Monitoring of First-line Drug Resistance Mutations Outside the Scope of Xpert MTB/RIF Ultra is Needed for Successful Control of DR-TB in Southern Mozambique.

Multidrug-resistant(MDR) tuberculosis in Southern Africa is of great concern, exacerbated by the spread of a clone harboring a mutation missed by Xpert Ultra. In Southern Mozambique, the presence of such mutation and rising cases of non-MDR isoniazid resistance highlights the need to ensure accurate detection of antimicrobial-resistance in the country.

Towards next-generation diagnostics for tuberculosis: identification of novel molecular targets by large-scale comparative genomics.

MOTIVATION: Tuberculosis (TB) remains one of the main causes of death worldwide. The long and cumbersome process of culturing Mycobacterium tuberculosis complex (MTBC) bacteria has encouraged the development of specific molecular tools for detecting the pathogen. Most of these tools aim to become novel TB diagnostics, and big efforts and resources are invested in their development, looking for the endorsement of the main public health agencies. Surprisingly, no study has been conducted where the vast amount of genomic data available is used to identify the best MTBC diagnostic markers. RESULTS: In this work, we used large-scale comparative genomics to identify 40 MTBC-specific loci. We assessed their genetic diversity and physiological features to select 30 that are good targets for diagnostic purposes. Some of these markers could be used to assess the physiological status of the bacilli. Remarkably, none of the most used MTBC markers is in our catalog. Illustrating the translational potential of our work, we develop a specific qPCR assay for quantification and identification of MTBC DNA. Our rational design of targeted molecular assays for TB could be used in many other fields of clinical and basic research. AVAILABILITY AND IMPLEMENTATION: The database of non-tuberculous mycobacteria assemblies can be accessed at: 10.5281/zenodo.3374377. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Cryptic Resistance Mutations Associated With Misdiagnoses of Multidrug-Resistant Tuberculosis.

Understanding why some multidrug-resistant tuberculosis cases are not detected by rapid phenotypic and genotypic routine clinical tests is essential to improve diagnostic assays and advance toward personalized tuberculosis treatment. Here, we combine whole-genome sequencing with single-colony phenotyping to identify a multidrug-resistant strain that had infected a patient for 9 years. Our investigation revealed the failure of rapid testing and genome-based prediction tools to identify the multidrug-resistant strain. The false-negative findings were caused by uncommon rifampicin and isoniazid resistance mutations. Although whole-genome sequencing data helped to personalize treatment, the patient developed extensively drug-resistant tuberculosis, highlighting the importance of coupling new diagnostic methods with appropriate treatment regimens.

High-resolution mapping of tuberculosis transmission: Whole genome sequencing and phylogenetic modelling of a cohort from Valencia Region, Spain.

BACKGROUND: Whole genome sequencing provides better delineation of transmission clusters in Mycobacterium tuberculosis than traditional methods. However, its ability to reveal individual transmission links within clusters is limited. Here, we used a 2-step approach based on Bayesian transmission reconstruction to (1) identify likely index and missing cases, (2) determine risk factors associated with transmitters, and (3) estimate when transmission happened. METHODS AND FINDINGS: We developed our transmission reconstruction method using genomic and epidemiological data from a population-based study from Valencia Region, Spain. Tuberculosis (TB) incidence during the study period was 8.4 cases per 100,000 people. While the study is ongoing, the sampling frame for this work includes notified TB cases between 1 January 2014 and 31 December 2016. We identified a total of 21 transmission clusters that fulfilled the criteria for analysis. These contained a total of 117 individuals diagnosed with active TB (109 with epidemiological data). Demographic characteristics of the study population were as follows: 80/109 (73%) individuals were Spanish-born, 76/109 (70%) individuals were men, and the mean age was 42.51 years (SD 18.46). We found that 66/109 (61%) TB patients were sputum positive at diagnosis, and 10/109 (9%) were HIV positive. We used the data to reveal individual transmission links, and to identify index cases, missing cases, likely transmitters, and associated transmission risk factors. Our Bayesian inference approach suggests that at least 60% of index cases are likely misidentified by local public health. Our data also suggest that factors associated with likely transmitters are different to those of simply being in a transmission cluster, highlighting the importance of differentiating between these 2 phenomena. Our data suggest that type 2 diabetes mellitus is a risk factor associated with being a transmitter (odds ratio 0.19 [95% CI 0.02-1.10], p < 0.003). Finally, we used the most likely timing for transmission events to study when TB transmission occurred; we identified that 5/14 (35.7%) cases likely transmitted TB well before symptom onset, and these were largely sputum negative at diagnosis. Limited within-cluster diversity does not allow us to extrapolate our findings to the whole TB population in Valencia Region. CONCLUSIONS: In this study, we found that index cases are often misidentified, with downstream consequences for epidemiological investigations because likely transmitters can be missed. Our findings regarding inferred transmission timing suggest that TB transmission can occur before patient symptom onset, suggesting also that TB transmits during sub-clinical disease. This result has direct implications for diagnosing TB and reducing transmission. Overall, we show that a transition to individual-based genomic epidemiology will likely close some of the knowledge gaps in TB transmission and may redirect efforts towards cost-effective contact investigations for improved TB control.

The impact of virus population diversity on the dynamics of cytomegalovirus DNAemia in allogeneic stem cell transplant recipients.

Mixed cytomegalovirus (CMV) infections are associated with delayed viral clearance in solid organ transplant recipients. We investigated whether this could be extrapolated to allogeneic stem cell transplant (allo-SCT) recipients. A total of 48 plasma specimens, obtained during 29 episodes of active CMV infection in 25 non-consecutive allo-SCT patients, were analysed. Baseline blood specimens, drawn shortly prior to the inception of pre-emptive antiviral therapy (pre-treatment specimen; n=29), as well as follow-up samples obtained either after the initiation of antiviral therapy (post-treatment specimen; n=15) or during recurrent episodes (n=4) were analysed. Plasma CMV DNA loads were quantified by real-time PCR and the CMV genotyping was performed by ultra-deep sequencing of hypervariable regions in the genes coding for glycoproteins N (gN) and O (gO). A trend towards higher CMV DNA peak loads, longer CMV DNAemia episode durations and slower CMV DNAemia decay rates was observed for episodes with mixed CMV genotype populations compared to those caused by single CMV variants, although the differences did not reach statistical significance. The length of the treatment course required to clear DNAemia was significantly longer in these mixed episodes (P=0.002). Significant changes in the number or frequency of CMV gN or gO genetic variants were documented following the initiation of antiviral therapy or in recurrent episodes. CMV diversity may have a major impact on the kinetics of CMV DNAemia clearance during the treatment of active CMV infection episodes in allo-SCT recipients.

Role of the first WHO mutation catalogue in the diagnosis of antibiotic resistance in Mycobacterium tuberculosis in the Valencia Region, Spain: a retrospective genomic analysis.

BACKGROUND: In June, 2021, WHO published the most complete catalogue to date of resistance-conferring mutations in Mycobacterium tuberculosis. Here, we aimed to assess the performance of genome-based antimicrobial resistance prediction using the catalogue and its potential for improving diagnostics in a real low-burden setting. METHODS: In this retrospective population-based genomic study M tuberculosis isolates were collected from 25 clinical laboratories in the low-burden setting of the Valencia Region, Spain. Culture-positive tuberculosis cases reported by regional public health authorities between Jan 1, 2014, and Dec 31, 2016, were included. The drug resistance profiles of these isolates were predicted by the genomic identification, via whole-genome sequencing (WGS), of the high-confidence resistance-causing variants included in the catalogue and compared with the phenotype. We determined the minimum inhibitory concentration (MIC) of the isolates with discordant resistance profiles using the resazurin microtitre assay. FINDINGS: WGS was performed on 785 M tuberculosis complex culture-positive isolates, and the WGS resistance prediction sensitivities were: 85·4% (95% CI 70·8-94·4) for isoniazid, 73·3% (44·9-92·2) for rifampicin, 50·0% (21·1-78·9) for ethambutol, and 57·1% (34·0-78·2) for pyrazinamide; all specificities were more than 99·6%. Sensitivity values were lower than previously reported, but the overall pan-susceptibility accuracy was 96·4%. Genotypic analysis revealed that four phenotypically susceptible isolates carried mutations (rpoB Leu430Pro and rpoB Ile491Phe for rifampicin and fabG1 Leu203Leu for isoniazid) known to give borderline resistance in standard phenotypic tests. Additionally, we identified three putative resistance-associated mutations (inhA Ser94Ala, katG Leu48Pro, and katG Gly273Arg for isoniazid) in samples with substantially higher MICs than those of susceptible isolates. Combining both genomic and phenotypic data, in accordance with the WHO diagnostic guidelines, we could detect two new multidrug-resistant cases. Additionally, we detected 11 (1·6%) of 706 isolates to be monoresistant to fluoroquinolone, which had been previously undetected. INTERPRETATION: We showed that the WHO catalogue enables the detection of resistant cases missed in phenotypic testing in a low-burden region, thus allowing for better patient-tailored treatment. We also identified mutations not included in the catalogue, relevant at the local level. Evidence from this study, together with future updates of the catalogue, will probably lead in the future to the partial replacement of culture testing with WGS-based drug susceptibility testing in our setting. FUNDING: European Research Council and the Spanish Ministerio de Ciencia.

Characterization of a unique repression system present in arbitrium phages of the SPbeta family.

Arbitrium-coding phages use peptides to communicate and coordinate the decision between lysis and lysogeny. However, the mechanism by which these phages establish lysogeny remains unknown. Here, focusing on the SPbeta phage family's model phages phi3T and SPß, we report that a six-gene operon called the "SPbeta phages repressor operon" (sro) expresses not one but two master repressors, SroE and SroF, the latter of which folds like a classical phage integrase. To promote lysogeny, these repressors bind to multiple sites in the phage genome. SroD serves as an auxiliary repressor that, with SroEF, forms the repression module necessary for lysogeny establishment and maintenance. Additionally, the proteins SroABC within the operon are proposed to constitute the transducer module, connecting the arbitrium communication system to the activity of the repression module. Overall, this research sheds light on the intricate and specialized repression system employed by arbitrium SPß-like phages in making lysis-lysogeny decisions.

Deciphering the Tangible Spatio-Temporal Spread of a 25-Year Tuberculosis Outbreak Boosted by Social Determinants.

Outbreak strains of Mycobacterium tuberculosis are promising candidates as targets in the search for intrinsic determinants of transmissibility, as they are responsible for many cases with sustained transmission; however, the use of low-resolution typing methods and restricted geographical investigations represent flaws in assessing the success of long-lived outbreak strains. We can now address the nature of outbreak strains by combining large genomic data sets and phylodynamic approaches. We retrospectively sequenced the whole genome of representative samples assigned to an outbreak circulating in the Canary Islands (the GC strain) since 1993, which accounts for ~20% of local tuberculosis cases. We selected a panel of specific single nucleotide polymorphism (SNP) markers for an in-silico search for additional outbreak-related sequences within publicly available tuberculosis genomic data. Using this information, we inferred the origin, spread, and epidemiological parameters of the GC strain. Our approach allowed us to accurately trace the historical and more recent dispersion of the GC strain. We provide evidence of a highly successful nature within the Canarian archipelago but limited expansion abroad. Estimation of epidemiological parameters from genomic data disagree with a distinctive biology of the GC strain. With the increasing availability of genomic data allowing for the accurate inference of strain spread and critical epidemiological parameters, we can now revisit the link between Mycobacterium tuberculosis genotypes and transmission, as is routinely carried out for SARS-CoV-2 variants of concern. We demonstrate that social determinants rather than intrinsically higher bacterial transmissibility better explain the success of the GC strain. Importantly, our approach can be used to trace and characterize strains of interest worldwide. IMPORTANCE Infectious disease outbreaks represent a significant problem for public health. Tracing outbreak expansion and understanding the main factors behind emergence and persistence remain critical to effective disease control. Our study allows researchers and public health authorities to use Whole-Genome Sequencing-based methods to trace outbreaks, and shows how available epidemiological information helps to evaluate the factors underpinning outbreak persistence. Taking advantage of all the freely available information placed in public repositories, researchers can accurately establish the expansion of an outbreak beyond original boundaries, and determine the potential risk of a strain to inform health authorities which, in turn, can define target strategies to mitigate expansion and persistence. Finally, we show the need to evaluate strain transmissibility in different geographic contexts to unequivocally associate spread to local or pathogenic factors, an important lesson taken from genomic surveillance of SARS-CoV-2.

Tracking SARS-CoV-2 introductions in Mozambique using pandemic-scale phylogenies: a retrospective observational study.

BACKGROUND: From the start of the SARS-CoV-2 outbreak, global sequencing efforts have generated an unprecedented amount of genomic data. Nonetheless, unequal sampling between high-income and low-income countries hinders the implementation of genomic surveillance systems at the global and local level. Filling the knowledge gaps of genomic information and understanding pandemic dynamics in low-income countries is essential for public health decision making and to prepare for future pandemics. In this context, we aimed to discover the timing and origin of SARS-CoV-2 variant introductions in Mozambique, taking advantage of pandemic-scale phylogenies. METHODS: We did a retrospective, observational study in southern Mozambique. Patients from Manhiça presenting with respiratory symptoms were recruited, and those enrolled in clinical trials were excluded. Data were included from three sources: (1) a prospective hospital-based surveillance study (MozCOVID), recruiting patients living in Manhiça, attending the Manhiça district hospital, and fulfilling the criteria of suspected COVID-19 case according to WHO; (2) symptomatic and asymptomatic individuals with SARS-CoV-2 infection recruited by the National Surveillance system; and (3) sequences from SARS-CoV-2-infected Mozambican cases deposited on the Global Initiative on Sharing Avian Influenza Data database. Positive samples amenable for sequencing were analysed. We used Ultrafast Sample placement on Existing tRees to understand the dynamics of beta and delta waves, using available genomic data. This tool can reconstruct a phylogeny with millions of sequences by efficient sample placement in a tree. We reconstructed a phylogeny (~7·6 million sequences) adding new and publicly available beta and delta sequences. FINDINGS: A total of 5793 patients were recruited between Nov 1, 2020, and Aug 31, 2021. During this time, 133 328 COVID-19 cases were reported in Mozambique. 280 good quality new SARS-CoV-2 sequences were obtained after the inclusion criteria were applied and an additional 652 beta (B.1.351) and delta (B.1.617.2) public sequences were included from Mozambique. We evaluated 373 beta and 559 delta sequences. We identified 187 beta introductions (including 295 sequences), divided in 42 transmission groups and 145 unique introductions, mostly from South Africa, between August, 2020 and July, 2021. For delta, we identified 220 introductions (including 494 sequences), with 49 transmission groups and 171 unique introductions, mostly from the UK, India, and South Africa, between April and November, 2021. INTERPRETATION: The timing and origin of introductions suggests that movement restrictions effectively avoided introductions from non-African countries, but not from surrounding countries. Our results raise questions about the imbalance between the consequences of restrictions and health benefits. This new understanding of pandemic dynamics in Mozambique can be used to inform public health interventions to control the spread of new variants. FUNDING: European and Developing Countries Clinical Trials, European Research Council, Bill & Melinda Gates Foundation, and Agència de Gestió d'Ajuts Universitaris i de Recerca.

Genomic analysis of Mycobacterium brumae sustains its nonpathogenic and immunogenic phenotype.

Mycobacterium brumae is a rapid-growing, non-pathogenic Mycobacterium species, originally isolated from environmental and human samples in Barcelona, Spain. Mycobacterium brumae is not pathogenic and it's in vitro phenotype and immunogenic properties have been well characterized. However, the knowledge of its underlying genetic composition is still incomplete. In this study, we first describe the 4 Mb genome of the M. brumae type strain ATCC 51384T assembling PacBio reads, and second, we assess the low intraspecies variability by comparing the type strain with Illumina reads from three additional strains. Mycobacterium brumae genome is composed of a circular chromosome with a high GC content of 69.2% and containing 3,791 CDSs, 97 pseudogenes, one prophage and no CRISPR loci. Mycobacterium brumae has shown no pathogenic potential in in vivo experiments, and our genomic analysis confirms its phylogenetic position with other non-pathogenic and rapid growing mycobacteria. Accordingly, we determined the absence of virulence-related genes, such as ESX-1 locus and most PE/PPE genes, among others. Although the immunogenic potential of M. brumae was proved to be as high as Mycobacterium bovis BCG, the only mycobacteria licensed to treat cancer, the genomic content of M. tuberculosis T cell and B cell antigens in M. brumae genome is considerably lower than those antigens present in M. bovis BCG genome. Overall, this work provides relevant genomic data on one of the species of the mycobacterial genus with high therapeutic potential.

Prevalence of SARS-CoV-2 and co-infection with malaria during the first wave of the pandemic (the Burkina Faso case).

Africa accounts for 1.5% of the global coronavirus disease 2019 (COVID-19) cases and 2.7% of deaths, but this low incidence has been partly attributed to the limited testing capacity in most countries. In addition, the population in many African countries is at high risk of infection with endemic infectious diseases such as malaria. Our aim is to determine the prevalence and circulation of SARS-CoV-2 variants, and the frequency of co-infection with the malaria parasite. We conducted serological tests and microscopy examinations on 998 volunteers of different ages and sexes in a random and stratified population sample in Burkina-Faso. In addition, nasopharyngeal samples were taken for RT-qPCR of SARS-CoV-2 and for whole viral genome sequencing. Our results show a 3.2 and a 2.5% of SARS-CoV-2 seroprevalence and PCR positivity; and 22% of malaria incidence, over the sampling period, with marked differences linked to age. Importantly, we found 8 cases of confirmed co-infection and 11 cases of suspected co-infection mostly in children and teenagers. Finally, we report the genome sequences of 13 SARS-CoV-2 isolates circulating in Burkina Faso at the time of analysis, assigned to lineages A.19, A.21, B.1.1.404, B.1.1.118, B.1 and grouped into clades; 19B, 20A, and 20B. This is the first population-based study about SARS-CoV-2 and malaria in Burkina Faso during the first wave of the pandemic, providing a relevant estimation of the real prevalence of SARS-CoV-2 and variants circulating in this Western African country. Besides, it highlights the non-negligible frequency of co-infection with malaria in African communities.

Fine-grain population structure and transmission patterns of Mycobacterium tuberculosis in southern Mozambique, a high TB/HIV burden area.

Genomic studies of the Mycobacterium tuberculosis complex (MTBC) might shed light on the dynamics of its transmission, especially in high-burden settings, where recent outbreaks are embedded in the complex natural history of the disease. To this end, we conducted a 1 year prospective surveillance-based study in Mozambique. We applied whole-genome sequencing (WGS) to 295 positive cultures. We fully characterized MTBC isolates by phylogenetics and dating evaluation, and carried out a molecular epidemiology analysis to investigate further associations with pre-defined transmission risk factors. The majority of strains (49.5%, 136/275) belonged to lineage (L) 4; 57.8 % of them (159/275) were in genomic transmission clusters (cut-off 5 SNPs), and a strikingly high proportion (45.5%) shared an identical genotype (0 SNP pairwise distance). We found two 'likely endemic' clades, comprising 67 strains, belonging to L1.2, which dated back to the late 19th century and were associated with recent spread among people living with human immunodeficiency virus (PLHIV). We describe for the first time the population structure of MTBC in our region, a high tuberculosis (TB)/HIV burden area. Clustering analysis revealed an unforeseen pattern of spread and high rates of progression to active TB, suggesting weaknesses in TB control activities. The long-term presence of local strains in Mozambique, which were responsible for large transmission among HIV/TB-coinfected patients, calls into question the role of HIV in TB transmission.

Epidemiological and Genomic Analysis of a Large SARS-CoV-2 Outbreak in a Long-Term Care Facility in Catalonia, Spain.

Limiting outbreaks in long-term care facilities (LTCFs) is a cornerstone strategy to avoid an excess of COVID-19-related morbidity and mortality and to reduce its burden on the health system. We studied a large outbreak that occurred at an LTCF, combining methods of classical and genomic epidemiology analysis. The outbreak lasted for 31 days among residents, with an attack rate of 98% and 57% among residents and staff, respectively. The case fatality rate among residents was 16% (n = 15). Phylogenetic analysis of 59 SARS-CoV-2 isolates revealed the presence of two closely related viral variants in all cases (B.1.177 lineage), revealing a far more complex outbreak than initially thought and suggesting an initial spread driven by staff members. In turn, our results suggest that resident relocations to mitigate viral spread might have increased the risk of infection for staff members, creating secondary chains of transmission that were responsible for prolonging the outbreak. Our results highlight the importance of considering unnoticed chains of transmission early during an outbreak and making an adequate use and interpretation of diagnostic tests. Outbreak containment measures should be carefully tailored to each LTCF. IMPORTANCE The impact of COVID-19 on long-term care facilities (LTCFs) has been disproportionately large due to the high frailty of the residents. Here, we report epidemiological and genomic findings of a large outbreak that occurred at an LTCF, which ultimately affected almost all residents and nearly half of staff members. We found that the outbreak was initially driven by staff members; however, later resident relocation to limit the outbreak resulted in transmission from residents to staff members, evidencing the complexity and different phases of the outbreak. The phylogenetic analysis of SARS-CoV-2 isolates indicated that two closely related variants were responsible for the large outbreak. Our study highlights the importance of combining methods of classical and genomic epidemiology to take appropriate outbreak containment measures in LTCFs.

Population-based sequencing of Mycobacterium tuberculosis reveals how current population dynamics are shaped by past epidemics.

Transmission is a driver of tuberculosis (TB) epidemics in high-burden regions, with assumed negligible impact in low-burden areas. However, we still lack a full characterization of transmission dynamics in settings with similar and different burdens. Genomic epidemiology can greatly help to quantify transmission, but the lack of whole genome sequencing population-based studies has hampered its application. Here, we generate a population-based dataset from Valencia region and compare it with available datasets from different TB-burden settings to reveal transmission dynamics heterogeneity and its public health implications. We sequenced the whole genome of 785 Mycobacterium tuberculosis strains and linked genomes to patient epidemiological data. We use a pairwise distance clustering approach and phylodynamic methods to characterize transmission events over the last 150 years, in different TB-burden regions. Our results underscore significant differences in transmission between low-burden TB settings, i.e., clustering in Valencia region is higher (47.4%) than in Oxfordshire (27%), and similar to a high-burden area as Malawi (49.8%). By modeling times of the transmission links, we observed that settings with high transmission rate are associated with decades of uninterrupted transmission, irrespective of burden. Together, our results reveal that burden and transmission are not necessarily linked due to the role of past epidemics in the ongoing TB incidence, and highlight the need for in-depth characterization of transmission dynamics and specifically tailored TB control strategies.

An evolutionary functional genomics approach identifies novel candidate regions involved in isoniazid resistance in Mycobacterium tuberculosis.

Efforts to eradicate tuberculosis are hampered by the rise and spread of antibiotic resistance. Several large-scale projects have aimed to specifically link clinical mutations to resistance phenotypes, but they were limited in both their explanatory and predictive powers. Here, we combine functional genomics and phylogenetic associations using clinical strain genomes to decipher the architecture of isoniazid resistance and search for new resistance determinants. This approach has allowed us to confirm the main target route of the antibiotic, determine the clinical relevance of redox metabolism as an isoniazid resistance mechanism and identify novel candidate genes harboring resistance mutations in strains with previously unexplained isoniazid resistance. This approach can be useful for characterizing how the tuberculosis bacilli acquire resistance to new antibiotics and how to forestall them.

Accuracy of an amplicon-sequencing nanopore approach to identify variants in tuberculosis drug-resistance-associated genes.

A rapid and accurate diagnostic assay represents an important means to detect Mycobacterium tuberculosis, identify drug-resistant strains and ensure treatment success. Currently employed techniques to diagnose drug-resistant tuberculosis include slow phenotypic tests or more rapid molecular assays that evaluate a limited range of drugs. Whole-genome-sequencing-based approaches can detect known drug-resistance-conferring mutations and novel variations; however, the dependence on growing samples in culture, and the associated delays in achieving results, represents a significant limitation. As an alternative, targeted sequencing strategies can be directly performed on clinical samples at high throughput. This study proposes a targeted sequencing assay to rapidly detect drug-resistant strains of M. tuberculosis using the Nanopore MinION sequencing platform. We designed a single-tube assay that targets nine genes associated with drug resistance to seven drugs and two phylogenetic-determining regions to determine strain lineage and tested it in nine clinical isolates and six sputa. The study's main aim is to calibrate MinNION variant calling to detect drug-resistance-associated mutations with different frequencies to match the accuracy of Illumina (the current gold-standard sequencing technology) from both culture and sputum samples. After calibrating Nanopore MinION variant calling, we demonstrated 100% agreement between Illumina WGS and our MinION set up to detect known drug resistance and phylogenetic variants in our dataset. Importantly, other variants in the amplicons are also detected, decreasing the recall. We identify minority variants and insertions/deletions as crucial bioinformatics challenges to fully reproduce Illumina WGS results.

Genomic analyses of Mycobacterium tuberculosis from human lung resections reveal a high frequency of polyclonal infections.

Polyclonal infections occur when at least two unrelated strains of the same pathogen are detected in an individual. This has been linked to worse clinical outcomes in tuberculosis, as undetected strains with different antibiotic resistance profiles can lead to treatment failure. Here, we examine the amount of polyclonal infections in sputum and surgical resections from patients with tuberculosis in the country of Georgia. For this purpose, we sequence and analyse the genomes of Mycobacterium tuberculosis isolated from the samples, acquired through an observational clinical study (NCT02715271). Access to the lung enhanced the detection of multiple strains (40% of surgery cases) as opposed to just using a sputum sample (0-5% in the general population). We show that polyclonal infections often involve genetically distant strains and can be associated with reversion of the patient's drug susceptibility profile over time. In addition, we find different patterns of genetic diversity within lesions and across patients, including mutational signatures known to be associated with oxidative damage; this suggests that reactive oxygen species may be acting as a selective pressure in the granuloma environment. Our results support the idea that the magnitude of polyclonal infections in high-burden tuberculosis settings is underestimated when only testing sputum samples.

Evolutionary and Phenotypic Characterization of Two Spike Mutations in European Lineage 20E of SARS-CoV-2.

We have detected two mutations in the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at amino acid positions 1163 and 1167 that appeared independently in multiple transmission clusters and different genetic backgrounds. Furthermore, both mutations appeared together in a cluster of 1,627 sequences belonging to clade 20E. This cluster is characterized by 12 additional single nucleotide polymorphisms but no deletions. The available structural information on the S protein in the pre- and postfusion conformations predicts that both mutations confer rigidity, which could potentially decrease viral fitness. Accordingly, we observed reduced infectivity of this spike genotype relative to the ancestral 20E sequence in vitro, and the levels of viral RNA in nasopharyngeal swabs were not significantly higher. Furthermore, the mutations did not impact thermal stability or antibody neutralization by sera from vaccinated individuals but moderately reduce neutralization by convalescent-phase sera from the early stages of the pandemic. Despite multiple successful appearances of the two spike mutations during the first year of SARS-CoV-2 evolution, the genotype with both mutations was displaced upon the expansion of the 20I (Alpha) variant. The midterm fate of the genotype investigated was consistent with the lack of advantage observed in the clinical and experimental data. IMPORTANCE We observed repeated, independent emergence of mutations in the SARS-CoV-2 spike involving amino acids 1163 and 1167, within the HR2 functional motif. Conclusions derived from evolutionary and genomic diversity analysis suggest that the co-occurrence of both mutations might pose an advantage for the virus and therefore a threat to effective control of the epidemic. However, biological characterization, including in vitro experiments and analysis of clinical data, indicated no clear benefit in terms of stability or infectivity. In agreement with this, continuous epidemiological surveillance conducted months after the first observations revealed that both mutations did not successfully outcompete other variants and stopped circulating 9 months after their initial detection. Additionally, we evaluated the potential of both mutations to escape neutralizing antibodies, finding that the presence of these two mutations on their own is not likely to confer antibody escape. Our results provide an example of how newly emerged spike mutations can be assessed to better understand the risk posed by new variants and indicate that some spike mutations confer no clear advantage to the virus despite independently emerging multiple times and are eventually displaced by fitter variants.

The first wave of the COVID-19 epidemic in Spain was associated with early introductions and fast spread of a dominating genetic variant.

The coronavirus disease 2019 (COVID-19) pandemic has affected the world radically since 2020. Spain was one of the European countries with the highest incidence during the first wave. As a part of a consortium to monitor and study the evolution of the epidemic, we sequenced 2,170 samples, diagnosed mostly before lockdown measures. Here, we identified at least 500 introductions from multiple international sources and documented the early rise of two dominant Spanish epidemic clades (SECs), probably amplified by superspreading events. Both SECs were related closely to the initial Asian variants of SARS-CoV-2 and spread widely across Spain. We inferred a substantial reduction in the effective reproductive number of both SECs due to public-health interventions (Re < 1), also reflected in the replacement of SECs by a new variant over the summer of 2020. In summary, we reveal a notable difference in the initial genetic makeup of SARS-CoV-2 in Spain compared with other European countries and show evidence to support the effectiveness of lockdown measures in controlling virus spread, even for the most successful genetic variants.

Whole-genome sequencing of Mycobacterium tuberculosis directly from clinical samples for high-resolution genomic epidemiology and drug resistance surveillance: an observational study.

BACKGROUND: Direct whole-genome sequencing of Mycobacterium tuberculosis from clinical specimens will be a major breakthrough in tuberculosis diagnosis and control. To date, direct whole-genome sequencing has never been used in genomic epidemiology, and its accuracy in transmission inference remains unknown. We investigated the technical challenges imposed by direct whole-genome sequencing, and used it to infer transmission clusters and predict drug resistance. METHODS: Using an optimised workflow, we did direct whole-genome sequencing for 37 clinical specimens from 23 tuberculosis patients. Nine sputum samples from nine patients who were infected with different non-tuberculous mycobacteria and culture-negative for tuberculosis were used as controls in the qPCR assays and pre-sequencing runs. Additionally, 780 clinical isolates in the region of Comunidad Valenciana (Spain) were whole-genome sequenced between Jan 1, 2014, and Dec 31, 2016. We analysed the genomic variants to build a tuberculosis transmission network for the region, including the clinical specimens, and to predict drug susceptibility profiles. FINDINGS: After sequencing 37 clinical specimens, 28 specimens (22 [85%] of 26 smear-positive and six [55%] of 11 smear-negative) met the quality criteria for downstream analysis. All 28 clinical specimens clustered with their matching culture isolates, with a median distance of 0 single nucleotide polymorphisms. Of the 28 clinical specimens, 16 (57%) were accurately assigned to ten transmission clusters in the region, and 12 (43%) were unique cases. Transmission inferences and drug-susceptibility predictions from direct whole-genome sequencing data were concordant with sequences from corresponding cultures and phenotypic drug-susceptibility testing. Complete genomic analysis, within a week of specimen receipt, cost €217 per sample (excluding personnel costs). INTERPRETATION: Direct whole-genome sequencing could be used to accurately delineate transmission clusters of tuberculosis and conduct culture-independent surveillance. Compared with conventional approaches, direct whole-genome sequencing allows researchers to do real-time genomic epidemiology and drug resistance surveillance in settings where culture and drug susceptibility testing are not available. FUNDING: European Research Council; Ministerio de Ciencia, Innovación y Universidades (Spanish Government).