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HIV prevention with pre-exposure prophylaxis (PrEP) constitutes a major pillar in fighting the ongoing epidemic. While daily oral PrEP adherence may be challenging, long-acting (LA-)PrEP in oral or implant formulations could overcome frequent dosing with convenient administration. The novel drug islatravir (ISL) may be suitable for LA-PrEP, but dose-dependent reductions in CD 4 + $$ \mathrm{CD}{4}^{+} $$ T cell and lymphocyte counts were observed at high doses. We developed a mathematical model to predict ISL pro-drug levels in plasma and active intracellular ISL-triphosphate concentrations after oral vs. subcutaneous implant dosing. Using phase II trial data, we simulated antiviral effects and estimated HIV risk reduction for multiple dosages and dosing frequencies. We then established exposure thresholds where no adverse effects on immune cells were observed. Our findings suggest that implants with 56-62 mg ISL offer effective HIV risk reduction without reducing lymphocyte counts. Oral 0.1 mg daily, 3-5 mg weekly, and 10 mg biweekly ISL provide comparable efficacy, but weekly and biweekly doses may affect lymphocyte counts, while daily dosing regimen offered no advantage over existing oral PrEP. Oral 0.5-1 mg on demand provided > 90 % $$ >90\% $$ protection, while not being suitable for post-exposure prophylaxis. These findings suggest ISL could be considered for further development as a promising and safe agent for implantable PrEP.
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BACKGROUND: Pre-exposure prophylaxis (PrEP) with oral emtricitabine/tenofovir disoproxil (FTC/TDF) proved highly efficient in preventing HIV. Since 09/2019, FTC/TDF-PrEP is covered by health insurances in Germany, if prescribed by licensed specialists. However, methods to longitudinally monitor progress in PrEP implementation in Germany are lacking. METHODS: Utilizing anonymous FTC/TDF prescription data from 2017-2021, we developed a mathematical model to disentangle HIV-treatment from PrEP prescriptions, as well as to translate PrEP prescriptions into number of PrEP users. We used the model to estimate past- and future PrEP uptake dynamics, to predict coverage of PrEP needs and to quantify the impact of COVID-19 on PrEP uptake on a national and regional level. RESULTS: We identified significant (p<0.01) decelerating effects of the first- and second COVID-19-lockdown on PrEP uptake in 04/2020 and 12/2020. We estimated 26,159 (CI: 25,751-26,571) PrEP users by 12/2021, corresponding to 33% PrEP coverage of people in need. We projected 64,794 (CI: 62,956-66,557) PrEP users by 12/2030, corresponding to 81% PrEP coverage. We identified profound regional differences, with high PrEP coverage and uptake in metropoles and low coverage in more rural regions. CONCLUSIONS: Our approach presents a comprehensive solution to monitor and forecast PrEP implementation from anonymous data and highlighted that the COVID-19 pandemic significantly decelerated PrEP uptake in Germany. Moreover, slow PrEP uptake in rural areas indicate that structural barriers in PrEP care, education or information exist that may hamper the goal of ending the AIDS epidemic by 2030.
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Fármacos Anti-HIV , COVID-19 , Infecções por HIV , Profilaxia Pré-Exposição , Humanos , Profilaxia Pré-Exposição/estatística & dados numéricos , Alemanha/epidemiologia , Infecções por HIV/prevenção & controle , Infecções por HIV/epidemiologia , COVID-19/prevenção & controle , COVID-19/epidemiologia , Fármacos Anti-HIV/uso terapêutico , Fármacos Anti-HIV/administração & dosagem , Masculino , Combinação Emtricitabina e Fumarato de Tenofovir Desoproxila/uso terapêutico , Feminino , Modelos Teóricos , AdultoRESUMO
The joint analysis of two datasets [Formula: see text] and [Formula: see text] that describe the same phenomena (e.g. the cellular state), but measure disjoint sets of variables (e.g. mRNA vs. protein levels) is currently challenging. Traditional methods typically analyze single interaction patterns such as variance or covariance. However, problem-tailored external knowledge may contain multiple different information about the interaction between the measured variables. We introduce MIASA, a holistic framework for the joint analysis of multiple different variables. It consists of assembling multiple different information such as similarity vs. association, expressed in terms of interaction-scores or distances, for subsequent clustering/classification. In addition, our framework includes a novel qualitative Euclidean embedding method (qEE-Transition) which enables using Euclidean-distance/vector-based clustering/classification methods on datasets that have a non-Euclidean-based interaction structure. As an alternative to conventional optimization-based multidimensional scaling methods which are prone to uncertainties, our qEE-Transition generates a new vector representation for each element of the dataset union [Formula: see text] in a common Euclidean space while strictly preserving the original ordering of the assembled interaction-distances. To demonstrate our work, we applied the framework to three types of simulated datasets: samples from families of distributions, samples from correlated random variables, and time-courses of statistical moments for three different types of stochastic two-gene interaction models. We then compared different clustering methods with vs. without the qEE-Transition. For all examples, we found that the qEE-Transition followed by Ward clustering had superior performance compared to non-agglomerative clustering methods but had a varied performance against ultrametric-based agglomerative methods. We also tested the qEE-Transition followed by supervised and unsupervised machine learning methods and found promising results, however, more work is needed for optimal parametrization of these methods. As a future perspective, our framework points to the importance of more developments and validation of distance-distribution models aiming to capture multiple-complex interactions between different variables.
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Algoritmos , Análise por Conglomerados , Humanos , Biologia Computacional/métodosRESUMO
BACKGROUND: Direct RNA sequencing (dRNA-seq) on the Oxford Nanopore Technologies (ONT) platforms can produce reads covering up to full-length gene transcripts, while containing decipherable information about RNA base modifications and poly-A tail lengths. Although many published studies have been expanding the potential of dRNA-seq, its sequencing accuracy and error patterns remain understudied. RESULTS: We present the first comprehensive evaluation of sequencing accuracy and characterisation of systematic errors in dRNA-seq data from diverse organisms and synthetic in vitro transcribed RNAs. We found that for sequencing kits SQK-RNA001 and SQK-RNA002, the median read accuracy ranged from 87% to 92% across species, and deletions significantly outnumbered mismatches and insertions. Due to their high abundance in the transcriptome, heteropolymers and short homopolymers were the major contributors to the overall sequencing errors. We also observed systematic biases across all species at the levels of single nucleotides and motifs. In general, cytosine/uracil-rich regions were more likely to be erroneous than guanines and adenines. By examining raw signal data, we identified the underlying signal-level features potentially associated with the error patterns and their dependency on sequence contexts. While read quality scores can be used to approximate error rates at base and read levels, failure to detect DNA adapters may be a source of errors and data loss. By comparing distinct basecallers, we reason that some sequencing errors are attributable to signal insufficiency rather than algorithmic (basecalling) artefacts. Lastly, we generated dRNA-seq data using the latest SQK-RNA004 sequencing kit released at the end of 2023 and found that although the overall read accuracy increased, the systematic errors remain largely identical compared to the previous kits. CONCLUSIONS: As the first systematic investigation of dRNA-seq errors, this study offers a comprehensive overview of reproducible error patterns across diverse datasets, identifies potential signal-level insufficiency, and lays the foundation for error correction methods.
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Sequenciamento por Nanoporos , Análise de Sequência de RNA , Análise de Sequência de RNA/métodos , Sequenciamento por Nanoporos/métodos , Nanoporos , Humanos , Animais , RNA/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodosRESUMO
The idea of guidance toward a target is central to axon pathfinding and brain wiring in general. In this work, we show how several thousand axonal growth cones self-pattern without target-dependent guidance during neural superposition wiring in Drosophila. Ablation of all target lamina neurons or loss of target adhesion prevents the stabilization but not the development of the pattern. Intravital imaging at the spatiotemporal resolution of growth cone dynamics in intact pupae and data-driven dynamics simulations reveal a mechanism by which >30,000 filopodia do not explore potential targets, but instead simultaneously generate and navigate a dynamic filopodial meshwork that steers growth directions. Hence, a guidance mechanism can emerge from the interactions of the axons being guided, suggesting self-organization as a more general feature of brain wiring.
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Orientação de Axônios , Drosophila melanogaster , Cones de Crescimento , Animais , Drosophila melanogaster/crescimento & desenvolvimento , Cones de Crescimento/fisiologia , Neurônios/fisiologia , Pseudópodes/fisiologiaRESUMO
The SARS-CoV-2 pandemic has highlighted the need to better define in-hospital transmissions, a need that extends to all other common infectious diseases encountered in clinical settings. To evaluate how whole viral genome sequencing can contribute to deciphering nosocomial SARS-CoV-2 transmission 926 SARS-CoV-2 viral genomes from 622 staff members and patients were collected between February 2020 and January 2021 at a university hospital in Munich, Germany, and analysed along with the place of work, duration of hospital stay, and ward transfers. Bioinformatically defined transmission clusters inferred from viral genome sequencing were compared to those inferred from interview-based contact tracing. An additional dataset collected at the same time at another university hospital in the same city was used to account for multiple independent introductions. Clustering analysis of 619 viral genomes generated 19 clusters ranging from 3 to 31 individuals. Sequencing-based transmission clusters showed little overlap with those based on contact tracing data. The viral genomes were significantly more closely related to each other than comparable genomes collected simultaneously at other hospitals in the same city (n = 829), suggesting nosocomial transmission. Longitudinal sampling from individual patients suggested possible cross-infection events during the hospital stay in 19.2% of individuals (14 of 73 individuals). Clustering analysis of SARS-CoV-2 whole genome sequences can reveal cryptic transmission events missed by classical, interview-based contact tracing, helping to decipher in-hospital transmissions. These results, in line with other studies, advocate for viral genome sequencing as a pathogen transmission surveillance tool in hospitals.
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COVID-19 , Infecção Hospitalar , Humanos , SARS-CoV-2/genética , COVID-19/epidemiologia , COVID-19/genética , Genoma Viral/genética , Infecção Hospitalar/epidemiologia , Infecção Hospitalar/genética , Hospitais UniversitáriosRESUMO
Most human immunodeficiency virus (HIV) infections occur in cisgender women in resource-limited settings. In women, self-protection with emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) constitutes a major pillar of HIV prevention. However, clinical trials in women had inconsistent outcomes, sparking uncertainty about adherence requirements and reluctance in evaluating on-demand regimens. We analyzed data from published FTC/TDF-PrEP trials to establish efficacy ranges in cisgender women. In a 'bottom-up' approach, we modeled hypotheses in the context of risk-group-specific, adherence-efficacy profiles and challenged those hypotheses with clinical data. We found that different clinical outcomes were related to the proportion of women taking the product, allowing coherent interpretation of the data. Our analysis showed that 90% protection was achieved when women took some product. We found that hypotheses of putative male/female differences were either not impactful or statistically inconsistent with clinical data. We propose that differing clinical outcomes could arise from pill-taking behavior rather than biological factors driving specific adherence requirements in cisgender women.
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Fármacos Anti-HIV , Infecções por HIV , Profilaxia Pré-Exposição , Humanos , Feminino , Masculino , Tenofovir/uso terapêutico , Emtricitabina/uso terapêutico , Fármacos Anti-HIV/uso terapêutico , Infecções por HIV/tratamento farmacológico , Infecções por HIV/prevenção & controle , Adesão à MedicaçãoRESUMO
Immunocompromised individuals are at higher risk of developing protracted and severe COVID-19, and understanding individual disease courses and SARS-CoV-2 immune responses in these individuals is of the utmost importance. For more than two years, we followed an immunocompromised individual with a protracted SARS-CoV-2 infection that was eventually cleared in the absence of a humoral neutralizing SARS-CoV-2 antibody response. By conducting an in-depth examination of this individual's immune response and comparing it to a large cohort of convalescents who spontaneously cleared a SARS-CoV-2 infection, we shed light on the interplay between B- and T-cell immunity and how they interact in clearing SARS-CoV-2 infection.
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Globally, most HIV infections occur in heterosexual women in resource-limited settings. In these settings, female self-protection with generic emtricitabine/tenofovir disoproxil fumarate pre-exposure prophylaxis (FTC/TDF-PrEP) may constitute a major pillar of the HIV prevention portfolio. However, clinical trials in women had inconsistent outcomes, sparking uncertainty regarding risk-group specific adherence requirements and causing reluctance in testing and recommending on-demand regimen in women. We analyzed all FTC/TDF-PrEP trials to establish PrEP efficacy ranges in women. In a 'bottom-up' approach, we modeled hypotheses corroborating risk-group specific adherence-efficacy profiles. Finally, we used the clinical efficacy ranges to (in-)validate hypotheses. We found that different clinical outcomes could solely be explained by the proportion of enrolled participants not taking the product, allowing, for the first time, to unify clinical observations. This analysis showed that 90% protection was achieved, when women took some of the product. Using 'bottom-up' modelling, we found that hypotheses of putative male/female differences were either irrelevant, or statistically inconsistent with clinical data. Furthermore, our multiscale modelling indicated that 90% protection was achieved if oral FTC/TDF was taken at least twice weekly.
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Substantial opportunities for global health intelligence and research arise from the combined and optimised use of secondary data within data ecosystems. Secondary data are information being used for purposes other than those intended when they were collected. These data can be gathered from sources on the verge of widespread use such as the internet, wearables, mobile phone apps, electronic health records, or genome sequencing. To utilise their full potential, we offer guidance by outlining available sources and approaches for the processing of secondary data. Furthermore, in addition to indicators for the regulatory and ethical evaluation of strategies for the best use of secondary data, we also propose criteria for assessing reusability. This overview supports more precise and effective policy decision making leading to earlier detection and better prevention of emerging health threats than is currently the case.
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Telefone Celular , Aplicativos Móveis , Ecossistema , Saúde Global , InternetRESUMO
BACKGROUND: Comprehensive pathogen genomic surveillance represents a powerful tool to complement and advance precision vaccinology. The emergence of the Alpha variant in December 2020 and the resulting efforts to track the spread of this and other severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern led to an expansion of genomic sequencing activities in Germany. METHODS: At Robert Koch Institute (RKI), the German National Institute of Public Health, we established the Integrated Molecular Surveillance for SARS-CoV-2 (IMS-SC2) network to perform SARS-CoV-2 genomic surveillance at the national scale, SARS-CoV-2-positive samples from laboratories distributed across Germany regularly undergo whole-genome sequencing at RKI. RESULTS: We report analyses of 3623 SARS-CoV-2 genomes collected between December 2020 and December 2021, of which 3282 were randomly sampled. All variants of concern were identified in the sequenced sample set, at ratios equivalent to those in the 100-fold larger German GISAID sequence dataset from the same time period. Phylogenetic analysis confirmed variant assignments. Multiple mutations of concern emerged during the observation period. To model vaccine effectiveness in vitro, we employed authentic-virus neutralization assays, confirming that both the Beta and Zeta variants are capable of immune evasion. The IMS-SC2 sequence dataset facilitated an estimate of the SARS-CoV-2 incidence based on genetic evolution rates. Together with modeled vaccine efficacies, Delta-specific incidence estimation indicated that the German vaccination campaign contributed substantially to a deceleration of the nascent German Delta wave. CONCLUSIONS: SARS-CoV-2 molecular and genomic surveillance may inform public health policies including vaccination strategies and enable a proactive approach to controlling coronavirus disease 2019 spread as the virus evolves.
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COVID-19 , SARS-CoV-2 , COVID-19/epidemiologia , COVID-19/prevenção & controle , Genoma Viral , Genômica , Humanos , Filogenia , SARS-CoV-2/genética , VacinologiaRESUMO
RNA dimerization is the noncovalent association of two human immunodeficiency virus-1 (HIV-1) genomes. It is a conserved step in the HIV-1 life cycle and assumed to be a prerequisite for binding to the viral structural protein Pr55Gag during genome packaging. Here, we developed functional analysis of RNA structure-sequencing (FARS-seq) to comprehensively identify sequences and structures within the HIV-1 5' untranslated region (UTR) that regulate this critical step. Using FARS-seq, we found nucleotides important for dimerization throughout the HIV-1 5' UTR and identified distinct structural conformations in monomeric and dimeric RNA. In the dimeric RNA, key functional domains, such as stem-loop 1 (SL1), polyadenylation signal (polyA) and primer binding site (PBS), folded into independent structural motifs. In the monomeric RNA, SL1 was reconfigured into long- and short-range base pairings with polyA and PBS, respectively. We show that these interactions disrupt genome packaging, and additionally show that the PBS-SL1 interaction unexpectedly couples the PBS with dimerization and Pr55Gag binding. Altogether, our data provide insights into late stages of HIV-1 life cycle and a mechanistic explanation for the link between RNA dimerization and packaging.
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HIV-1 , Regiões 5' não Traduzidas/genética , Dimerização , HIV-1/fisiologia , Humanos , Conformação de Ácido Nucleico , RNA Viral/química , Proteínas Virais/metabolismoRESUMO
The role of schools as a source of infection and driver in the coronavirus-pandemic has been controversial and is still not completely clarified. To prevent harm and disadvantages for children and adolescents, but also adults, detailed data on school outbreaks is needed, especially when talking about open schools employing evidence-based safety concepts. Here, we investigated the first significant COVID-19 school outbreak in Hamburg, Germany, after the re-opening of schools in 2020. Using clinical, laboratory, and contact data and spatial measures for epidemiological and environmental studies combined with whole-genome sequencing (WGS) analysis, we examined the causes and the course of the secondary school outbreak. The potential index case was identified by epidemiological tracking and the lessons in classrooms with presumably high virus spreading rates and further infection chains in the setting. Sequence analysis of samples detected one sample of a different virus lineage and 25 virus genomes with almost identical sequences, of which 21 showed 100% similarity. Most infections occurred in connection with two lesson units of the primary case. Likely, 31 students (12-14 years old), two staff members, and three family members were infected in the school or the typical household. Sequence analysis revealed an outbreak cluster with a single source that was epidemiologically identified as a member of the educational staff. In lesson units, two superspreading events of varying degrees with airborne transmission took place. These were influenced by several parameters including the exposure times, the use of respiratory masks while speaking and spatial or structural conditions at that time.
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COVID-19/epidemiologia , Surtos de Doenças , Instituições Acadêmicas , COVID-19/diagnóstico , COVID-19/prevenção & controle , COVID-19/transmissão , Busca de Comunicante , Surtos de Doenças/prevenção & controle , Pessoal de Educação , Família , Feminino , Genoma Viral/genética , Alemanha/epidemiologia , Humanos , Masculino , Filogenia , Quarentena , Fatores de Risco , SARS-CoV-2/classificação , SARS-CoV-2/genética , SARS-CoV-2/isolamento & purificação , EstudantesRESUMO
Deep convolutional neural networks (DCNNs) are routinely used for image segmentation of biomedical data sets to obtain quantitative measurements of cellular structures like tissues. These cellular structures often contain gaps in their boundaries, leading to poor segmentation performance when using DCNNs like the U-Net. The gaps can usually be corrected by post-hoc computer vision (CV) steps, which are specific to the data set and require a disproportionate amount of work. As DCNNs are Universal Function Approximators, it is conceivable that the corrections should be obsolete by selecting the appropriate architecture for the DCNN. In this article, we present a novel theoretical framework for the gap-filling problem in DCNNs that allows the selection of architecture to circumvent the CV steps. Combining information-theoretic measures of the data set with a fundamental property of DCNNs, the size of their receptive field, allows us to formulate statements about the solvability of the gap-filling problem independent of the specifics of model training. In particular, we obtain mathematical proof showing that the maximum proficiency of filling a gap by a DCNN is achieved if its receptive field is larger than the gap length. We then demonstrate the consequence of this result using numerical experiments on a synthetic and real data set and compare the gap-filling ability of the ubiquitous U-Net architecture with variable depths. Our code is available at https://github.com/ai-biology/dcnn-gap-filling.
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Redes Neurais de Computação , Visão OcularRESUMO
Pre-exposure prophylaxis (PrEP) is an important pillar to prevent HIV transmission. Because of experimental and clinical shortcomings, mathematical models that integrate pharmacological, viral- and host factors are frequently used to quantify clinical efficacy of PrEP. Stochastic simulations of these models provides sample statistics from which the clinical efficacy is approximated. However, many stochastic simulations are needed to reduce the associated sampling error. To remedy the shortcomings of stochastic simulation, we developed a numerical method that allows predicting the efficacy of arbitrary prophylactic regimen directly from a viral dynamics model, without sampling. We apply the method to various hypothetical dolutegravir (DTG) prophylaxis scenarios. The approach is verified against state-of-the-art stochastic simulation. While the method is more accurate than stochastic simulation, it is superior in terms of computational performance. For example, a continuous 6-month prophylactic profile is computed within a few seconds on a laptop computer. The method's computational performance, therefore, substantially expands the horizon of feasible analysis in the context of PrEP, and possibly other applications.
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Fármacos Anti-HIV/uso terapêutico , Biologia Computacional/métodos , Simulação por Computador , Infecções por HIV/tratamento farmacológico , Profilaxia Pré-Exposição/estatística & dados numéricos , Monitoramento de Medicamentos , HIV-1 , Humanos , Processos Estocásticos , Resultado do TratamentoRESUMO
Variability of synapse numbers and partners despite identical genes reveals the limits of genetic determinism. Here, we use developmental temperature as a non-genetic perturbation to study variability of brain wiring and behavior in Drosophila. Unexpectedly, slower development at lower temperatures increases axo-dendritic branching, synapse numbers, and non-canonical synaptic partnerships of various neurons, while maintaining robust ratios of canonical synapses. Using R7 photoreceptors as a model, we show that changing the relative availability of synaptic partners using a DIPγ mutant that ablates R7's preferred partner leads to temperature-dependent recruitment of non-canonical partners to reach normal synapse numbers. Hence, R7 synaptic specificity is not absolute but based on the relative availability of postsynaptic partners and presynaptic control of synapse numbers. Behaviorally, movement precision is temperature robust, while movement activity is optimized for the developmentally encountered temperature. These findings suggest genetically encoded relative and scalable synapse formation to develop functional, but not identical, brains and behaviors.
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Encéfalo/crescimento & desenvolvimento , Encéfalo/metabolismo , Drosophila/crescimento & desenvolvimento , Drosophila/metabolismo , Neurônios/metabolismo , Sinapses/metabolismo , Temperatura , Adaptação Fisiológica , Animais , Axônios/metabolismo , Proteínas de Drosophila/metabolismo , Neurogênese , Células Fotorreceptoras de Invertebrados/metabolismoRESUMO
By October 2021, 230 million SARS-CoV-2 diagnoses have been reported. Yet, a considerable proportion of cases remains undetected. Here, we propose GInPipe, a method that rapidly reconstructs SARS-CoV-2 incidence profiles solely from publicly available, time-stamped viral genomes. We validate GInPipe against simulated outbreaks and elaborate phylodynamic analyses. Using available sequence data, we reconstruct incidence histories for Denmark, Scotland, Switzerland, and Victoria (Australia) and demonstrate, how to use the method to investigate the effects of changing testing policies on case ascertainment. Specifically, we find that under-reporting was highest during summer 2020 in Europe, coinciding with more liberal testing policies at times of low testing capacities. Due to the increased use of real-time sequencing, it is envisaged that GInPipe can complement established surveillance tools to monitor the SARS-CoV-2 pandemic. In post-pandemic times, when diagnostic efforts are decreasing, GInPipe may facilitate the detection of hidden infection dynamics.
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COVID-19/diagnóstico , COVID-19/epidemiologia , Genoma Viral , SARS-CoV-2/genética , COVID-19/história , Europa (Continente)/epidemiologia , História do Século XXI , Humanos , Incidência , Pandemias , Filogenia , SARS-CoV-2/classificação , SARS-CoV-2/isolamento & purificação , Escócia , Suíça , VitóriaRESUMO
Single-cell RNA sequencing (scRNA-seq) has become ubiquitous in biology. Recently, there has been a push for using scRNA-seq snapshot data to infer the underlying gene regulatory networks (GRNs) steering cellular function. To date, this aspiration remains unrealized due to technical and computational challenges. In this work we focus on the latter, which is under-represented in the literature. We took a systemic approach by subdividing the GRN inference into three fundamental components: data pre-processing, feature extraction, and inference. We observed that the regulatory signature is captured in the statistical moments of scRNA-seq data and requires computationally intensive minimization solvers to extract it. Furthermore, current data pre-processing might not conserve these statistical moments. Although our moment-based approach is a didactic tool for understanding the different compartments of GRN inference, this line of thinking-finding computationally feasible multi-dimensional statistics of data-is imperative for designing GRN inference methods.
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Here, we report on the increasing frequency of the SARS-CoV-2 lineage A.27 in Germany during the first months of 2021. Genomic surveillance identified 710 A.27 genomes in Germany as of 2 May 2021, with a vast majority identified in laboratories from a single German state (Baden-Wuerttemberg, n = 572; 80.5%). Baden-Wuerttemberg is located near the border with France, from where most A.27 sequences were entered into public databases until May 2021. The first appearance of this lineage based on sequencing in a laboratory in Baden-Wuerttemberg can be dated to early January '21. From then on, the relative abundance of A.27 increased until the end of February but has since declined-meanwhile, the abundance of B.1.1.7 increased in the region. The A.27 lineage shows a mutational pattern typical of VOIs/VOCs, including an accumulation of amino acid substitutions in the Spike glycoprotein. Among those, L18F, L452R and N501Y are located in the epitope regions of the N-terminal- (NTD) or receptor binding domain (RBD) and have been suggested to result in immune escape and higher transmissibility. In addition, A.27 does not show the D614G mutation typical for all VOIs/VOCs from the B lineage. Overall, A.27 should continue to be monitored nationally and internationally, even though the observed trend in Germany was initially displaced by B.1.1.7 (Alpha), while now B.1.617.2 (Delta) is on the rise.