Mycobacterium abscessus is an emerging opportunistic pathogen affecting patients with chronic lung diseases, primarily cystic fibrosis (CF), or those under immunosuppression. Hence, investigations into the epidemiology and transmission of M. abscessus and accurate antibiotic susceptibility data are essential for the effective treatment of infections caused by this pathogen. This retrospective nationwide study included all clinical M. abscessus isolates (n = 59) from 29 patients diagnosed in the Czech Republic and Slovakia between 2018 and 2023. Whole genome sequencing (WGS) was performed to identify clusters and classify isolates into predominant circulating clones (DCC). Subspecies identification of unique isolates showed subspecies abscessus as the most prevalent (69.0%). The results of drug-susceptibility testing showed that 65.5% of all isolates were resistant to at least three antibiotics tested. CF patients under 24 years of age were the most at-risk group for M. abscessus infection. WGS identified seven clusters (including two cross-border) comprising CF and non-CF patients with a total clustering rate of 48.3%. One cluster involved patients infected with subspecies massiliense strains differing by 0 single nucleotide polymorphisms hospitalized in the same center. Furthermore, we identified representatives of all major DCCs. This study revealed predominant Mycobacterium abscessus complex clones circulating in the Czech Republic and Slovakia. The results show the high discriminatory power of WGS in the molecular epidemiology of M. abscessus and provide supporting evidence of direct or indirect cross-transmission of subspecies massiliense among both CF and non-CF patients. IMPORTANCEThis study highlights the importance of understanding Mycobacterium abscessus transmission because it poses a growing threat to vulnerable populations, especially young cystic fibrosis patients. Investigating how it spreads and which antibiotics work best is crucial for effective treatment. This research used whole genome sequencing to track M. abscessus and found evidence of potential transmission between patients, including across borders. The findings suggest that dominant strains are circulating and some patients may be infected through direct or indirect contact. This knowledge can inform infection control and treatment strategies.

Nontuberculous mycobacteria (NTM) are emerging as notable causative agents of opportunistic infections. To examine clinical significance, species distribution, and temporal trends of NTM in Denmark, we performed a nationwide register-based study of all unique persons with NTM isolated in the country during 1991-2022. We categorized patients as having definite disease, possible disease, or isolation by using a previously validated method. The incidence of pulmonary NTM increased throughout the study period, in contrast to earlier findings. Mycobacterium malmoense, M. kansasii, M. szulgai, and M. avium complex were the most clinically significant species based on microbiologic findings; M. avium dominated in incidence. This study shows the need for surveillance for an emerging infection that is not notifiable in most countries, provides evidence to support clinical decision-making, and highlights the importance of not considering NTM as a single entity.

Accurate rainfall estimates with high spatiotemporal resolution are vital for urban drainage applications, and if adjusted to ground observations, weather radar data has potential for these applications. The density of meteorological rain gauges for adjustment is, however, often sparse and non-uniformly distributed in space. Opportunistic rainfall sensors provide an increased density of ground observations but often with reduced or unknown accuracy for each individual station. This paper demonstrates the merging of data from weather radar, personal weather stations, and commercial microwave links into an integrated rainfall product. Merging opportunistic rainfall estimates is shown to improve the accuracy of the opportunistic rainfall observations through a quality control algorithm. In this study, we show that the accuracy of rainfall estimates is significantly improved by merging opportunistic rainfall data and weather radar data when compared to the accuracy of each rainfall product without merging. Nash-Sutcliffe efficiency (NSE) values up to 0.88 are obtained for daily accumulated merged rainfall products, while the NSE-values of the individual rainfall products range from −7.44 to 0.65, and similar tendencies are observed for root mean squared error (RMSE) values. For merging weather radar and opportunistic rainfall data, a novel approach, i.e., “moving median bias adjustment” is presented. Applying this approach, a high-performing rainfall product is derived independently from conventional high-quality rain gauges, which in this study are only used for independent validation. In addition, it is demonstrated that accurate rainfall estimates can be obtained by sub-daily merging, underscoring the importance of merging in nowcasting and near real-time applications.

Despite the fact that the majority of people in tuberculosis (TB)-endemic areas are vaccinated with the Bacillus Calmette-Guerin (BCG) vaccine, TB remains the leading infectious cause of death. Data from both animal models and humans show that BCG and subunit vaccines induce T cells of different phenotypes, and little is known about how BCG priming influences subsequent booster vaccines. To test this, we designed a novel Mycobacterium tuberculosis-specific (or "non-BCG") subunit vaccine with protective efficacy in both mice and guinea pigs and compared it to a known BCG boosting vaccine. In naive mice, this M. tuberculosis-specific vaccine induced similar protection compared with the BCG boosting vaccine. However, in BCG-primed animals, only the M. tuberculosis-specific vaccine added significantly to the BCG-induced protection. This correlated with the priming of T cells with a lower degree of differentiation and improved lung-homing capacity. These results have implications for TB vaccine design.

Examining CD8+ and CD4+ T cell responses after primary Yellow Fever vaccination in a cohort of 210 volunteers, we have identified and tetramer-validated 92 CD8+ and 50 CD4+ T cell epitopes, many inducing strong and prevalent (i.e. immunodominant) T cell responses. Restricted by 40 and 14 HLA-class I and II allotypes, respectively, these responses have wide population coverage and might be of considerable academic, diagnostic and therapeutic interest. The broad coverage of epitopes and HLA overcame the otherwise confounding effects of HLA diversity and non-HLA background providing the first evidence of T cell immunodomination in humans. Also, double-staining of CD4+ T cells with tetramers representing the same HLA-binding core, albeit with different flanking regions, demonstrated an extensive diversification of the specificities of many CD4+ T cell responses. We suggest that this could reduce the risk of pathogen escape, and that multi-tetramer staining is required to reveal the true magnitude and diversity of CD4+ T cell responses. Our T cell epitope discovery approach uses a combination of 1) overlapping peptides representing the entire Yellow Fever virus proteome to search for peptides containing CD4+ and/or CD8+ T cell epitopes, 2) predictors of peptide-HLA binding to suggest epitopes and their restricting HLA allotypes, 3) generation of peptide-HLA tetramers to identify T cell epitopes, and 4) analysis of ex vivo T cell responses to validate the same. This approach is systematic, exhaustive, and can be done in any individual of any HLA haplotype. It is all-inclusive in the sense that it includes all protein antigens and peptide epitopes, and encompasses both CD4+ and CD8+ T cell epitopes. It is efficient and, importantly, reduces the false discovery rate. The unbiased nature of the T cell epitope discovery approach presented here should support the refinement of future peptide-HLA class I and II predictors and tetramer technologies, which eventually should cover all HLA class I and II isotypes. We believe that future investigations of emerging pathogens (e.g. SARS-CoV-2) should include population-wide T cell epitope discovery using blood samples from patients, convalescents and/or long-term survivors, who might all hold important information on T cell epitopes and responses.

I kontrast til Einstein og i forlængelse af nogle temaer i fænomenologi og ma­tematik opridser denne artikel nogle punkter i Niels Bohrs videnskabsfilosofi. Den filosofiske interesse heraf ligger i at tage komplementariteten for den "hårde" ting, som Bohr omtalte, og som filosofferne - som han generelt havde det dårligt med - efter hans mening ikke fattede meget af ( de forstod ikke, at der virkelig var noget, der skulle læres, og at de måtte ofre deres fordomme, cf. Favrholdt 1992: 34, 39, 118􀀑 Blædel 1985: 232􀀒 Rozental 1985: 80-82).

The observation, by Alter et al., of the enrichment of NK cell "escape" variants in individuals carrying certain Killer-cell Immunoglobulin-like Receptor (KIR) genes is compelling evidence that natural killer (NK) cells exert selection pressure on HIV-1. Alter et al hypothesise that variant peptide, in complex with HLA class I molecules binds KIR receptors and either increases NK cell inhibition or decreases NK cell activation compared to wild type peptide thus leading to virus escape from the NK cell response. According to this hypothesis, in order for NK cells to select for an escape variant, an individual must carry both the KIR and an HLA ligand that binds the variant peptide. In this study we estimate the proportion of the population that is capable of selecting for escape variants and use both epidemiological modelling and a model-free approach to investigate whether this proportion explains the observed variant enrichment. We found that the fraction of individuals within whom the variant would have a selective advantage was low and was unable to explain the high degree of enrichment observed. We conclude that whilst Alter et al's data is consistent with selection pressure, the mechanism that they postulate is unlikely. The importance of this work is twofold. Firstly, it forces a re-evaluation of some of the clearest evidence that NK cells exert a protective effect in HIV-1 infection. Secondly, it implies that there is a significant aspect of immunology that is not understood: it is possible that KIRs bind much more widely than was previously appreciated; that a gene in linkage with the KIR genes is responsible for considerable peptide-dependent selection or that variant peptides are indirectly impacting KIR ligation.

Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is the causative agent of one of the most important porcine diseases with a high impact on animal health, welfare, and production economy. PRRSV exhibits a multitude of immunoevasive strategies that, in combination with a very high mutation rate, has hampered the development of safe and broadly protective vaccines. Aiming at a vaccine inducing an effective cytotoxic T cell response, a bioinformatics approach was taken to identify conserved PRRSV-derived peptides predicted to react broadly with common swine leukocyte antigen (SLA) class I alleles. Briefly, all possible 9- and 10-mer peptides were generated from 104 complete PRRSV type 2 genomes of confirmed high quality, and peptides with high binding affinity to five common SLAs were identified combining the NetMHCpan and positional scanning combinatorial peptide libraries binding predictions. Predicted binders were prioritized according to genomic conservation and SLA coverage using the PopCover algorithm. From this, 53 peptides were acquired for further analysis. Binding affinity and stability of a subset of 101 peptide-SLA combinations were validated in vitro for 4 of the 5 SLAs. Eventually, 23% of the predicted peptide-SLA combinations showed to form complexes with a dissociation half-life ≥30 min. Additionally, combining the two prediction methods proved to be more robust across alleles than either method used alone in terms of predicted-to-observed correlations. In summary, our approach represents a finely tuned epitope prediction pipeline providing a rationally selected ensemble of peptides for future in vivo experiments with pigs expressing the included SLAs.

Outbreaks of Yellow Fever occur regularly in endemic areas of Africa and South America frequently leading to mass vaccination campaigns straining the availability of the attenuated Yellow Fever vaccine, YF-17D. The WHO has recently decided to discontinue regular booster-vaccinations since a single vaccination is deemed to confer life-long immune protection. Here, we have examined humoral (neutralizing antibody) and cellular (CD8 and CD4 T cell) immune responses in primary and booster vaccinees (the latter spanning 8 to 36 years after primary vaccination). After primary vaccination, we observed strong cellular immune responses with T cell activation peaking ≈2 weeks and subsiding to background levels ≈ 4 weeks post-vaccination. The number of antigen-specific CD8+ T cells declined over the following years. In >90% of vaccinees, in vitro expandable T cells could still be detected >10 years post-vaccination. Although most vaccinees responded to a booster vaccination, both the humoral and cellular immune responses observed following booster vaccination were strikingly reduced compared to primary responses. This suggests that pre-existing immunity efficiently controls booster inoculums of YF-17D. In a situation with epidemic outbreaks, one could argue that a more efficient use of a limited supply of the vaccine would be to focus on primary vaccinations.

The aim of the present study was to identify influenza A-derived peptides which bind to both HLA class I and -II molecules and by immunization lead to both HLA class I and class II restricted immune responses. Eight influenza A-derived 9-11 mer peptides with simultaneous binding to both HLA-A*02:01 and HLA-DRB1*01:01 molecules were identified by bioinformatics and biochemical technology. Immunization of transgenic HLA-A*02:01/HLA-DRB1* 01: 01 mice with four of these double binding peptides gave rise to both HLA class I and class II restricted responses by CD8 and CD4 T cells, respectively, whereas four of the double binding peptides did result in HLA-A*02:01 restricted responses only. According to their cytokine profile, the CD4 T cell responses were of the Th2 type. In influenza infected mice, we were unable to detect natural processing in vivo of the double restricted peptides and in line with this, peptide vaccination did not decrease virus titres in the lungs of intranasally influenza challenged mice. Our data show that HLA class I and class II double binding peptides can be identified by bioinformatics and biochemical technology. By immunization, double binding peptides can give rise to both HLA class I and class I restricted responses, a quality which might be of potential interest for peptide-based vaccine development.

Binding of peptides to MHC class I (MHC-I) molecules is the most selective event in the processing and presentation of Ags to CTL, and insights into the mechanisms that govern peptide-MHC-I binding should facilitate our understanding of CTL biology. Peptide-MHC-I interactions have traditionally been quantified by the strength of the interaction, that is, the binding affinity, yet it has been shown that the stability of the peptide-MHC-I complex is a better correlate of immunogenicity compared with binding affinity. In this study, we have experimentally analyzed peptide-MHC-I complex stability of a large panel of human MHC-I allotypes and generated a body of data sufficient to develop a neural network-based pan-specific predictor of peptide-MHC-I complex stability. Integrating the neural network predictors of peptide-MHC-I complex stability with state-of-the-art predictors of peptide-MHC-I binding is shown to significantly improve the prediction of CTL epitopes. The method is publicly available at http://www.cbs.dtu.dk/services/NetMHCstabpan.

The live attenuated yellow fever vaccine (YF-17D) has been successfully used for more than 70 years. It is generally considered a safe vaccine, however, recent reports of serious adverse events following vaccination have raised concerns and led to suggestions that even safer YF vaccines should be developed. Replication deficient adenoviruses (Ad) have been widely evaluated as recombinant vectors, particularly in the context of prophylactic vaccination against viral infections in which induction of CD8+ T-cell mediated immunity is crucial, but potent antibody responses may also be elicited using these vectors. In this study, we present two adenobased vectors targeting non-structural and structural YF antigens and characterize their immunological properties. We report that a single immunization with an Ad-vector encoding the non-structural protein 3 from YF-17D could elicit a strong CD8+ T-cell response, which afforded a high degree of protection from subsequent intracranial challenge of vaccinated mice. However, full protection was only observed using a vector encoding the structural proteins from YF-17D. This vector elicited virus-specific CD8+ T cells as well as neutralizing antibodies, and both components were shown to be important for protection thus mimicking the situation recently uncovered in YF-17D vaccinated mice. Considering that Ad-vectors are very safe, easy to produce and highly immunogenic in humans, our data indicate that a replication deficient adenovector-based YF vaccine may represent a safe and efficient alternative to the classical live attenuated YF vaccine and should be further tested.

Background Tuberculosis (TB) control strategies are focused mainly on prevention, early diagnosis, compliance to treatment and contact tracing. The objectives of this study were to explore the frequency and risk factors of recent transmission of clinical isolates of Mycobacterium tuberculosis complex (MTBC) in Cantabria in Northern Spain from 2012 through 2013 and to analyze their clonal complexity for better understanding of the transmission dynamics in a moderate TB incidence setting. Methods DNA from 85 out of 87 isolates from bacteriologically confirmed cases of MTBC infection were extracted directly from frozen stocks and genotyped using the mycobacterial interspersed repetitive units-variable number tandem repeat (MIRU-VNTR) method. The MIRU-VNTRplus database tool was used to identify clusters and lineages and to build a neighbor joining (NJ) phylogenetic tree. In addition, data were compared to the SITVIT2 database at the Pasteur Institute of Guadeloupe. Results The rate of recent transmission was calculated to 24%. Clustering was associated with being Spanish-born. A high prevalence of isolates of the Euro-American lineage was found. In addition, MIRU-VNTR profiles of the studied isolates corresponded to previously found MIRU-VNTR types in other countries, including Spain, Belgium, Great Britain, USA, Croatia, South Africa and The Netherlands. Six of the strains analyzed represented clonal variants. Conclusion Transmission of MTBC is well controlled in Cantabria. The majority of TB patients were born in Spain. The population structure of MTBC in Cantabria has a low diversity of major clonal lineages with the Euro-American lineage predominating.

Affinity and stability of peptides bound by major histocompatibility complex (MHC) class I molecules are important factors in presentation of peptides to cytotoxic T lymphocytes (CTLs). In silico prediction methods of peptide-MHC binding followed by experimental analysis of peptide-MHC interactions constitute an attractive protocol to select target peptides from the vast pool of viral proteome peptides. We have earlier reported the peptide binding motif of the porcine MHC-I molecules SLA-1*04:01 and SLA-2*04:01, identified by an ELISA affinity-based positional scanning combinatorial peptide library (PSCPL) approach. Here, we report the peptide binding motif of SLA-3*04:01 and combine two prediction methods and analysis of both peptide binding affinity and stability of peptide-MHC complexes to improve rational peptide selection. Using a peptide prediction strategy combining PSCPL binding matrices and in silico prediction algorithms (NetMHCpan), peptide ligands from a repository of 8900 peptides were predicted for binding to SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01 and validated by affinity and stability assays. From the pool of predicted peptides for SLA-1*04:01, SLA-2*04:01, and SLA-3*04:01, a total of 71, 28, and 38% were binders with affinities below 500 nM, respectively. Comparison of peptide-SLA binding affinity and complex stability showed that peptides of high affinity generally, but not always, produce complexes of high stability. In conclusion, we demonstrate how state-of-the-art prediction and in vitro immunology tools in combination can be used for accurate selection of peptides for MHC class I binding, hence providing an expansion of the field of peptide-MHC analysis also to include pigs as a livestock experimental model.

Major histocompatibility complex (MHC) class I molecules regulate adaptive immune responses through the presentation of antigenic peptides to CD8+ T cells. Polymorphisms in the peptide binding region of class I molecules determine peptide binding affinity and stability during antigen presentation, and different antigen peptide motifs are associated with specific genetic sequences of class I molecules. Understanding bovine leukocyte antigen (BoLA), peptide-MHC class I binding specificities may facilitate development of vaccines or reagents for quantifying the adaptive immune response to intracellular pathogens, such as foot-and-mouth disease virus (FMDV). Six synthetic BoLA class I (BoLA-I) molecules were produced, and the peptide binding motif was generated for five of the six molecules using a combined approach of positional scanning combinatorial peptide libraries (PSCPLs) and neural network-based predictions (NetMHCpan). The updated NetMHCpan server was used to predict BoLA-I binding peptides within the P1 structural polyprotein sequence of FMDV (strain A24 Cruzeiro) for BoLA-1*01901, BoLA-2*00801, BoLA-2*01201, and BoLA-4*02401. Peptide binding affinity and stability were determined for these BoLA-I molecules using the luminescent oxygen channeling immunoassay (LOCI) and scintillation proximity assay (SPA). The functional diversity of known BoLA alleles was predicted using the MHCcluster tool, and functional predictions for peptide motifs were compared to observed data from this and prior studies. The results of these analyses showed that BoLA alleles cluster into three distinct groups with the potential to define "BoLA supertypes." This streamlined approach identifies potential T cell epitopes from pathogens, such as FMDV, and provides insight into T cell immunity following infection or vaccination.