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The transition from MIRU-VNTR-based epidemiology studies in tuberculosis (TB) to genomic epidemiology has transformed how we track transmission. However, short-read sequencing is poor at analyzing repetitive regions such as the MIRU-VNTR loci. This causes a gap between the new genomic data and the large amount of information stored in historical databases. Long-read sequencing could bridge this knowledge gap by allowing analysis of repetitive regions. However, the feasibility of extracting MIRU-VNTRs from long reads and linking them to historical data has not been evaluated. In our study, an in silico arm, consisting of inference of MIRU patterns from long-read sequences (using MIRUReader program), was compared with an experimental arm, involving standard amplification and fragment sizing. We analyzed overall performance on 39 isolates from South Africa and confirmed reproducibility in a sample enriched with 62 clustered cases from Spain. Finally, we ran 25 consecutive incident cases, demonstrating the feasibility of correctly assigning new clustered/orphan cases by linking data inferred from genomic analysis to MIRU-VNTR databases. Of the 3,024 loci analyzed, only 11 discrepancies (0.36%) were found between the two arms: three attributed to experimental error and eight to misassigned alleles from long-read sequencing. A second round of analysis of these discrepancies resulted in agreement between the experimental and in silico arms in all but one locus. Adjusting the MIRUReader program code allowed us to flag potential in silico misassignments due to suboptimal coverage or unfixed double alleles. Our study indicates that long-read sequencing could help address potential chronological and geographical gaps arising from the transition from molecular to genomic epidemiology of tuberculosis., Importance: The transition from molecular epidemiology in tuberculosis (TB), based on the analysis of repetitive regions (VNTR-based genotyping), to genomic epidemiology transforms in the precision with which we track transmission. However, short-read sequencing, the most common method for performing genomic analysis, is poor at analyzing repetitive regions. This means that we face a gap between the new genomic data and the large amount of information stored in historical databases, which is also an obstacle to cross-national surveillance involving settings where only molecular data are available. Long-read sequencing could help bridge this knowledge gap by allowing analysis of repetitive regions. Our study demonstrates that MIRU-VNTR patterns can be successfully inferred from long-read sequences, allowing the correct assignment of new cases as clustered/orphan by linking new data extracted from genomic analysis to historical MIRU-VNTR databases. Our data may provide a starting point for bridging the knowledge gap between the molecular and genomic eras in tuberculosis epidemiology., Competing Interests: The authors declare no conflict of interest.

Introduction Mycobacterium caprae is a member of the Mycobacterium tuberculosis complex (MTBC) not routinely identified to species level. It lacks specific clinical features of presentation and may therefore not be identified as the causative agent of tuberculosis. Use of whole genome sequencing (WGS) in the investigation of a family microepidemic of tuberculosis in Almería, Spain, unexpectedly identified the involvement of M. caprae .AimWe aimed to evaluate the presence of additional unidentified M. caprae cases and to determine the magnitude of this occurrence.MethodsFirst-line characterisation of the MTBC isolates was done by MIRU-VNTR, followed by WGS. Human and animal M. caprae isolates were integrated in the analysis.ResultsA comprehensive One Health strategy allowed us to (i) detect other 11 M. caprae infections in humans in a period of 18 years, (ii) systematically analyse M. caprae infections on an epidemiologically related goat farm and (iii) geographically expand the study by including 16 M. caprae isolates from other provinces. Integrative genomic analysis of 41 human and animal M. caprae isolates showed a high diversity of strains. The animal isolates' diversity was compatible with long-term infection, and close genomic relationships existed between isolates from goats on the farm and recent cases of M. caprae infection in humans.DiscussionZoonotic circulation of M. caprae strains had gone unnoticed for 18 years. Systematic characterisation of MTBC at species level and/or extended investigation of the possible sources of exposure in all tuberculosis cases would minimise the risk of overlooking similar zoonotic events.

Laundry sector consumes a huge amount of water which is usually discharged as wastewater instead of being reused. The application of biological treatment of laundry wastewater coupled with post-treatment utilizing advanced oxidation processes creates a possibility to recycle water to the washing process. However, the investigations on such systems are very limited. In the present work, a novel approach of post-treatment of laundry wastewater utilizing solar photo-Fenton operated at a pilot scale in a compound parabolic collector (CPC) photoreactor is proposed. Sodium dodecyl sulfate (SDS) was used as a representative of surfactants applied in the laundry system. The effect of feed matrix was investigated using distilled water as a reference matrix and synthetic wastewater simulating the composition of biologically pre-treated laundry wastewater. Different concentrations of H 2 O 2 (50-400 mg/L) and ferrous iron (2.75-10 mg/L) were assayed. For comparison purpose, experiments at neutral pH using ethylenediamine-N,N'-disuccinic acid (EDDS) as an iron complexing agent were carried out. A high SDS removal efficiency was obtained under both neutral and acidic pH, reaching 89% and 96%, respectively, in just 8 min. However, the remaining organic load originating from EDDS needs application of further post-treatment steps. Therefore, the solar photo-Fenton operated under acidic pH was found to be a more promising approach of post-treatment of laundry wastewater aimed at its reuse.