Background: Globally, Pseudomonas aeruginosa is a high-priority opportunistic pathogen which displays several intrinsic and acquired antimicrobial resistance (AMR) mechanisms, leading to challenging treatments and mortality of patients. Moreover, its wide virulence arsenal, particularly the type III secretion system (T3SS) exoU⁺ virulotype, plays a crucial role in pathogenicity and poor outcome of infections. In depth insights into the molecular epidemiology of P. aeruginosa, especially the prevalence of high-risk clones (HRCs), are crucial for the comprehension of virulence and AMR features and their dissemination among distinct strains. This study aims to evaluate the prevalence and distribution of HRCs and non-HRCs among Brazilian isolates of P. aeruginosa. Methods: A systematic review and meta-analysis were conducted on studies published between 2011 and 2023, focusing on the prevalence of P. aeruginosa clones determined by multilocus sequence typing (MLST) in Brazil. Data were extracted from retrospective cross-sectional and case-control studies, encompassing clinical and non-clinical samples. The analysis included calculating the prevalence rates of various sequence types (STs) and assessing the regional variability in the distribution of HRCs and non-HRCs. Results: A total of 872 samples were analyzed within all studies, of which 298 (34.17%) were MLST typed, identifying 78 unique STs. HRCs accounted for 48.90% of the MLST-typed isolates, with ST277 being the most prevalent (100/298—33.55%), followed by ST244 (29/298—9.73%), ST235 (13/298—4.36%), ST111 (2/298—0.67%), and ST357 (2/298—0.67%). Significant regional variability was observed, with the Southeast region showing a high prevalence of ST277, while the North region shows a high prevalence of MLST-typed samples and HRCs. Conclusions: Finally, this systematic review and meta-analysis highlight the role of P. aeruginosa clones in critical issue of AMR in P. aeruginosa in Brazil and the need of integration of comprehensive data from individual studies.

Pseudomonas aeruginosa is a high-priority bacterial agent that causes healthcare-acquired infections (HAIs), which often leads to serious infections and poor prognosis in vulnerable patients. Its increasing resistance to antimicrobials, associated with SPM production, is a case of public health concern. Therefore, this study aims to determine the antimicrobial resistance, virulence, and genotyping features of P. aeruginosa strains producing SPM-1 in the Northern region of Brazil. To determine the presence of virulence and resistance genes, the PCR technique was used. For the susceptibility profile of antimicrobials, the Kirby–Bauer disk diffusion method was performed on Mueller–Hinton agar. The MLST technique was used to define the ST of the isolates. The exoS⁺/exoU⁻ virulotype was standard for all strains, with the aprA, lasA, toxA, exoS, exoT, and exoY genes as the most prevalent. All the isolates showed an MDR or XDR profile against the six classes of antimicrobials tested. HRC ST277 played a major role in spreading the SPM-1-producing P. aeruginosa strains.

Bedaquiline, an antimicrobial used to treat drug-resistant tuberculosis (DR-TB), was introduced in Brazil in October 2021. Monitoring the emergence and transmission of DR-TB is crucial for implementing public health to control the spread of DR strains of Mycobacterium tuberculosis. To measure its impact on the multi-drug treatment scheme in the state of Pará, we aimed to conduct genomic surveillance of DR-TB after bedaquiline was introduced in Brazil. Individuals treated for DR-TB between October 2021 and December 2022, in the reference hospital to treat DR-TB cases from the state of Pará, were included in the study. Clinical and bacteriological information was obtained from the National Laboratory Management Environment and the Special TB Treatment Information System. Genomic DNA was extracted from bacterial cultures performed at the Pará Central Laboratory (LACEN-PA). Whole-genome sequencing (WGS) was obtained using Illumina Nextera-XT and NextSeq 550 and genomes were analyzed using the MAGMA and TB-Profiler pipelines interpreted according to the World Health Organization (WHO) mutations catalog 2nd edition. Geoprocessing was performed based on the patient’s residences. Cutoffs of 5–12 single nucleotide polymorphisms (SNPs) were used for transmission analysis. From the 103 patients reported as DR-TB, viable cultures were obtained from 67. Forty isolates were selected randomly for WGS. Among these, a mixed infection of M. tuberculosis L1 and L4 and a co-infection of M. tuberculosis and Mycobacterium chelonae were observed. The genotypic drug susceptibility profile of TB stains (39/40) was as follows: sensitive (1/2, 5%), rifampicin mono-resistant (RR) (4/10%), isoniazid mono-resistant (1/2%), multidrug-resistant (MDR) (21/52%), extensively drug-resistant (XDR) (3/7%), pre-XDR (8/20%), and other (1/2%). Among the 38 isolates of M. tuberculosis strains without mixed infection, using a cutoff of 12 SNPs and suggestive of recent TB transmission, 14 (37%) were grouped into five clusters (C1–C5) and included RR (C5), MDR (C3, C4, C5), pre-XDR, and XDR (C2) strains. We recommend greater attention from the regional public health authorities to detect and track resistance to new drugs, especially in areas with pre-XDR and XDR cases. This is the first report on the detection and transmission of XDR-TB in Pará, Brazil, after the recent re-definition of XDR-TB by the WHO in 2021.

Mycobacterium tuberculosis (Mtb) Central Asian Strain (CAS) Lineage 3 (L3) genotype is predominantly found in East-Africa, Central-Asia, Western-Asia, and South-Asia; however, a new spoligotyping CAS/SIT2545 was found in northern regions of Brazil. We aimed to characterize and describe the genetic diversity and perform a phylogenetic assessment of this novel genotype. We performed 24-MIRU-VNTR loci and Whole-genome sequencing (WGS) of six Brazilian isolates previously spoligotyped. The libraries were prepared using a Nextera-XT kit and sequenced in a NextSeq 550 Illumina instrument. We performed lineage assignment and genomic characterization. From publicly available genomes of Mtb L3 and other lineages, we created a robust dataset to run the MTBSeq pipeline and perform a phylogenetic analysis. MIRU-VNTR and WGS confirmed CAS/SIT2545 belongs to L3. Out of 1691 genomes, 1350 (79.83%) passed in quality control (genomic coverage > 95%). Strain 431 differed in 52 single nucleotide variants (SNV), confirming it does not belong to the same transmission chain. The eight genomes from a global dataset clustered closer to Brazilian strains differed in >52 SNVs. We hypothesized L3 and L1 were introduced in Brazilian Northern in the same historical event; however, there is a need for additional studies exploring the genetic diversity of Mtb Brazilian Northern.

The MTBseq pipeline, published in 2018, was designed to address bioinformatics challenges in tuberculosis research using whole-genome sequencing data. It was the first publicly available pipeline on GitHub to perform full analysis of whole-genome sequencing (WGS) data for Mycobacterium tuberculosis encompassing quality control through mapping, variant calling for lineage classification, drug resistance prediction, and phylogenetic inference. However, the pipeline's architecture is not optimal for analyses on high-performance computing or cloud computing environments, which often involve large datasets. To optimize the pipeline, we created MTBseq-nf, a Nextflow wrapper which offers shorter execution times through parallelization along with multiple other key improvements. The MTBseq-nf wrapper, as opposed to the linear, batched analysis of samples in the TBfull step of MTBseq pipeline, can execute multiple instances of the same step in parallel and therefore makes full use of the provided computational resources. For evaluation of scalability and reproducibility, we used 90 M. tuberculosis genomes (European Nucleotide Archive - ENA accession PRJEB7727) for the benchmarking analysis on a dedicated computational server. In our experiments the execution time of MTBseq-nf parallel analysis mode is at least twice as fast as the standard MTBseq pipeline for more than 20 samples. Furthermore, the MTBseq-nf wrapper facilitates reproducibility using the nf-core, bioconda, and biocontainers projects for platform independence. The proposed MTBseq-nf wrapper pipeline is, user-friendly, optimized for hardware efficiency, scalable for larger datasets, and exhibits improved reproducibility.

Globally, tuberculosis (TB) remains a top cause of death from infectious diseases, with an estimated 1.5 million deaths annually. Given its substantial social and economic burden, TB is a priority in the United Nations 2030 Agenda for Sustainable Development. The WHO’s End TB Strategy emphasises research, innovation, and the rapid implementation of new technologies such as whole genome sequencing (WGS), which are pivotal for precision health approaches and drug-resistant TB (DR-TB) surveillance. This study aims to strengthen genomic TB surveillance in the North and Northeast Brazilian regions by applying WGS to study DR-TB cases, training professionals in genomics and bioinformatics, and deploying a national surveillance platform (GEMIBRA). This is an observational, cross-sectional, prospective, quantitative and qualitative study to be conducted in the states of Pará, Amazonas, Ceará, and Bahia. A total of 500 Mycobacterium tuberculosis complex (MTBC) isolates from DR-TB cases will undergo WGS, representing 87% of the expected DR-TB cases, including cases of non-tuberculous mycobacteria (NTM) isolates among the DR samples. Data will be analyzed for genotype-phenotype correlations, mutation patterns, and associations with clinical and epidemiological characteristics. Capacity-building activities, including theoretical and hands-on bioinformatics training, will be carried out. The GEMIBRA platform will support data visualization, spatial distribution, and clinical decision-making. The project will generate evidence for validate the contribution of the integration of WGS into Brazil’s TB surveillance system, support precision treatment approaches, and inform public health interventions. It will also contribute to workforce development and the introduction of decentralized WGS-based diagnostics in resource-limited regions. The project adopts a translational research model and a networked, decentralised approach, facilitating the prompt integration of the knowledge generated into public health practice. Ultimately, this work will contribute to combating TB transmission by identifying transmission dynamics, emerging resistant strains, and informing the National Plan to End TB as a public health problem.