Clonal hematopoiesis (CH) is associated with age and an increased risk of myeloid malignancies, cardiovascular risk, and all-cause mortality. We tested for CH in a setting where hematopoietic stem cells (HSCs) of the same individual are exposed to different degrees of proliferative stress and environments, ie, in long-term survivors of allogeneic hematopoietic stem cell transplantation (allo-HSCT) and their respective related donors (n = 42 donor-recipient pairs). With a median follow-up time since allo-HSCT of 16 years (range, 10-32 years), we found a total of 35 mutations in 23 out of 84 (27.4%) study participants. Ten out of 42 donors (23.8%) and 13 out of 42 recipients (31%) had CH. CH was associated with older donor and recipient age. We identified 5 cases of donor-engrafted CH, with 1 case progressing into myelodysplastic syndrome in both donor and recipient. Four out of 5 cases showed increased clone size in recipients compared with donors. We further characterized the hematopoietic system in individuals with CH as follows: (1) CH was consistently present in myeloid cells but varied in penetrance in B and T cells; (2) colony-forming units (CFUs) revealed clonal evolution or multiple independent clones in individuals with multiple CH mutations; and (3) telomere shortening determined in granulocytes suggested ∼20 years of added proliferative history of HSCs in recipients compared with their donors, with telomere length in CH vs non-CH CFUs showing varying patterns. This study provides insight into the long-term behavior of the same human HSCs and respective CH development under different proliferative conditions.

Genomic sequencing is essential to track the evolution and spread of SARS-CoV-2, optimize molecular tests, treatments, vaccines, and guide public health responses. To investigate the global SARS-CoV-2 genomic surveillance, we used sequences shared via GISAID to estimate the impact of sequencing intensity and turnaround times on variant detection in 189 countries. In the first two years of the pandemic, 78% of high-income countries sequenced >0.5% of their COVID-19 cases, while 42% of low- and middle-income countries reached that mark. Around 25% of the genomes from high income countries were submitted within 21 days, a pattern observed in 5% of the genomes from low- and middle-income countries. We found that sequencing around 0.5% of the cases, with a turnaround time <21 days, could provide a benchmark for SARS-CoV-2 genomic surveillance. Socioeconomic inequalities undermine the global pandemic preparedness, and efforts must be made to support low- and middle-income countries improve their local sequencing capacity.

Background In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40–80 % (Volz et al., 2021; Leung et al., 2021; Davies et al., 2021). Aim This study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland. Methods We generated whole genome sequences from 11.8 % of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant’s transmission fitness advantage on a national and a regional scale. Results We estimate B.1.1.7 had a transmission fitness advantage of 43–52 % compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07–1.41] from 01 January until 17 January 2021 and 1.18 [1.06–1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00–1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021. Conclusion The observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2–3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online.

SARS-CoV-2, the virus responsible for the current COVID-19 pandemic, is evolving into different genetic variants by accumulating mutations as it spreads globally. In addition to this diversity of consensus genomes across patients, RNA viruses can also display genetic diversity within individual hosts, and co-existing viral variants may affect disease progression and the success of medical interventions. To systematically examine the intra-patient genetic diversity of SARS-CoV-2, we processed a large cohort of 3939 publicly-available deeply sequenced genomes with specialised bioinformatics software, along with 749 recently sequenced samples from Switzerland. We found that the distribution of diversity across patients and across genomic loci is very unbalanced with a minority of hosts and positions accounting for much of the diversity. For example, the D614G variant in the Spike gene, which is present in the consensus sequences of 67.4% of patients, is also highly diverse within hosts, with 29.7% of the public cohort being affected by this coexistence and exhibiting different variants. We also investigated the impact of several technical and epidemiological parameters on genetic heterogeneity and found that age, which is known to be correlated with poor disease outcomes, is a significant predictor of viral genetic diversity.

Pathogen genomes provide insights into their evolution and epidemic spread. We sequenced 1,439 SARS-CoV-2 genomes from Switzerland, representing 3-7% of all confirmed cases per week. Using these data, we demonstrate that no one lineage became dominant, pointing against evolution towards general lower virulence. On an epidemiological level, we report no evidence of cryptic transmission before the first confirmed case. We find many early viral introductions from Germany, France, and Italy and many recent introductions from Germany and France. Over the summer, we quantify the number of non-traceable infections stemming from introductions, quantify the effective reproductive number, and estimate the degree of undersampling. Our framework can be applied to quantify evolution and epidemiology in other locations or for other pathogens based on genomic data.

In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now coined B.1.1.7. Based on the UK data and later additional data from other countries, a transmission advantage of around 40-80% was estimated for this variant. In Switzerland, since spring 2020, we perform whole genome sequencing of SARS-CoV-2 samples obtained from a large diagnostic lab (Viollier AG) on a weekly basis for genomic surveillance. The lab processes SARS-CoV-2 samples from across Switzerland. Based on a total of 7631 sequences obtained from samples collected between 14.12.2020 and 11.02.2021 at Viollier AG, we determine the relative proportion of the B.1.1.7 variant on a daily basis. In addition, we use data from a second lab (Dr Risch) screening all their samples for the B.1.1.7 variant. These two datasets represent 11.5 % of all SARS-CoV-2 confirmed cases across Switzerland during the considered time period. They allow us to quantify the transmission advantage of the B.1.1.7 variant on a national and a regional scale. Taking all our data and estimates together, we propose a transmission advantage of 49-65% of B.1.1.7 compared to the other circulating variants. Further, we estimate the effective reproductive number through time for B.1.1.7 and the other variants, again pointing to a higher transmission rate of B.1.1.7. In particular, for the time period 01.01.2021-17.01.2021, we estimate an average reproductive number for B.1.1.7 of 1.28 [1.07-1.49] while the estimate for the other variants is 0.83 [0.63-1.03], based on the total number of confirmed cases and our Viollier sequencing data. Switzerland tightened measures on 18.01.2021. A comparison of the empirically confirmed case numbers up to 20.02.2021 to a very simple model using the estimates of the reproductive number from the first half of January provides indication that the rate of spread of all variants slowed down recently. In summary, the dynamics of increase in frequency of B.1.1.7 is as expected based on the observations in the UK. Our plots are available online and constantly updated with new data to closely monitor the changes in absolute numbers.

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020 - the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland’s border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86–98% reduction in introductions during Switzerland’s strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred, using a phylodynamic model. We found that transmission slowed 35–63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.

The environments in which animals develop and evolve are profoundly shaped by bacteria, which affect animals both indirectly through their role in biogeochemical processes and directly through antagonistic or beneficial interactions. The outcomes of these activities can differ according to environmental context. In a series of laboratory experiments with diapausing eggs of the water flea Daphnia magna, we manipulated two environmental parameters, temperature and presence of bacteria, and examined their effect on development. At elevated temperatures (≥26°C), resting eggs developing without live bacteria had reduced hatching success and correspondingly higher rates of severe morphological abnormalities compared with eggs with bacteria in their environment. The beneficial effect of bacteria was strongly reduced at 20°C. Neither temperature nor the presence of bacteria affected directly developing parthenogenetic eggs. The mechanistic basis of this effect of bacteria on development is unclear, but these results highlight the complex interplay of biotic and abiotic factors influencing animal development after diapause.