","created_at":"2024-06-05 09:02:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":179339,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy overview illustrating the methods applied to DNA extracted from culture-confirmed \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eM. bovis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e-positive tissue samples (n=60) from 57 different African buffalo, selected and included in the study following mycobacterial species identification. \u003c/strong\u003eAfter amplifying three target genes (\u003cem\u003ehsp65\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, 16S rRNA), long-read amplicon sequencing was conducted on 56 samples using Oxford Nanopore Technologies (ONT), the Native Barcoding Kit 96 V14, and a single R10.4.1 flow cell. \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex (MTBC) speciation was achieved by amplifying and sequencing the \u003cem\u003egyrA\u003c/em\u003e and \u003cem\u003egyrB\u003c/em\u003e gene targets on 11 randomly selected samples using a single Flongle R10.4.1 flow cell (ONT).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/b48500506253a343cca29f57.png"},{"id":57759076,"identity":"9325c196-cd83-4763-a00c-3538c971b02e","added_by":"auto","created_at":"2024-06-05 09:02:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":127797,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of reads with quality score \u0026gt;Q12 obtained using Oxford Nanopore Technologies (ONT) targeted next-generation sequencing (tNGS) across 56 African buffalo tissue samples.\u003c/strong\u003e Among 78.6% of the samples (n=44), over 200,000 reads were generated, with a maximum of 897,809 reads. Conversely, the remaining 21.4% (n=12) of samples yielded reads ranging between 63,705 and 197,343, all of which were included in the analysis. The vertical red dotted line highlights the threshold for the number of reads used for downstream analysis.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/a5e9acb54c9fced35bdf6421.png"},{"id":57759079,"identity":"fde94419-e479-426c-a856-3c1b0e1239be","added_by":"auto","created_at":"2024-06-05 09:02:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":145745,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e(a) Visualization depicting the distribution of reads across different target genes (16S rRNA, \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003erpoB, hsp65\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e) for DNA from each African buffalo tissue sample (n=7) where the presence of non-tuberculous mycobacteria or heterogeneous mycobacterial communities was detected. \u003c/strong\u003eReference-free sorting and assembly of consensus sequences were performed on randomly selected reads. The relative abundance of the target genes amplified using a multiplex PCR and sequenced using Oxford Nanopore Technologies is shown. \u003cstrong\u003e(b) The relative abundance of reads appertaining to different mycobacteria and closely related organisms including \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eStreptomyces\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003esp. is illustrated\u003c/strong\u003e. Identification of mycobacterial communities, as indicated in Figure 2a, based on the amplification of the \u003cem\u003ehsp65\u003c/em\u003e gene. \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex (MTBC); \u003cem\u003eMycobacterium avium\u003c/em\u003e complex (MAC); NB18261 mediastinal lymph node; NB18258 lung; NB18206 subiliac lymph node; NB17074 and KS19028 pooled head lymph nodes; NB17057 parotid; NB17050 retropharyngeal lymph node.\u003c/p\u003e","description":"","filename":"Figure3AB.png","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/26ff6624c6ba7e7f1979601c.png"},{"id":61793780,"identity":"c57e2265-bdb9-4edf-9b5a-4b4e441db1f6","added_by":"auto","created_at":"2024-08-05 16:15:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1595485,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/d9a6ff09-4f52-49c6-b78d-c77b25de747b.pdf"},{"id":57759078,"identity":"75f66ee1-a094-4d14-ab1c-92c656451ec3","added_by":"auto","created_at":"2024-06-05 09:02:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":579191,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Material1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/257a874bc0fd407cc11e584e.pdf"},{"id":57759081,"identity":"a16e23bf-da28-4709-bf95-4fe9d27894c7","added_by":"auto","created_at":"2024-06-05 09:02:24","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":571727,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Material2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/b168d4add6ee19312ec83a68.pdf"},{"id":57759080,"identity":"871b8f74-fdda-43e7-8746-c7e3d8299b1f","added_by":"auto","created_at":"2024-06-05 09:02:24","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":17281,"visible":true,"origin":"","legend":"","description":"","filename":"Suppl.Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4329505/v1/96c08a21a70ea5dfb3f52186.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Insights into Mycobacteriome Composition in Mycobacterium bovis-Infected African Buffalo (Syncerus caffer) Tissue Samples: A Culture-Independent Approach","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAnimal tuberculosis (TB), caused by \u003cem\u003eMycobacterium bovis\u003c/em\u003e (\u003cem\u003eM. bovis\u003c/em\u003e) and other members of the \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex (MTBC), is a threat to livestock and wildlife populations\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Among the diverse mycobacterial species, \u003cem\u003eM. bovis\u003c/em\u003e is a significant pathogen capable of causing severe chronic infectious disease, particularly in animals such as African buffaloes (\u003cem\u003eSyncerus caffer\u003c/em\u003e)\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. African buffaloes are well-known wildlife maintenance hosts for \u003cem\u003eM. bovis\u003c/em\u003e, contributing to the potential direct and indirect transmission of the pathogen to domestic livestock, other susceptible wildlife species like African lions (\u003cem\u003ePanthera leo\u003c/em\u003e), rhinoceros (\u003cem\u003eCeratotherium simum\u003c/em\u003e, \u003cem\u003eDiceros bicornis\u003c/em\u003e), African elephants (\u003cem\u003eLoxodonta africana\u003c/em\u003e), and humans\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn African buffaloes, \u003cem\u003eante-mortem\u003c/em\u003e detection of infection is based on the \u003cem\u003ein vivo\u003c/em\u003e or \u003cem\u003ein vitro\u003c/em\u003e measurement of \u003cem\u003eM. bovis\u003c/em\u003e antigen-specific cell-mediated immunological (CMI) responses, using the tuberculin skin test (TST) or the interferon-γ (IFN-γ) release assay (IGRA), respectively\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Although conventional TST uses purified protein derivatives (PPDs) from \u003cem\u003eM. bovis\u003c/em\u003e and \u003cem\u003eM. avium\u003c/em\u003e, in vitro cytokine stimulation assays have employed PPDs or mycobacterial peptides, such as early secretory antigen target 6 kDa (ESAT\u003cem\u003e-6\u003c/em\u003e) and culture filtrate protein 10 kDa (CFP-10), for identifying infected individuals. Unfortunately, cross-reactive host responses to non-tuberculous mycobacteria (NTMs), especially when using PPDs to stimulate antigen-specific cell-mediated immunity (CMI) responses, lead to diagnostic interference\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Non-tuberculous mycobacteria, once considered benign environmental organisms prevalent in soil and water, are now recognized as potential pathogens with implications for human and animal health\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Infection with NTMs can cause diseases collectively referred to as mycobacteriosis, affecting not only humans but also various livestock and wildlife species\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eCurrently, the gold standard for definitive diagnosis and characterisation of \u003cem\u003eM. bovis\u003c/em\u003e and other mycobacteria relies on culture-based methods, where bacterial isolates obtained from infected animals undergo phenotypic and genotypic analyses\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. However, the application of mycobacterial culture may not be feasible, especially if samples originate from Foot-and-Mouth Disease (FMD) endemic areas. In South Africa, most of the FMD-endemic areas coincide with well-known \u003cem\u003eM. bovis\u003c/em\u003e-endemic wildlife parks such as Hluhluwe-iMfolozi Park (HiP; KwaZulu-Natal Province) and Kruger National Park (KNP; Mpumalanga and Limpopo Provinces). In these regions, the movement of cloven-hooved animals including samples is subjected to regulatory restrictions. Consequently, the inability to transport samples from these FMD-endemic regions poses a significant obstacle to employing mycobacterial culture for \u003cem\u003eM. bovis\u003c/em\u003e detection. As a result, there is a need for DNA-based culture-independent \u003cem\u003eM. bovis\u003c/em\u003e diagnostic techniques as well as an unbiased approach to investigate complex host-mycobacterial interactions.\u003c/p\u003e \u003cp\u003eTo date, a few commercially available PCR assays have been reported to detect MTBC members and NTMs directly from animal specimens, including oronasal swabs, tissue homogenates, and respiratory secretions, including bronchoalveolar lavage samples. However, these assays cannot differentiate between the different members of the MTBC. Assays include but are not limited to the Xpert\u0026reg; MTB/RIF Ultra (Cepheid, Sunnyvale, California, USA)\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, artus\u0026reg; \u003cem\u003eM. tuberculosis\u003c/em\u003e PCR Kit (Qiagen, Venlo, Limburg, Netherlands)\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, COBAS\u0026reg; TaqMan\u0026reg; MTB Test kit (Roche Diagnostics, Indianapolis, Indiana, United States)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, BactoReal\u0026reg; kit (Ingenetix, Vienna, Austria)\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e, and VetMAX\u0026trade; \u003cem\u003eM. tuberculosis\u003c/em\u003e Complex PCR Kit (Thermo Fisher Scientific, Waltham, Massachusetts, United States)\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e for MTBC DNA detection, and the Hain Geno-Type CM\u003cem\u003edirect\u003c/em\u003e VER 1.0-line probe assay\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e for MTBC/NTM DNA detection and identification of commonly found NTM species in human clinical samples. The latter test, however, has been reported to be less successful when applied to samples that had not undergone prior culture\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In contrast, PCR amplification of housekeeping genes such as the beta subunit of RNA polymerase (\u003cem\u003erpoB)\u003c/em\u003e, partial heat-shock protein (\u003cem\u003ehsp65)\u003c/em\u003e, and the \u003cem\u003eKu\u003c/em\u003e genes, in conjunction with amplicon sequencing, have successfully detected \u003cem\u003eMycobacterium\u003c/em\u003e genus DNA and provided species identification in \u003cem\u003eante-mortem\u003c/em\u003e samples from wildlife species, circumventing the need for culture-based methods\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, these targets are unable to differentiate specific MTBC members and require an additional region-of-difference PCR (RD-PCR) for speciation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Unfortunately, RD-PCRs were initially tailored for the identification of MTBC in mycobacterial cultures, posing significant challenges in adapting them for use with DNA extracted directly from samples\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Sequencing of selected genomic targets has shown promise as an alternative tool for discerning phylogenetically related slow-growing mycobacteria by interrogating DNA sequence polymorphisms\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Genes encoding DNA gyrase subunits \u003cem\u003egyrA\u003c/em\u003e and \u003cem\u003egyrB\u003c/em\u003e have demonstrated satisfactory discriminatory power, facilitating precise taxonomic resolution and classification of distinct MTBC members\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDespite being a sub-optimal gene target for \u003cem\u003eMycobacterium\u003c/em\u003e genus speciation, studies have demonstrated the advantages of using full-length 16S rRNA amplicon sequencing for taxonomic classification, as opposed to short-read amplicon sequencing\u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Nonetheless, previous methods for high-throughput full-length 16S rRNA gene amplicon sequencing using Oxford Nanopore Technologies (ONT) technology often relied solely on reference database alignment\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e rather than employing \u003cem\u003ede novo\u003c/em\u003e generation of sequence features, such as amplicon sequence variants (ASV) or operational taxonomic units (OTU).\u003c/p\u003e \u003cp\u003eCurrently, the generation of whole-genome sequences for epidemiological investigations of animal TB relies on mycobacterial culture; however, analyses can be impeded by the presence of other microorganisms that outcompete MTBC growth in culture\u003csup\u003e\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Co-infections can also modulate immune response, particularly in infections with closely related microorganisms that share antigenic properties\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. This study describes the use of a three- housekeeping-gene (\u003cem\u003ehsp65\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e and 16S rRNA) in a culture-independent in-house multiplex PCR method, followed by single-nucleotide polymorphism (SNP) level MTBC confirmation (\u003cem\u003egyrA\u003c/em\u003e and \u003cem\u003egyrB\u003c/em\u003e), to identify and characterize all \u003cem\u003eMycobacteria spp\u003c/em\u003e. directly from culture-confirmed \u003cem\u003eM. bovis\u003c/em\u003e infected tissue.\u003c/p\u003e \u003cp\u003eUsing a novel culture-independent targeted next-generation sequencing (tNGS) approach, we aimed to characterize the mycobacteriome, which refers to the community of mycobacteria present in a sample, of \u003cem\u003eM. bovis\u003c/em\u003e infected tissue from African buffaloes. For this purpose, we applied a novel reference-free sorting tool\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e on ONT-sequenced amplicons and based on their similarity in sequence and length, we were able to build consensus sequences revealing the mycobacteriome present in each sample\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. This approach contributes to the refinement of diagnostic strategies, enhancing our ability to comprehensively study the mycobacterial landscape in wildlife and ensuring the effective surveillance of \u003cem\u003eM. bovis\u003c/em\u003e in regions where it poses a significant threat to both animal health and conservation efforts.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 60 tissue samples from 57 individual African buffaloes from the Hluhluwe-iMfolozi Park (HiP), South Africa (SA), were selected in the present study and included pooled head lymph nodes (n = 5), pooled thoracic lymph nodes (n = 7), lung tissue (n = 7), tonsil (n = 5), tracheobronchial lymp nodes (n = 12), mediastinal lymph nodes (n = 8), parotid (n = 4), retropharyngeal lymph nodes (n = 6), prescapular lymph nodes (n = 3), two mandibular lymph nodes, and one subiliac lymph node. All buffalo samples had previously been confirmed as infected using the aforementioned culture methods, and the presence of the \u003cem\u003eM. bovis\u003c/em\u003e region of difference 4 (RD4) signature was confirmed from culture-positive crude DNA extracts\u003csup\u003e22\u003c/sup\u003e. Spacer oligonucleotide typing hybridization assay (spoligotyping) revealed that all samples fit one of two profiles, SB0130 (n=39) and SB1474 (n=21) (Suppl. Table 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eONT targeted amplicon sequencing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll samples showing amplification of \u0026gt;1 target gene were included for amplicon sequencing, whereas four samples (2 tonsils, one lung, and one parotid) for which none of the targets could be visualized after electrophoresis were excluded from downstream analysis. The \u003cem\u003ehsp65, rpoB\u003c/em\u003e, and 16S rRNA gene regions were successfully amplified from 55 samples (Figure 1). One pooled head lymph nodes sample did not amplify the \u003cem\u003erpoB\u003c/em\u003e target. The number of reads per specimen with Q12 or greater ranged from 63,705 to 897,809 (Mean (\u003cem\u003eM\u003c/em\u003e) =\u0026thinsp;320,985 reads, Standard Deviation (SD)\u0026thinsp;=\u0026thinsp;154,129), and the total number of bases sequenced ranged from 38,921,972 to 554,606,081 (\u003cem\u003eM\u003c/em\u003e =\u0026thinsp;199,128,119 bases, SD\u0026thinsp;=\u0026thinsp;95,521,803). The N50 read length (median read length of the longest contigs) varied from 558 to 781 bases. The mean read length for the samples ranged from 576 to 658 bases. The mean read quality, as indicated by the Phred score, ranged between 14.2 and 14.5. A total of 200,000 reads with \u0026gt;Q12 were randomly selected from each sample for downstream analysis (Figure 2).\u003c/p\u003e\n\u003cp\u003eSince amplification of the three main targets occurred in a single tube, PCR products amplified were not normalized, and therefore shorter sequences were predominant. The distribution of reads for each target varied, with \u003cem\u003ehsp65\u003c/em\u003e ranging from 31-79%, \u003cem\u003erpoB\u003c/em\u003e 2-30%, and 16S rRNA 1-8% of the selected reads (Table 1, Figure 3a). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Distribution of read counts for the seven African buffalo tissue samples (identification number in first row) where the presence of non-tuberculous mycobacteria or heterogeneous mycobacterial communities was identified.\u0026nbsp;\u003c/strong\u003eReference-free sorting and assembly of consensus sequences were performed on a maximum of 200,000 randomly selected reads (\u0026gt;Q12) for each sample. For tissue samples with fewer reads, the entire available dataset was included. Reads were generated using Oxford Nanopore Technologies (ONT) on targeted amplified housekeeping genes shown in the first column. Reads that could not be assigned to any of the three targets were grouped as unclassified and excluded from downstream analysis. NB17057 parotid;\u0026nbsp;NB17074 and KS19028 pooled head lymph nodes; NB17050 retropharyngeal lymph node; NB18206 subiliac lymph node; NB18261 mediastinal lymph node; NB18258 lung.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"631\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB17057\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB17074\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB17050\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB18206\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB18261\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB18258\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKS19028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ehsp65\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e38771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e153928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e101257\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e90572\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e119897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e62228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e159430\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003erpoB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e1644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003eNA\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e49733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e49978\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e56224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e53955\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e10135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e16S rRNA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e4791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e9471\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e2876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e3010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e4725\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e2186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e9757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eunclassified\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e18499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e36601\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e46134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e33795\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e19154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e81631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e20678\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncluded for analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e63705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e200000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e200000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e177355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e200000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e200000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e200000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.620253164556964%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal number reads\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e63705\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e204856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e230365\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e177355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e351470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.550632911392405%\" valign=\"top\"\u003e\n \u003cp\u003e271981\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.075949367088608%\" valign=\"top\"\u003e\n \u003cp\u003e249582\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e# For sample NB17074 no amplification was observed for \u003cem\u003erpoB\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMycobacteriome composition\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEvidence of \u003cem\u003eMycobacterium\u003c/em\u003e spp. DNA presence was detected in 93.3% (56/60) of the DNA samples extracted directly from tissue homogenates. Among the 56 samples subjected to amplicon generation and subsequent deep sequencing for the three targets, the \u003cem\u003erpoB\u003c/em\u003e PCR exhibited the highest sensitivity for MTBC detection (98.2%), followed by \u003cem\u003ehsp65\u003c/em\u003e (94.6%), and 16S rRNA (92.8%). The shorter target PCR (\u003cem\u003ehsp65\u003c/em\u003e) demonstrated the highest efficacy in detecting NTM and heterogeneous mycobacterial populations compared to alternative targets (Table 2), as well as closely related microorganisms such as \u003cem\u003eStreptomyces\u003c/em\u003e sp. (Figure 3b).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Synopsis of the reference-free sorting and assembly outcomes of consensus sequences for the three \u003cem\u003eMycobacterium\u003c/em\u003e spp. target genes (\u003cem\u003ehsp65, rpoB\u003c/em\u003e, 16S rRNA) included in the culture-independent next-generation sequencing approach.\u0026nbsp;\u003c/strong\u003eThe composition of the mycobacteriome varied depending on the three independent targets. Notably, the shorter target PCR (\u003cem\u003ehsp65\u003c/em\u003e) demonstrated the ability to identify the highest proportion of mycobacteria, with amplification and \u003cem\u003eMycobacterium\u003c/em\u003e spp. sequences detected in 93.3% of the samples tested (56/60). The \u003cem\u003erpoB\u003c/em\u003e PCR displayed the highest sensitivity for MTBC detection, identifying MTBC in 91.7% of all samples included (55/60).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.185667752442995%\" valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ehsp65\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003erpoB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e16S rRNA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.185667752442995%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;complex (MTBC)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.185667752442995%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNon-tuberculous\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003cem\u003emycobacteria\u003c/em\u003e (NTM)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.185667752442995%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMTBC + NTM\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"49.185667752442995%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e55\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.938110749185668%\" valign=\"top\"\u003e\n \u003cp\u003e54\u003csup\u003e\u0026sect;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e# One sample could not be amplified using the \u003cem\u003erpoB\u003c/em\u003e target\u003c/p\u003e\n\u003cp\u003e\u0026sect; For two samples (NB18154 and KS19028), the 16S rRNA consensus sequences were classified as organisms not belonging to the \u003cem\u003eMycobacterium\u003c/em\u003e genus. Further analysis using NCBI Basic Local Alignment Search Tool (BLAST) identified the presence of \u003cem\u003eNiallia\u003c/em\u003e sp. in NB18154 and \u003cem\u003eStreptomyces\u003c/em\u003e sp. in KS19028.\u003c/p\u003e\n\u003cp\u003eBased on previous molecular analyses, which involved RD-PCRs and spoligotyping used to confirm the presence of \u003cem\u003eM. bovis\u003c/em\u003e within the selected samples, our goal was to assess the ability of the novel culture-independent methodology to detect and speciate MTBC members. Using a subset of eleven tissue DNA samples, the g\u003cem\u003eyrA\u003c/em\u003e and g\u003cem\u003eyrB\u003c/em\u003e genes were amplified and sequenced on a single Flongle flow cell (ONT). The number of reads with Q12 or greater ranged from 118 to 1,918 (\u003cem\u003eM\u003c/em\u003e =\u0026thinsp;1,157 reads, SD\u0026thinsp;=\u0026thinsp;489), and the total number of bases sequenced ranged from 20,411 to 328,224 (\u003cem\u003eM\u003c/em\u003e = 200,948 bases, SD\u0026thinsp;= \u0026nbsp;85,764). The mean read quality, as indicated by the Phred score, was consistently above 13 (11/11). All reads with \u0026gt;Q12 quality scores were selected from each sample for downstream analysis.\u003c/p\u003e\n\u003cp\u003eThe three additional targets employed for confirming the presence of \u003cem\u003eM. bovis\u003c/em\u003e DNA (\u003cem\u003egyrA\u003c/em\u003e, \u003cem\u003egyrB1\u003c/em\u003e, and \u003cem\u003egyrB2\u003c/em\u003e) were successfully amplified in all 11 selected samples. Specifically, the \u003cem\u003egyrA\u003c/em\u003e gene target amplicon sequences confirmed the presence of MTBC DNA in approximately three-quarters of the samples (8 out of 11), while \u003cem\u003egyrB1\u003c/em\u003e and \u003cem\u003egyrB2\u003c/em\u003e confirmed the RD and spoligotyping speciation results obtained from culture-derived DNA in all samples. For two samples (NB17057 and KS19028), however, the total number of reads (656 and 118) and the number of consensus sequences identified as MTBC in one or more targets (92 and 43) were lower compared to the corresponding mean values generated for the other samples (total number of reads 10,149).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to the detection of MTBC DNA, tNGS of the \u003cem\u003ehsp65\u003c/em\u003e gene successfully identified diverse mycobacterial species in different tissue specimens, including two pooled head lymph nodes, one lung, one mediastinal lymph node, one parotid, one retropharyngeal lymph node, and one subiliac lymph node. \u003cem\u003eMycobacterium avium complex\u003c/em\u003e (MAC) was detected in four samples (7.1%), \u003cem\u003eM. smegmatis\u003c/em\u003e in two (3.6%), \u003cem\u003eM. komaniense\u003c/em\u003e and an unclassified \u003cem\u003eMycobacterium\u003c/em\u003e sp. in one sample each (1.8%). Additionally, DNA of mycobacteria\u0026rsquo;s closely related organisms such as \u003cem\u003eStreptomyces sp.\u0026nbsp;\u003c/em\u003ewere amplified and further identified using the\u003cem\u003e\u0026nbsp;hsp65\u0026nbsp;\u003c/em\u003etarget gene (Figure 3b).\u003cem\u003e\u0026nbsp;\u003c/em\u003eIn the DNA sample NB17074, originating from lung tissue, \u003cem\u003eM. smegmatis\u003c/em\u003e was identified using \u003cem\u003ehsp65\u003c/em\u003e and 16S rRNA targets, but no amplification was observed using \u003cem\u003erpoB\u0026nbsp;\u003c/em\u003ePCR. Conversely, in one retropharyngeal lymph node (sample NB17057), \u003cem\u003eM. komaniense\u003c/em\u003e was detected using \u003cem\u003ehsp65\u003c/em\u003e and 16S rRNA PCRs, while MTBC DNA was detected using \u003cem\u003erpoB\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt least two distinct strains of MAC were detected, exhibiting 15 genomic modifications, including single nucleotide variations and indels. These strains displayed the highest \u003cem\u003ehsp65\u003c/em\u003e sequence homology to \u003cem\u003eM. avium\u003c/em\u003e and \u003cem\u003eM. colombiense\u003c/em\u003e. The MAC sequences were exclusively detected in tissue samples exhibiting heterogeneous bacterial populations (4/4), including MTBC in three samples, and a combination of \u003cem\u003eStreptomyces\u003c/em\u003e sp. and \u003cem\u003eMycobacterial\u003c/em\u003e sp. in one sample (Table 3). The samples originated from various locations including lung tissue,\u0026nbsp;mediastinal\u0026nbsp;lymph nodes,\u0026nbsp;head lymph nodes,\u0026nbsp;and\u0026nbsp;subiliac lymph nodes. Finally, the relative abundance of reads classified as MAC varied between 0.3 and 17% for the \u003cem\u003ehsp65\u003c/em\u003e target in the above-mentioned samples (Figure 3b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003e \u003cstrong\u003ePercentage of \u003cem\u003ehsp65\u003c/em\u003e PCR target reads (%) indicating the presence of non-tuberculous mycobacteria or heterogeneous mycobacterial communities in each African buffalo tissue sample where the DNA of these organisms was detected.\u003c/strong\u003e NB17057 parotid;\u0026nbsp;NB17074 and KS19028 pooled head lymph nodes; NB17050 retropharyngeal lymph node; NB18206 subiliac lymph node; NB18261 mediastinal lymph node; NB18258 lung.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB17057\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB17074\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB17050\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB18206\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB18261\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNB18258\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eKS19028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eM. komaniense\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eM. smegmatis\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMTBC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e99.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e99.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e95.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e83.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMAC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e16.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eMycobacterium sp.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e6.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.655629139072847%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eStreptomyces sp.\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.119205298013245%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.092715231788079%\" valign=\"top\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.76158940397351%\" valign=\"top\"\u003e\n \u003cp\u003e82.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWhile \u003cem\u003eM. bovis\u003c/em\u003e culture is regarded as the gold standard technique for detecting animal TB, it necessitates a substantial bacterial load and is time-intensive, often taking eight weeks or more to confirm a diagnosis definitively. To overcome these challenges, various direct molecular techniques, such as real-time PCR, have been developed for rapid and specific identification of MTBC DNA\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The advantages of this approach include high diagnostic sensitivity (Se), specificity (Sp), and shorter turnaround time for a definitive diagnosis. Additionally, modern molecular methods enable the testing of large numbers of samples at low cost and with limited laboratory equipment, without the need for a biosafety level 3 (BSL3) facility, which is required for culturing this zoonotic agent. For instance, recent studies reported Se varying between 87.70\u0026ndash;100%\u003csup\u003e20,38\u0026ndash;40\u003c/sup\u003e and Sp of 93.66\u0026ndash;100%\u003csup\u003e40\u0026ndash;43\u003c/sup\u003e for targeted PCR detection of \u003cem\u003eM. bovis\u003c/em\u003e in tissue samples from infected cattle herds compared to mycobacterial culture. However, while direct molecular techniques enable rapid and accurate diagnosis, they require careful standardization to avoid false positive results due to imperfect specificity. Cross-reactivity of IS\u003cem\u003e6110\u003c/em\u003e-based real-time PCRs has been reported for non-MTBC mycobacterial isolates, such as \u003cem\u003eM. marinum\u003c/em\u003e and \u003cem\u003eM. avium\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Therefore, despite their advantages, the potential for cross-reactivity and the need for standardization are important considerations when direct molecular techniques are applied for \u003cem\u003eM. bovis\u003c/em\u003e DNA detection and animal TB surveillance. At the same time, MTBC strains lacking commonly used real-time PCR target genes such as IS\u003cem\u003e6110\u003c/em\u003e have been described from human clinical samples, leading to false negative outcomes\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur culture-independent detection method applied to 60 samples, independently confirmed to harbour \u003cem\u003eM. bovis\u003c/em\u003e through culture and molecular characterisation (RD-PCRs and spoligotyping), showed a Se of 91.7%, which was comparable to previous observations using different molecular means. The advantage of the approach reported in this study is the ability to distinguish between various mycobacterial species and estimate the relative abundance of each population present, facilitating characterisation of the mycobacteriome. This approach targets a wide range of mycobacterial species, which may lead to interference in culture or \u003cem\u003ein vivo\u003c/em\u003e diagnostic test results. Furthermore, the single-tube amplification of multiple targets allows the user to obtain a more comprehensive understanding of the sample composition. However, caution is advised when interpreting the distribution abundances of amplicons obtained for the three target genes, as the affinity of the primer pairs used may vary significantly. Finally, the inclusion of discriminatory genes, such as \u003cem\u003egyrA\u003c/em\u003e and \u003cem\u003egyrB\u003c/em\u003e, provides additional information, especially for complex clinical settings, where mixed pathogens may occur in various hosts and the environment\u003csup\u003e\u003cspan additionalcitationids=\"CR47 CR48 CR49 CR50 CR51\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Mycobacterial species differentiation can have significant implications for antimicrobial treatment in humans, since most \u003cem\u003eM. bovis\u003c/em\u003e strains are naturally resistant to pyrazinamide, an essential first-line antibiotic used to treat TB patients\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA comprehensive characterisation of bacterial communities found in infected patients is crucial for understanding their immunomodulatory role and potential involvement in pathogenesis, facilitating the identification of unique microbial biomarkers that appear enriched or depleted in specific cohorts\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. This study explores the capabilities of long-read Nanopore-based sequencing to provide high-throughput and high-accuracy profiles of housekeeping genes for the genus \u003cem\u003eMycobacterium\u003c/em\u003e, alongside de novo generated consensus sequences utilizing full-length 16S rRNA gene amplicon sequencing. The presence of NTM in animals and people infected with MTBC carries significant medical consequences. Firstly, their presence may hinder the detection of MTBC through culture methods, potentially resulting in false negative outcomes. Secondly, NTM could impact immune responses to MTBC, influence the progression of infection, and modulate host response to existing live attenuated vaccines such as the Bacillus Calmette\u0026ndash;Gu\u0026eacute;rin (BCG) strain\u003csup\u003e\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe most common NTM found in this study through targeted deep sequencing were members of the MAC, followed by \u003cem\u003eM. smegmatis\u003c/em\u003e, \u003cem\u003eM. komaniense\u003c/em\u003e, and an uncharacterized \u003cem\u003eMycobacterium\u003c/em\u003e sp. This finding aligns with previous observations in wild and domestic ungulates such as cattle\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e, pigs\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e, wild boar\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, and African buffalo\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, suggesting a high presence of \u003cem\u003eM. avium\u003c/em\u003e and \u003cem\u003eM. colombiense\u003c/em\u003e in tissue samples due to transient colonisation or co-infection with MTBC. In this study, \u003cem\u003eM. komaniense\u003c/em\u003e, a rapidly growing NTM closely related to \u003cem\u003eM. moriokaense\u003c/em\u003e, was identified in a single parotid showing a lesion score of 2. Notably, this newly described mycobacterial species was initially documented in bovine nasal swabs, soil, and water samples collected from 2010 to 2012 in South Africa\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. One of the four isolates previously reported by Gcebe et al. was obtained from a soil sample taken in the same geographic region (HiP, KwaZulu Natal Province) where the buffaloes in the current study were sampled\u003csup\u003e\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. These findings suggest potential geographic adaptation of certain mycobacterial species and temporal persistence. However, the clinical significance of \u003cem\u003eM. komaniense\u003c/em\u003e is unknown. The concurrent detection of \u003cem\u003eM. bovis\u003c/em\u003e and \u003cem\u003eM. komaniense\u003c/em\u003e in a retropharyngeal lymph node exhibiting a small focal lesion with a diameter\u0026thinsp;\u0026lt;\u0026thinsp;10 mm (lesion score 1) does not necessarily preclude the possibility of an incidental finding. With the rising incidence of NTM infections, particularly those caused by MAC, among both immunocompromised and immunocompetent human patients globally, there is a need for further investigation of the clinical implications posed by these emerging pathogens. A One Health approach, that includes mycobacterial strains from human, animal, and environmental origins, is required to investigate common etiological determinants of infection, comorbidities, and virulence factors influencing clinical outcomes.\u003c/p\u003e \u003cp\u003eIn this study, a targeted PCR deep-sequencing culture-independent approach, using DNA from tissues confirmed to contain \u003cem\u003eM. bovis\u003c/em\u003e, was used to explore the composition of the mycobacteriome. The shorter target PCR (\u003cem\u003ehsp65\u003c/em\u003e) demonstrated superior capability in detecting NTM and heterogeneous populations of mycobacteria compared to alternative targets. However, since none of the three targets amplified simultaneously in the multiplex PCR could distinguish between \u003cem\u003eM. bovis\u003c/em\u003e and other members of the MTBC using amplicon sequencing, the incorporation of additional ecotype-specific markers (g\u003cem\u003eyrA\u003c/em\u003e and g\u003cem\u003eyrB\u003c/em\u003e genes) was imperative for the diagnostic pipeline\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Implementing the outlined method in future studies, particularly those involving samples containing multiple mycobacterial species and from microbially complex sites, such as the upper respiratory tract, will enhance understanding of the diverse interactions and within-host coexistence of mycobacterial species.\u003c/p\u003e \u003cp\u003eSimilar to prior research reports\u003csup\u003e\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e, our findings indicate that Nanopore-based targeted amplicon sequencing can generate comparable results to existing high-throughput assays for the detection and characterisation of MTBC organisms. However, it is important to note that Nanopore costs may fluctuate significantly based on batch sizes and the utilization of flow cells. Moreover, because of the frequent updates in chemistry and base calling algorithms, constant validation of new kits and pipelines might pose a hurdle for clinical applications. One of the main drawbacks is the short longevity of flow cells, which may impede progress in longer-term projects. Finally, transitioning entirely from mycobacterial cultures, which usually enhance DNA yield and indicate viability, poses a challenge in demonstrating the transmission and actual infection potential of the mycobacteria detected via a culture-independent approach. Both culturing and PCR may introduce bias, leading to findings that might not faithfully reflect the original mycobacteriome\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e,\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Therefore, innovative research efforts should focus on refining RNA-based detection methods to differentiate viable bacilli and remnant DNA draining through the lymph system in clinical samples\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBy applying a culture-independent targeted next-generation sequencing approach to DNA extracted from previously culture-confirmed \u003cem\u003eM. bovis\u003c/em\u003e infected African buffalo tissues, we were able to detect mycobacterial DNA in 93.3% of the samples. Of these, 98.2% were positive for MTBC DNA. Mycobacterial-specific amplicons were sequenced and identified positive tissue samples using a one-tube multiplex amplicon sequencing approach. This technique provided rapid, portable, and comparable results to previously published molecular methods. This study presents an alternative to culture-based detection methods for the detection of animal TB and for characterisation of mycobacterial communities in wildlife tissue samples.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStudy Population\u003c/h2\u003e \u003cp\u003eBetween 2017 and 2019, a routine veterinary annual test-and-slaughter program was conducted in Hluhluwe-iMfolozi Park (HiP), South Africa (SA), on different herds of African buffaloes\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. All animals were captured, immobilized, and whole blood collected, as previously described\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Positive animals were euthanized by gunshot based on the detection of cell-mediated immunity (CMI) responses toward \u003cem\u003eM. bovis-\u003c/em\u003especific antigens (n\u0026thinsp;=\u0026thinsp;67). All buffaloes were handled by the Enzemvelo Wildlife Services and KZN state veterinarians. Various tissue samples (lymph nodes from the head, thorax, and lung) were collected during necropsies, and lesion scores were assigned as previously described (Suppl. Table\u0026nbsp;1)\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. For each sample, tissue homogenate aliquots were split for mycobacterial culture and culture-independent analyses, with processing occurring in a BSL-3 laboratory up to the step of DNA extraction. Briefly, approximately 10 g of tissue was homogenized in 50-mL skirted tubes (Becton Dickinson, Franklin Lakes, New Jersey, USA) containing eight 4.8-mm metal beads and 4 mL of sterile phosphate-buffered saline (PBS) using a blender (Bullet Blender 50; Next Advance, Averill Park, NY, USA) for 15 min at maximum speed, as previously described\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. After decontamination, performed with BD MycoPrep\u0026trade; (N-acetyl L-cysteine sodium hydroxide) and PBS following the manufacturer\u0026rsquo;s instructions, all samples were centrifuged for 15 min at 1500 \u0026times; g and the supernatant was decanted. Each pellet was resuspended in 1 ml PBS and 500 \u0026micro;l of this suspension was transferred to a Mycobacteria Growth Indicator Tube (MGIT\u0026trade;) supplemented with PANTA and incubated in a BACTEC\u0026trade; MGIT\u0026trade; 960 Mycobacterial Detection System (both Becton Dickinson). An additional aliquot of tissue homogenate was subsequently preserved (\u0026minus;\u0026thinsp;80\u0026deg;C) for DNA extractions, repeat culturing, and/or future sequencing. All Mycobacteria Growth Indicator Tubes (MGIT\u0026trade;) were incubated for 56 days and culture-positive crude extracts were subjected to speciation using a PCR targeting genetic regions of difference to confirm \u003cem\u003eM. bovis\u003c/em\u003e infections, as previously described\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Further genetic speciation using spoligotyping was performed\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample selection and processing\u003c/h3\u003e\n\u003cp\u003eA total of 60 frozen native tissue homogenates from 57 different African buffaloes were retrospectively selected from the cohort mentioned above and included for downstream analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) based on \u003cem\u003eM. bovis\u003c/em\u003e culture and PCR confirmation. Previously frozen tissue homogenates (1 mL aliquot) were subjected to genomic DNA extraction using the DNeasy Blood and Tissue kit (Qiagen) with modifications, as previously described \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. Briefly, tissue homogenates were heat-inactivated (98\u0026deg;C for 45 minutes), then centrifuged (1,500 x g for 10 minutes), after which 300 \u0026micro;L of Buffer ATL (Qiagen) was added to the cell pellet. Subsequently, 25 \u0026micro;L of Proteinase K (Qiagen) was added and allowed to digest overnight at 56\u0026deg;C with agitation at 600 rpm. The sample was centrifuged at 5,500 x g for 5 minutes, after which 500 \u0026micro;L of supernatant was collected and transferred to a 1.5 mL tube. An additional 400 \u0026micro;L of buffer AL and 400 \u0026micro;L of ethanol was mixed with the supernatant and then transferred to a Mini Spin Column (Qiagen). Finally, DNA purification was conducted using wash buffers AW1 and AW2 (Qiagen), followed by elution in 60 \u0026micro;L of buffer AE (Qiagen) pre-warmed to 54\u0026deg;C. Concentrations of DNA were quantified using the Qubit 1x dsDNA High Sensitivity Assay kit (Thermo Fisher Scientific), following the manufacturer's instructions. Subsequently, DNA integrity and presence of PCR inhibitors were assessed by amplification of the variable regions V3-V4 within the 16S gene, using previously published primers (prbac1/prbac2) and PCR conditions \u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e. Finally, the PCR products were visualized by 1% agarose gel electrophoresis.\u003c/p\u003e\n\u003ch3\u003eTargeted amplicon sequencing using Oxford Nanopore Technologies (ONT)\u003c/h3\u003e\n\u003cp\u003eA multiplex PCR-based amplification targeting three housekeeping genes, namely \u003cem\u003ehsp65\u003c/em\u003e (441 bp), \u003cem\u003erpoB\u003c/em\u003e (680 bp) and the full-length 16S rRNA gene (~\u0026thinsp;1,500 bp), was performed culture-independently using DNA extracted from buffalo tissue homogenates, as previously described \u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e. Presence of the amplified products was confirmed by 1% agarose gel electrophoresis. All samples showing amplification of \u0026gt;\u0026thinsp;1 target were included for amplicon sequencing. Using the Native Barcoding Kit 96 V14 kit (ONT), amplicons were end-repaired, individually barcoded, pooled into a single library, native adapter-ligated, loaded onto a single R10.4.1 flow cell (\u0026gt;\u0026thinsp;1,250 pores), and sequenced on a MinION mk1C device (ONT). Building upon prior molecular analyses, which encompassed RD-PCRs and spoligotyping, confirming the presence of \u003cem\u003eM. bovis\u003c/em\u003e within the selected tissues, we aimed to verify the efficacy of the novel culture-independent methodology on a subset of samples. Therefore, eleven DNA samples were randomly selected to confirm the presence of \u003cem\u003eM. bovis\u003c/em\u003e using \u003cem\u003egyrA\u003c/em\u003e and \u003cem\u003egyrB\u003c/em\u003e targeted amplicon sequencing. Three independent 25 \u0026micro;L reactions containing 14 \u0026micro;L Q5 High-Fidelity 2X Master Mix (New England Biolabs Inc., Ipswich, Massachusetts, United States ), 0.5 \u0026micro;L of each 50 \u0026micro;M primer stock solution \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, 6 \u0026micro;L sterile, nuclease free water, and 2 \u0026micro;L undiluted extracted DNA. The PCR cycling conditions were as follows: 1 cycle initial denaturation at 98\u0026deg;C for 15 min, followed by 40 cycles of denaturation (98\u0026deg;C for 30 s), annealing (62.5\u0026deg;C for 30 s) and elongation (72\u0026deg;C for 2 min). Final elongation took place at 72\u0026deg;C for 5 min. The presence of the amplified products was confirmed by 1% agarose gel electrophoresis. Amplicons were end-repaired, individually barcoded, and native adapter-ligated using the Native Barcoding Kit 96 V14 kit (ONT). Finally, the pooled library was loaded onto a single Flongle R10.4.1 flow cell (\u0026gt;\u0026thinsp;60 pores) and sequenced using the MinION mk1C device (both ONT).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData analyses\u003c/h2\u003e \u003cp\u003eFor the targeted amplicon sequencing datasets, base-calling, demultiplexing, and trimming of the barcodes were performed in real-time using Guppy [v6.4.6] (260 bps \u0026ndash; High-Accuracy)\u003csup\u003e74\u003c/sup\u003e. Data acquisition and base-calling were stopped after 72 h for the three targets run using an R10.4.1 flow cell and after 22 h for the \u003cem\u003egyrA\u003c/em\u003e and \u003cem\u003egyrB\u003c/em\u003e run using a Flongle flow cell (Supplementary Material 1 and 2). Quality control, filtering, and summary reports for Nanopore reads were generated using nanoq v0.10.0\u003csup\u003e75\u003c/sup\u003e and reads with a Q score of \u0026lt;\u0026thinsp;12 were discarded. Thereafter, reference-free reads sorting, based on similarity and length, was performed using the amplicon sorter tool [v2023-06-19]\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. A total of 200,000 randomly chosen reads with minimum and maximum lengths of 300 bp and 2000 bp, respectively, were selected for each barcode generated, using the three target amplicon approach (\u003cem\u003ehsp65\u003c/em\u003e, \u003cem\u003erpoB\u003c/em\u003e, and 16S rRNA). Finally, ABRicate (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/tseemann/abricate\u003c/span\u003e\u003cspan address=\"https://github.com/tseemann/abricate\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and custom databases, generated as previously described\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e, were used for the screening of consensus sequences and summarizing the report files. For the analysis, the following interpretation criteria were established:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eCoverage\u0026thinsp;\u0026ge;\u0026thinsp;90% and identity\u0026thinsp;\u0026le;\u0026thinsp;90%, the sequence was reported as unclassified.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCoverage\u0026thinsp;\u0026ge;\u0026thinsp;90% and identity fell within the range of 90\u0026ndash;98%, the sequence was classified as \u003cem\u003eMycobacterium\u003c/em\u003e sp.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eCoverage\u0026thinsp;\u0026ge;\u0026thinsp;90% and identity\u0026thinsp;\u0026ge;\u0026thinsp;98%, the sequence was reported according to the results table.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eSince the database only contained mycobacterial sequences and to characterise bacterial contaminants, all consensus sequences with a corresponding length to 16S rRNA and showing an identity lower than 98% were manually searched using the NCBI Basic Local Alignment Search Tool (BLAST).\u003c/p\u003e \u003cp\u003eReads generated from the \u003cem\u003egyrB\u003c/em\u003e and \u003cem\u003egyrA\u003c/em\u003e amplicons were selected based on lengths with a minimum of 50 bp to a maximum of 200 bp. Consensus sequences were then generated for each species amplified and target gene. Relative abundances were determined by analyzing the representative pool of reads. Sequence comparison with a custom database, generated with \u003cem\u003egyrB\u003c/em\u003e and \u003cem\u003egyrA\u003c/em\u003e sequences for all members of the MTBC, was performed as above.\u003c/p\u003e \u003cp\u003eFor all bioinformatics tools, default settings were used unless stated otherwise. The distribution of consensus sequences generated per target gene and relative abundance of \u003cem\u003eMycobacterium\u003c/em\u003e sp. identified across different samples was visualized using the R package ggplot2.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eEthics\u003c/h2\u003e \u003cp\u003eSouth African Veterinary Council (SAVC)-registered wildlife veterinarians were responsible for all procedures, including immobilization of animals, blood collection, euthanasia, and tissue sampling. No animal was specifically immobilized, sampled, or sacrificed for this study. Ethical approval for this study was granted by Stellenbosch University Animal Care and Use Research Ethics Committee (SU-ACUD16-00072; SU-ACU-2019-9081) and the Stellenbosch University Biological and Environmental Safety Research Ethics Committee (SU-BEE-2021-22561). Section 20 approval was granted by the South African Department of Agriculture, Land Reform and Rural Development (DALRRD 12/11/1/7/6 and 12/11/1/7/2). The study was conducted following the local legislation and institutional requirements and the authors complied with the ARRIVE guidelines.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eAdditional Information\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eGG: Conceptualization, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. TK: Data curation, Writing \u0026ndash; review \u0026amp; editing. SKM: Methodology, Writing \u0026ndash; review \u0026amp; editing. ES: Investigation, Methodology, Writing \u0026ndash; review \u0026amp; editing. AGL: Funding acquisition, Resources, Writing \u0026ndash; review \u0026amp; editing. RMW: Funding acquisition, Resources, Writing \u0026ndash; review \u0026amp; editing. NB: Investigation, Methodology, Writing \u0026ndash; review \u0026amp; editing. MAM: Conceptualization, Methodology, Resources, Supervision, Writing \u0026ndash; review \u0026amp; editing. WG: Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank Dr David Cooper, Alicia and Warren McCall, Debbie Cooke, Dr Rowan Leeming, Dumisani Zwane, JP van Heerden, and the Game Capture staff from KwaZulu-Natal Ezemvelo Wildlife for the capture and sampling of buffaloes, and their support of this study. This work was supported by funding from the South African government through the South African Medical Research Council and the National Research Foundation South African Research Chair Initiative (Grant #86949), Wellcome Trust Foundation (222941/Z/21/Z), European Union supported by the Global Health EDCTP3 Joint Undertaking and its members [Project 101103171], and American Association of Zoo Veterinarians Wild Animal Health Fund (S005651). The content is the sole responsibility of the authors and does not necessarily represent the official views of the funders.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets presented in this study were submitted to the European Nucleotide Archive (ENA) under project reference number PRJEB75236, https://www.ebi.ac.uk/ena/browser/view/PRJEB75236.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMeiring, C., van Helden, P. D. \u0026amp; Goosen, W. J. TB control in humans and animals in South Africa: A perspective on problems and successes. \u003cem\u003eFront Vet Sci\u003c/em\u003e 5, 298, doi:10.3389/fvets.2018.00298 (2018).\u003c/li\u003e\n\u003cli\u003eMuller, B.\u003cem\u003e et al.\u003c/em\u003e Zoonotic \u003cem\u003eMycobacterium bovis\u003c/em\u003e-induced tuberculosis in humans. \u003cem\u003eEmerg. Infect. Dis.\u003c/em\u003e 19, 899-908, doi:10.3201/eid1906.120543 (2013).\u003c/li\u003e\n\u003cli\u003eBernitz, N.\u003cem\u003e et al.\u003c/em\u003e Test characteristics of assays to detect \u003cem\u003eMycobacterium bovis\u003c/em\u003e infection in high-prevalence African buffalo (\u003cem\u003eSyncerus caffer\u003c/em\u003e) herds. \u003cem\u003eJ. Wildl. Dis.\u003c/em\u003e 56, 462-465 (2020).\u003c/li\u003e\n\u003cli\u003eDwyer, R. A., Witte, C., Buss, P., Goosen, W. J. \u0026amp; Miller, M. Epidemiology of tuberculosis in multi-host wildlife systems: implications for black (\u003cem\u003eDiceros bicornis\u003c/em\u003e) and white (\u003cem\u003eCeratotherium simum\u003c/em\u003e) rhinoceros. \u003cem\u003eFront Vet Sci\u003c/em\u003e 7, 580476, doi:10.3389/fvets.2020.580476 (2020).\u003c/li\u003e\n\u003cli\u003eGoosen, W. J.\u003cem\u003e et al.\u003c/em\u003e Culture-independent PCR detection and differentiation of \u003cem\u003eMycobacteria\u003c/em\u003e spp. in antemortem respiratory samples from African elephants (\u003cem\u003eLoxodonta africana\u003c/em\u003e) and rhinoceros (\u003cem\u003eCeratotherium simum\u003c/em\u003e, \u003cem\u003eDiceros bicornis\u003c/em\u003e) in South Africa. \u003cem\u003ePathogens\u003c/em\u003e 11, doi:10.3390/pathogens11060709 (2022).\u003c/li\u003e\n\u003cli\u003eGoosen, W. J.\u003cem\u003e et al.\u003c/em\u003e Identification and molecular characterization of \u003cem\u003eMycobacterium bovis\u003c/em\u003e DNA in GeneXpert(R) MTB/RIF ultra-positive, culture-negative sputum from a rural community in South Africa. \u003cem\u003eOne Health\u003c/em\u003e 18, 100702, doi:10.1016/j.onehlt.2024.100702 (2024).\u003c/li\u003e\n\u003cli\u003eMiller, M.\u003cem\u003e et al.\u003c/em\u003e Detection of antibodies to tuberculosis antigens in free-ranging lions (\u003cem\u003ePanthera leo\u003c/em\u003e) infected with \u003cem\u003eMycobacterium bovis\u003c/em\u003e in Kruger National Park, South Africa. \u003cem\u003eJ. Zoo Wildl. Med.\u003c/em\u003e 43, 317-323, doi:10.1638/2011-0171.1 (2012).\u003c/li\u003e\n\u003cli\u003eBernitz, N.\u003cem\u003e et al.\u003c/em\u003e Impact of \u003cem\u003eMycobacterium bovis\u003c/em\u003e-induced pathology on interpretation of QuantiFERON(R)-TB Gold assay results in African buffaloes (\u003cem\u003eSyncerus caffer\u003c/em\u003e). \u003cem\u003eVet. Immunol. Immunopathol.\u003c/em\u003e 217, 109923, doi:10.1016/j.vetimm.2019.109923 (2019).\u003c/li\u003e\n\u003cli\u003eParsons, S. D.\u003cem\u003e et al.\u003c/em\u003e Modification of the QuantiFERON-TB Gold (In-Tube) assay for the diagnosis of \u003cem\u003eMycobacterium bovis\u003c/em\u003e infection in African buffaloes (\u003cem\u003eSyncerus caffer\u003c/em\u003e). \u003cem\u003eVet. Immunol. Immunopathol.\u003c/em\u003e 142, 113-118, doi:10.1016/j.vetimm.2011.04.006 (2011).\u003c/li\u003e\n\u003cli\u003eBiet, F. \u0026amp; Boschiroli, M. L. Non-tuberculous mycobacterial infections of veterinary relevance. \u003cem\u003eRes. Vet. Sci.\u003c/em\u003e 97 Suppl, S69-77, doi:10.1016/j.rvsc.2014.08.007 (2014).\u003c/li\u003e\n\u003cli\u003eAugustynowicz-Kopec, E.\u003cem\u003e et al.\u003c/em\u003e Interferon gamma release assays in patients with respiratory isolates of non-tuberculous mycobacteria - a preliminary study. \u003cem\u003ePol. J. Microbiol.\u003c/em\u003e 68, 15-19, doi:10.21307/pjm-2019-002 (2019).\u003c/li\u003e\n\u003cli\u003eGcebe, N., Rutten, V., Gey van Pittius, N. C. \u0026amp; Michel, A. Prevalence and distribution of Non-Tuberculous Mycobacteria (NTM) in cattle, African buffaloes (\u003cem\u003eSyncerus caffer\u003c/em\u003e) and their environments in South Africa. \u003cem\u003eTransbound. Emerg. Dis.\u003c/em\u003e 60, 74-84, doi:10.1111/tbed.12133 (2013).\u003c/li\u003e\n\u003cli\u003eGhielmetti, G.\u003cem\u003e et al.\u003c/em\u003e Non-tuberculous mycobacteria isolated from lymph nodes and faecal samples of healthy slaughtered cattle and the abattoir environment. \u003cem\u003eTransbound. Emerg. Dis.\u003c/em\u003e 65, 711-718, doi:10.1111/tbed.12793 (2018).\u003c/li\u003e\n\u003cli\u003eWHOA. Bovine Tuberculosis. \u003cem\u003eTerrestrial Manual\u003c/em\u003e, doi:https://www.woah.org/app/uploads/2021/03/3-04-06-bovine-tb.pdf (2018).\u003c/li\u003e\n\u003cli\u003eGoosen, W. J.\u003cem\u003e et al.\u003c/em\u003e The Xpert MTB/RIF Ultra assay detects \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003ecomplex DNA in white rhinoceros (\u003cem\u003eCeratotherium simum\u003c/em\u003e) and African elephants (\u003cem\u003eLoxodonta africana\u003c/em\u003e). \u003cem\u003eSci. Rep.\u003c/em\u003e 10, 14482, doi:10.1038/s41598-020-71568-9 (2020).\u003c/li\u003e\n\u003cli\u003eGhielmetti, G.\u003cem\u003e et al.\u003c/em\u003e Tuberculosis in Swiss captive Asian elephants: microevolution of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e characterized by multilocus variable-number tandem-repeat analysis and whole-genome sequencing. \u003cem\u003eSci. Rep.\u003c/em\u003e 7, 14647, doi:10.1038/s41598-017-15278-9 (2017).\u003c/li\u003e\n\u003cli\u003eGhielmetti, G.\u003cem\u003e et al.\u003c/em\u003e Epidemiological tracing of bovine tuberculosis in Switzerland, multilocus variable number of tandem repeat analysis of \u003cem\u003eMycobacterium bovis \u003c/em\u003eand \u003cem\u003eMycobacterium caprae\u003c/em\u003e. \u003cem\u003ePLoS One\u003c/em\u003e 12, e0172474, doi:10.1371/journal.pone.0172474 (2017).\u003c/li\u003e\n\u003cli\u003eSchoning, J. M.\u003cem\u003e et al.\u003c/em\u003e Surveillance of bovine tuberculosis and risk estimation of a future reservoir formation in wildlife in Switzerland and Liechtenstein. \u003cem\u003ePLoS One\u003c/em\u003e 8, e54253, doi:10.1371/journal.pone.0054253 (2013).\u003c/li\u003e\n\u003cli\u003eDorn-In, S.\u003cem\u003e et al.\u003c/em\u003e Shedding of \u003cem\u003eMycobacterium caprae \u003c/em\u003eby wild red deer (\u003cem\u003eCervus elaphus\u003c/em\u003e) in the Bavarian alpine regions, Germany. \u003cem\u003eTransbound. Emerg. Dis.\u003c/em\u003e 67, 308-317, doi:10.1111/tbed.13353 (2020).\u003c/li\u003e\n\u003cli\u003eCourcoul, A.\u003cem\u003e et al.\u003c/em\u003e Estimation of sensitivity and specificity of bacteriology, histopathology and PCR for the confirmatory diagnosis of bovine tuberculosis using latent class analysis. \u003cem\u003ePLoS One\u003c/em\u003e 9, e90334, doi:10.1371/journal.pone.0090334 (2014).\u003c/li\u003e\n\u003cli\u003eGoosen, W. J.\u003cem\u003e et al.\u003c/em\u003e The VetMAX \u003cem\u003eM. tuberculosis\u003c/em\u003e complex PCR kit detects MTBC DNA in antemortem and postmortem samples from white rhinoceros (\u003cem\u003eCeratotherium simum\u003c/em\u003e), African elephants (\u003cem\u003eLoxodonta africana\u003c/em\u003e) and African buffaloes (\u003cem\u003eSyncerus caffer\u003c/em\u003e). \u003cem\u003eBMC Vet. Res.\u003c/em\u003e 16, 220, doi:10.1186/s12917-020-02438-9 (2020).\u003c/li\u003e\n\u003cli\u003eWarren, R. M.\u003cem\u003e et al.\u003c/em\u003e Differentiation of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex by PCR amplification of genomic regions of difference. \u003cem\u003eInt. J. Tuberc. Lung Dis.\u003c/em\u003e 10, 818-822 (2006).\u003c/li\u003e\n\u003cli\u003eKasai, H., Ezaki, T. \u0026amp; Harayama, S. Differentiation of phylogenetically related slowly growing mycobacteria by their \u003cem\u003egyrB \u003c/em\u003esequences. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 38, 301-308 (2000).\u003c/li\u003e\n\u003cli\u003eLandolt, P., Stephan, R., Stevens, M. J. A. \u0026amp; Scherrer, S. Three-reaction high-resolution melting assay for rapid differentiation of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex members. \u003cem\u003eMicrobiologyopen\u003c/em\u003e 8, doi:ARTN e91910.1002/mbo3.919 (2019).\u003c/li\u003e\n\u003cli\u003eNiemann, S., Harmsen, D., R\u0026uuml;sch-Gerdes, S. \u0026amp; Richter, E. Differentiation of clinical \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex isolates by \u003cem\u003egyrB \u003c/em\u003eDNA sequence polymorphism analysis. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 38, 3231-3234, doi:Doi 10.1128/Jcm.38.9.3231-3234.2000 (2000).\u003c/li\u003e\n\u003cli\u003eCallahan, B. J.\u003cem\u003e et al.\u003c/em\u003e High-throughput amplicon sequencing of the full-length 16S rRNA gene with single-nucleotide resolution. \u003cem\u003eNucleic Acids Res.\u003c/em\u003e 47, e103, doi:10.1093/nar/gkz569 (2019).\u003c/li\u003e\n\u003cli\u003eEarl, J. P.\u003cem\u003e et al.\u003c/em\u003e Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes. \u003cem\u003eMicrobiome\u003c/em\u003e 6, 190, doi:10.1186/s40168-018-0569-2 (2018).\u003c/li\u003e\n\u003cli\u003eJohnson, J. S.\u003cem\u003e et al.\u003c/em\u003e Evaluation of 16S rRNA gene sequencing for species and strain-level microbiome analysis. \u003cem\u003eNat Commun\u003c/em\u003e 10, 5029, doi:10.1038/s41467-019-13036-1 (2019).\u003c/li\u003e\n\u003cli\u003eCurry, K. D.\u003cem\u003e et al.\u003c/em\u003e Emu: species-level microbial community profiling of full-length 16S rRNA Oxford Nanopore sequencing data. \u003cem\u003eNat Methods\u003c/em\u003e 19, 845-853, doi:10.1038/s41592-022-01520-4 (2022).\u003c/li\u003e\n\u003cli\u003eZorz, J.\u003cem\u003e et al.\u003c/em\u003e SituSeq: an offline protocol for rapid and remote Nanopore 16S rRNA amplicon sequence analysis. \u003cem\u003eISME Commun\u003c/em\u003e 3, 33, doi:10.1038/s43705-023-00239-3 (2023).\u003c/li\u003e\n\u003cli\u003eGopalaswamy, R., Shanmugam, S., Mondal, R. \u0026amp; Subbian, S. Of tuberculosis and non-tuberculous mycobacterial infections - a comparative analysis of epidemiology, diagnosis and treatment. \u003cem\u003eJ. Biomed. Sci.\u003c/em\u003e 27, 74, doi:10.1186/s12929-020-00667-6 (2020).\u003c/li\u003e\n\u003cli\u003eMaiga, M.\u003cem\u003e et al.\u003c/em\u003e Failure to recognize nontuberculous mycobacteria leads to misdiagnosis of chronic pulmonary tuberculosis. \u003cem\u003ePLoS One\u003c/em\u003e 7, e36902, doi:10.1371/journal.pone.0036902 (2012).\u003c/li\u003e\n\u003cli\u003eRiello, F. N.\u003cem\u003e et al.\u003c/em\u003e Diagnosis of mycobacterial infections based on acid-fast bacilli test and bacterial growth time and implications on treatment and disease outcome. \u003cem\u003eBMC Infect. Dis.\u003c/em\u003e 16, 142, doi:10.1186/s12879-016-1474-6 (2016).\u003c/li\u003e\n\u003cli\u003eGorsich, E. E.\u003cem\u003e et al.\u003c/em\u003e Opposite outcomes of coinfection at individual and population scales. \u003cem\u003eP Natl Acad Sci USA\u003c/em\u003e 115, 7545-7550, doi:10.1073/pnas.1801095115 (2018).\u003c/li\u003e\n\u003cli\u003eVierstraete, A. R. \u0026amp; Braeckman, B. P. Amplicon_sorter: A tool for reference-free amplicon sorting based on sequence similarity and for building consensus sequences. \u003cem\u003eEcol. Evol.\u003c/em\u003e 12, e8603, doi:10.1002/ece3.8603 (2022).\u003c/li\u003e\n\u003cli\u003eMacovei, L.\u003cem\u003e et al.\u003c/em\u003e The hidden \u0026apos;mycobacteriome\u0026apos; of the human healthy oral cavity and upper respiratory tract. \u003cem\u003eJ. Oral Microbiol.\u003c/em\u003e 7, 26094, doi:10.3402/jom.v7.26094 (2015).\u003c/li\u003e\n\u003cli\u003eZeineldin, M. M., Lehman, K., Camp, P., Farrell, D. \u0026amp; Thacker, T. C. Diagnostic evaluation of the IS\u003cem\u003e1081\u003c/em\u003e-targeted real-time PCR for detection of \u003cem\u003eMycobacterium bovis\u003c/em\u003e DNA in bovine milk samples. \u003cem\u003ePathogens\u003c/em\u003e 12, doi:10.3390/pathogens12080972 (2023).\u003c/li\u003e\n\u003cli\u003eCosta, P.\u003cem\u003e et al.\u003c/em\u003e Enhanced detection of tuberculous mycobacteria in animal tissues using a semi-nested probe-based real-time PCR. \u003cem\u003ePLoS One\u003c/em\u003e 8, e81337, doi:10.1371/journal.pone.0081337 (2013).\u003c/li\u003e\n\u003cli\u003eLorente-Leal, V.\u003cem\u003e et al.\u003c/em\u003e Validation of a real-time PCR for the detection of \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003ecomplex members in bovine tissue samples. \u003cem\u003eFront Vet Sci\u003c/em\u003e 6, 61, doi:10.3389/fvets.2019.00061 (2019).\u003c/li\u003e\n\u003cli\u003eLorente-Leal, V.\u003cem\u003e et al.\u003c/em\u003e Direct PCR on tissue samples to detect \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003ecomplex: an alternative to the bacteriological culture. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 59, doi:10.1128/JCM.01404-20 (2021).\u003c/li\u003e\n\u003cli\u003eAraujo, C. P.\u003cem\u003e et al.\u003c/em\u003e Detection of \u003cem\u003eMycobacterium bovis\u003c/em\u003e in bovine and bubaline tissues using nested-PCR for TbD1. \u003cem\u003ePLoS One\u003c/em\u003e 9, e91023, doi:10.1371/journal.pone.0091023 (2014).\u003c/li\u003e\n\u003cli\u003eParra, A.\u003cem\u003e et al.\u003c/em\u003e Development of a molecular diagnostic test applied to experimental abattoir surveillance on bovine tuberculosis. \u003cem\u003eVet. Microbiol.\u003c/em\u003e 127, 315-324, doi:10.1016/j.vetmic.2007.09.001 (2008).\u003c/li\u003e\n\u003cli\u003eThacker, T. C., Harris, B., Palmer, M. V. \u0026amp; Waters, W. R. Improved specificity for detection of \u003cem\u003eMycobacterium bovis\u003c/em\u003e in fresh tissues using IS\u003cem\u003e6110\u003c/em\u003e real-time PCR. \u003cem\u003eBMC Vet. Res.\u003c/em\u003e 7, 50, doi:10.1186/1746-6148-7-50 (2011).\u003c/li\u003e\n\u003cli\u003eLok, K. H.\u003cem\u003e et al.\u003c/em\u003e Molecular differentiation of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e strains without IS\u003cem\u003e6110\u003c/em\u003e insertions. \u003cem\u003eEmerg. Infect. Dis.\u003c/em\u003e 8, 1310-1313, doi:10.3201/eid0811.020291 (2002).\u003c/li\u003e\n\u003cli\u003eSteensels, D., Fauville-Dufaux, M., Boie, J. \u0026amp; De Beenhouwer, H. Failure of PCR-based IS\u003cem\u003e6110\u003c/em\u003e analysis to detect vertebral spondylodiscitis caused by \u003cem\u003eMycobacterium bovis\u003c/em\u003e. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 51, 366-368, doi:10.1128/JCM.02524-12 (2013).\u003c/li\u003e\n\u003cli\u003eBaker, M. G., Lopez, L. D., Cannon, M. C., De Lisle, G. W. \u0026amp; Collins, D. M. Continuing \u003cem\u003eMycobacterium bovis\u003c/em\u003e transmission from animals to humans in New Zealand. \u003cem\u003eEpidemiol. Infect.\u003c/em\u003e 134, 1068-1073, doi:10.1017/S0950268806005930 (2006).\u003c/li\u003e\n\u003cli\u003eGibson, A. L.\u003cem\u003e et al.\u003c/em\u003e Molecular epidemiology of disease due to \u003cem\u003eMycobacterium bovis\u003c/em\u003e in humans in the United Kingdom. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 42, 431-434, doi:10.1128/JCM.42.1.431-434.2004 (2004).\u003c/li\u003e\n\u003cli\u003eGuven Gokmen, T.\u003cem\u003e et al.\u003c/em\u003e Molecular characterization of \u003cem\u003eMycobacterium bovis\u003c/em\u003e strains isolated from cattle and humans by spoligotyping and 24-locus MIRU-VNTR, and prevalence of positive IGRA in slaughterhouse workers in Southern Turkey. \u003cem\u003eIran J Vet Res\u003c/em\u003e 23, 210-218, doi:10.22099/IJVR.2022.42580.6186 (2022).\u003c/li\u003e\n\u003cli\u003eLari, N., Rindi, L., Bonanni, D., Tortoli, E. \u0026amp; Garzelli, C. Molecular analysis of clinical isolates of \u003cem\u003eMycobacterium bovis\u003c/em\u003e recovered from humans in Italy. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 44, 4218-4221, doi:10.1128/JCM.01216-06 (2006).\u003c/li\u003e\n\u003cli\u003eOrtiz, A. P.\u003cem\u003e et al.\u003c/em\u003e Whole genome sequencing links \u003cem\u003eMycobacterium bovis\u003c/em\u003e from cattle, cheese and humans in Baja California, Mexico. \u003cem\u003eFront Vet Sci\u003c/em\u003e 8, 674307, doi:10.3389/fvets.2021.674307 (2021).\u003c/li\u003e\n\u003cli\u003ePalaniyandi, K.\u003cem\u003e et al.\u003c/em\u003e Isolation and comparative genomics of \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e isolates from cattle and their attendants in South India. \u003cem\u003eSci. Rep.\u003c/em\u003e 9, 17892, doi:10.1038/s41598-019-54268-x (2019).\u003c/li\u003e\n\u003cli\u003eWahdan, A., Riad, E. M. \u0026amp; Enany, S. Genetic differentiation of \u003cem\u003eMycobacterium bovis \u003c/em\u003eand \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003eisolated from cattle and human sources in, Egypt (Suez Canal area). \u003cem\u003eComp. Immunol. Microbiol. Infect. Dis.\u003c/em\u003e 73, 101553, doi:10.1016/j.cimid.2020.101553 (2020).\u003c/li\u003e\n\u003cli\u003eAllix-Beguec, C.\u003cem\u003e et al.\u003c/em\u003e Importance of identifying \u003cem\u003eMycobacterium bovis\u003c/em\u003e as a causative agent of human tuberculosis. \u003cem\u003eEur. Respir. J.\u003c/em\u003e 35, 692-694, doi:10.1183/09031936.00137309 (2010).\u003c/li\u003e\n\u003cli\u003eDuvallet, C., Gibbons, S. M., Gurry, T., Irizarry, R. A. \u0026amp; Alm, E. J. Meta-analysis of gut microbiome studies identifies disease-specific and shared responses. \u003cem\u003eNat Commun\u003c/em\u003e 8, 1784, doi:10.1038/s41467-017-01973-8 (2017).\u003c/li\u003e\n\u003cli\u003ePoyntz, H. C.\u003cem\u003e et al.\u003c/em\u003e Non-tuberculous mycobacteria have diverse effects on BCG efficacy against \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e. \u003cem\u003eTuberculosis (Edinb)\u003c/em\u003e 94, 226-237, doi:10.1016/j.tube.2013.12.006 (2014).\u003c/li\u003e\n\u003cli\u003eTanner, R., Villarreal-Ramos, B., Vordermeier, H. M. \u0026amp; McShane, H. The humoral immune response to BCG vaccination. \u003cem\u003eFront. Immunol.\u003c/em\u003e 10, 1317, doi:10.3389/fimmu.2019.01317 (2019).\u003c/li\u003e\n\u003cli\u003eVerma, D., Chan, E. D. \u0026amp; Ordway, D. J. Non-tuberculous mycobacteria interference with BCG-current controversies and future directions. \u003cem\u003eVaccines (Basel)\u003c/em\u003e 8, doi:10.3390/vaccines8040688 (2020).\u003c/li\u003e\n\u003cli\u003eMareledwane, V., Adesiyun, A. A. \u0026amp; Hlokwe, T. M. Absence of tuberculosis-causing cycobacteria from slaughtered livestock tissues and environmental samples, Gauteng Province, South Africa. \u003cem\u003eInt. J. Microbiol.\u003c/em\u003e 2024, 4636652, doi:10.1155/2024/4636652 (2024).\u003c/li\u003e\n\u003cli\u003eKomijn, R. E.\u003cem\u003e et al.\u003c/em\u003e Prevalence of \u003cem\u003eMycobacterium avium\u003c/em\u003e in slaughter pigs in The Netherlands and comparison of \u003cem\u003eIS1245 \u003c/em\u003erestriction fragment length polymorphism patterns of porcine and human isolates. \u003cem\u003eJ. Clin. Microbiol.\u003c/em\u003e 37, 1254-1259, doi:10.1128/JCM.37.5.1254-1259.1999 (1999).\u003c/li\u003e\n\u003cli\u003eGhielmetti, G.\u003cem\u003e et al.\u003c/em\u003e Mycobacterial infections in wild boars (\u003cem\u003eSus scrofa\u003c/em\u003e) from Southern Switzerland: Diagnostic improvements, epidemiological situation and zoonotic potential. \u003cem\u003eTransbound. Emerg. Dis.\u003c/em\u003e 68, 573-586, doi:10.1111/tbed.13717 (2021).\u003c/li\u003e\n\u003cli\u003eGcebe, N., Rutten, V. P. M. G., van Pittius, N. G., Naicker, B. \u0026amp; Michel, A. L. \u003cem\u003eMycobacterium komaniense\u003c/em\u003e sp. nov., a rapidly growing non-tuberculous \u003cem\u003eMycobacterium \u003c/em\u003especies detected in South Africa. \u003cem\u003eInt. J. Syst. Evol. Microbiol.\u003c/em\u003e 68, 1526-1532, doi:10.1099/ijsem.0.002707 (2018).\u003c/li\u003e\n\u003cli\u003eSmith, N. H.\u003cem\u003e et al.\u003c/em\u003e Ecotypes of the \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex. \u003cem\u003eJ. Theor. Biol.\u003c/em\u003e 239, 220-225, doi:10.1016/j.jtbi.2005.08.036 (2006).\u003c/li\u003e\n\u003cli\u003eMurphy, S. G.\u003cem\u003e et al.\u003c/em\u003e Direct detection of drug-resistant \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e using targeted next generation sequencing. \u003cem\u003eFront Public Health\u003c/em\u003e 11, 1206056, doi:10.3389/fpubh.2023.1206056 (2023).\u003c/li\u003e\n\u003cli\u003eSzoboszlay, M.\u003cem\u003e et al.\u003c/em\u003e Nanopore is preferable over Illumina for 16S amplicon sequencing of the gut microbiota when species-level taxonomic classification, accurate estimation of richness, or focus on rare taxa is required. \u003cem\u003eMicroorganisms\u003c/em\u003e 11, doi:10.3390/microorganisms11030804 (2023).\u003c/li\u003e\n\u003cli\u003eTafess, K.\u003cem\u003e et al.\u003c/em\u003e Targeted-sequencing workflows for comprehensive drug resistance profiling of \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003ecultures using two commercial sequencing platforms: comparison of analytical and diagnostic performance, turnaround time, and cost. \u003cem\u003eClin. Chem.\u003c/em\u003e 66, 809-820, doi:10.1093/clinchem/hvaa092 (2020).\u003c/li\u003e\n\u003cli\u003eDamene, H.\u003cem\u003e et al.\u003c/em\u003e Broad diversity of Mycobacterium tuberculosis complex strains isolated from humans and cattle in Northern Algeria suggests a zoonotic transmission cycle. \u003cem\u003ePLoS Negl. Trop. Dis.\u003c/em\u003e 14, e0008894, doi:10.1371/journal.pntd.0008894 (2020).\u003c/li\u003e\n\u003cli\u003eSanoussi, C. N., Affolabi, D., Rigouts, L., Anagonou, S. \u0026amp; de Jong, B. Genotypic characterization directly applied to sputum improves the detection of Mycobacterium africanum West African 1, under-represented in positive cultures. \u003cem\u003ePLoS Negl. Trop. Dis.\u003c/em\u003e 11, e0005900, doi:10.1371/journal.pntd.0005900 (2017).\u003c/li\u003e\n\u003cli\u003eBeissner, M., Phillips, R. O. \u0026amp; Bretzel, G. Determining Viability of M. ulcerans by 16S rRNA RT Reverse Transcriptase Real-Time PCR. \u003cem\u003eMethods Mol. Biol.\u003c/em\u003e 2387, 81-86, doi:10.1007/978-1-0716-1779-3_9 (2022).\u003c/li\u003e\n\u003cli\u003eSmith, K.\u003cem\u003e et al.\u003c/em\u003e Optimisation of the tuberculin skin test for detection of \u003cem\u003eMycobacterium bovis \u003c/em\u003ein African buffaloes (\u003cem\u003eSyncerus caffer\u003c/em\u003e). \u003cem\u003ePrev. Vet. Med.\u003c/em\u003e 188, 105254, doi:10.1016/j.prevetmed.2020.105254 (2021).\u003c/li\u003e\n\u003cli\u003eGoosen, W. J.\u003cem\u003e et al.\u003c/em\u003e Improved detection of \u003cem\u003eMycobacterium tuberculosis \u003c/em\u003eand \u003cem\u003eM. bovis\u003c/em\u003e in African wildlife samples using cationic peptide decontamination and mycobacterial culture supplementation. \u003cem\u003eJ. Vet. Diagn. Invest.\u003c/em\u003e 34, 61-67, doi:10.1177/10406387211044192 (2022).\u003c/li\u003e\n\u003cli\u003eBelakehal, F.\u003cem\u003e et al.\u003c/em\u003e Evaluation of the discriminatory power of spoligotyping and 19-locus mycobacterial interspersed repetitive unit-variable number of tandem repeat analysis (MIRU-VNTR) of \u003cem\u003eMycobacterium bovis\u003c/em\u003e strains isolated from cattle in Algeria. \u003cem\u003ePLoS One\u003c/em\u003e 17, e0262390, doi:10.1371/journal.pone.0262390 (2022).\u003c/li\u003e\n\u003cli\u003eGhielmetti, G.\u003cem\u003e et al.\u003c/em\u003e Advancing animal tuberculosis surveillance using culture-independent long-read whole-genome sequencing. \u003cem\u003eFront. Microbiol.\u003c/em\u003e 14, doi:ARTN 1307440 10.3389/fmicb.2023.1307440 (2023).\u003c/li\u003e\n\u003cli\u003eRupf, S., Merte, K. \u0026amp; Eschrich, K. Quantification of bacteria in oral samples by competitive polymerase chain reaction. \u003cem\u003eJ. Dent. Res.\u003c/em\u003e 78, 850-856, doi:10.1177/00220345990780040501 (1999).\u003c/li\u003e\n\u003cli\u003eWick, R. R., Judd, L. M. \u0026amp; Holt, K. E. Performance of neural network basecalling tools for Oxford Nanopore sequencing. \u003cem\u003eGenome Biol.\u003c/em\u003e 20, 129, doi:10.1186/s13059-019-1727-y (2019).\u003c/li\u003e\n\u003cli\u003eSteinig, E. \u0026amp; Coin, L. Nanoq: ultra-fast quality control for nanopore reads. \u003cem\u003eJOSS\u003c/em\u003e 7 (2022).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"African buffaloes, culture-independent, mycobacteriome, Mycobacterium bovis, Oxford nanopore technology, targeted next-generation sequencing","lastPublishedDoi":"10.21203/rs.3.rs-4329505/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4329505/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAnimal tuberculosis significantly challenges global health, agriculture, and wildlife conservation efforts. Mycobacterial cultures necessitate stringent biosafety measures due to the risk of laboratory-acquired infections. In this study, we employed a culture-independent approach, using targeted long-read-based next-generation sequencing (tNGS), to investigate the mycobacterial composition in DNA extracted from \u003cem\u003eMycobacterium bovis\u003c/em\u003e infected culture-confirmed African buffalo tissue. We detected mycobacterial DNA in 93.3% of the samples and the sensitivity for detecting \u003cem\u003eMycobacterium tuberculosis\u003c/em\u003e complex (MTBC) was 91.7%, demonstrating a high concordance of our culture-independent tNGS approach with mycobacterial culture results.\u003c/p\u003e \u003cp\u003eWe identified heterogenous mycobacterial populations with various non-tuberculous mycobacteria, including members of the \u003cem\u003eMycobacterium avium\u003c/em\u003e complex, \u003cem\u003eM. smegmatis\u003c/em\u003e, and \u003cem\u003eM. komaniense\u003c/em\u003e. The latter \u003cem\u003eMycobacterium\u003c/em\u003e species was described in South Africa from bovine nasal swabs and environmental samples from the Hluhluwe-iMfolozi Park, which was the origin of the buffalo samples in the present study. This finding suggests that mycobacterial DNA found in the environment may confound detection of MTBC in wildlife.\u003c/p\u003e \u003cp\u003eIn conclusion, our approach represents an alternative to conventional methods for detecting mycobacterial DNA. This high-throughput technique enables the differentiation of heterogeneous mycobacterial populations and facilitates relative quantification, which will contribute valuable insights into the epidemiology, pathogenesis, and microbial synergy during mycobacterial infections.\u003c/p\u003e","manuscriptTitle":"Insights into Mycobacteriome Composition in Mycobacterium bovis-Infected African Buffalo (Syncerus caffer) Tissue Samples: A Culture-Independent Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-05 09:02:18","doi":"10.21203/rs.3.rs-4329505/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-19T05:39:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-18T08:52:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-10T15:13:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227926332207679348539251600282625488267","date":"2024-06-04T18:37:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"275934795783807960313741042265729967489","date":"2024-06-04T13:51:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-04T13:40:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-04T13:35:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-29T05:30:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-23T13:23:21+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-04-26T11:53:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c844d07b-1168-4a2b-a1b9-1a62509f1dfa","owner":[],"postedDate":"June 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32824993,"name":"Biological sciences/Microbiology/Infectious disease diagnostics"},{"id":32824994,"name":"Biological sciences/Microbiology/Pathogens"}],"tags":[],"updatedAt":"2024-08-05T16:06:56+00:00","versionOfRecord":{"articleIdentity":"rs-4329505","link":"https://doi.org/10.1038/s41598-024-68189-x","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-07-30 15:58:08","publishedOnDateReadable":"July 30th, 2024"},"versionCreatedAt":"2024-06-05 09:02:18","video":"","vorDoi":"10.1038/s41598-024-68189-x","vorDoiUrl":"https://doi.org/10.1038/s41598-024-68189-x","workflowStages":[]},"version":"v1","identity":"rs-4329505","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4329505","identity":"rs-4329505","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}