The landscape of the COVID-19 pandemic in Poland emerging from epidemiological and genomic data.

The COVID-19 pandemic has profoundly affected all aspects of our lives. Through real-time monitoring and rapid vaccine implementation, we succeeded in suppressing the spread of the disease and mitigating its consequences. Finally, conclusions can be summarized and drawn. Here, we use the example of Poland, which was seriously affected by the pandemic. Compared to other countries, Poland has not achieved impressive results in either testing or vaccination, which may explain its high mortality (case fatality rate, CFR 1.94%). Through retrospective analysis of data collected by the COVID-19 Data Portal Poland, we found significant regional differences in the number of tests performed, number of cases detected, number of COVID-19-related deaths, and vaccination rates. The Masovian, Greater Poland, and Pomeranian voivodeships, the country's leaders in vaccination, reported high case numbers but low death rates. In contrast, the voivodeships in the eastern and southern parts of Poland (Subcarpathian, Podlaskie, Lublin, Opole), which documented low vaccination levels and low case numbers, had higher COVID-19-related mortality rates. The strong negative correlation between the CFR and the percentage of the population that was vaccinated in Poland supports the validity of vaccination. To gain insight into virus evolution, we sequenced more than 500 genomes and analyzed nearly 80 thousand SARS-CoV-2 genome sequences deposited in GISAID by Polish diagnostic centers. We showed that the SARS-CoV-2 variant distribution over time in Poland reflected that in Europe. Haplotype network analysis allowed us to follow the virus transmission routes and identify potential superspreaders in each pandemic wave.

The standardisation of the approach to metagenomic human gut analysis: from sample collection to microbiome profiling.

In recent years, the number of metagenomic studies increased significantly. Wide range of factors, including the tremendous community complexity and variability, is contributing to the challenge in reliable microbiome community profiling. Many approaches have been proposed to overcome these problems making hardly possible to compare results of different studies. The significant differences between procedures used in metagenomic research are reflected in a variation of the obtained results. This calls for the need for standardisation of the procedure, to reduce the confounding factors originating from DNA isolation, sequencing and bioinformatics analyses in order to ensure that the differences in microbiome composition are of a true biological origin. Although the best practices for metagenomics studies have been the topic of several publications and the main aim of the International Human Microbiome Standard (IHMS) project, standardisation of the procedure for generating and analysing metagenomic data is still far from being achieved. To highlight the difficulties in the standardisation of metagenomics methods, we thoroughly examined each step of the analysis of the human gut microbiome. We tested the DNA isolation procedure, preparation of NGS libraries for next-generation sequencing, and bioinformatics analysis, aimed at identifying microbial taxa. We showed that the homogenisation time is the leading factor impacting sample diversity, with the recommendation for a shorter homogenisation time (10 min). Ten minutes of homogenisation allows for better reflection of the bacteria gram-positive/gram-negative ratio, and the obtained results are the least heterogenous in terms of beta-diversity of samples microbial composition. Besides increasing the homogenisation time, we observed further potential impact of the library preparation kit on the gut microbiome profiling. Moreover, our analysis revealed that the choice of the library preparation kit influences the reproducibility of the results, which is an important factor that has to be taken into account in every experiment. In this study, a tagmentation-based kit allowed for obtaining the most reproducible results. We also considered the choice of the computational tool for determining the composition of intestinal microbiota, with Kraken2/Bracken pipeline outperforming MetaPhlAn2 in our in silico experiments. The design of an experiment and a detailed establishment of an experimental protocol may have a serious impact on determining the taxonomic profile of the intestinal microbiome community. Results of our experiment can be helpful for a wide range of studies that aim to better understand the role of the gut microbiome, as well as for clinical purposes.

Cancer Stem Cell-Inducing Media Activates Senescence Reprogramming in Fibroblasts.

Cellular senescence is a tumor-suppressive mechanism blocking cell proliferation in response to stress. However, recent evidence suggests that senescent tumor cells can re-enter the cell cycle to become cancer stem cells, leading to relapse after cancer chemotherapy treatment. Understanding how the senescence reprogramming process is a precursor to cancer stem cell formation is of great medical importance. To study the interplay between senescence, stemness, and cancer, we applied a stem cell medium (SCM) to human embryonic fibroblasts (MRC5 and WI-38) and cancer cell lines (A549 and 293T). MRC5 and WI-38 cells treated with SCM showed symptoms of oxidative stress and became senescent. Transcriptome analysis over a time course of SCM-induced senescence, revealed a developmental process overlapping with the upregulation of genes for growth arrest and the senescence-associated secretory phenotype (SASP). We demonstrate that histone demethylases jumonji domain-containing protein D3 (Jmjd3) and ubiquitously transcribed tetratricopeptide repeat, X chromosome (Utx), which operate by remodeling chromatin structure, are implicated in the senescence reprogramming process to block stem cell formation in fibroblasts. In contrast, A549 and 293T cells cultured in SCM were converted to cancer stem cells that displayed the phenotype of senescence uncoupled from growth arrest. The direct overexpression of DNA methyltransferases (Dnmt1 and Dnmt3A), ten-eleven translocation methylcytosine dioxygenases (Tet1 and Tet3), Jmjd3, and Utx proteins could activate senescence-associated beta-galactosidase (SA-ß-gal) activity in 293T cells, suggesting that epigenetic alteration and chromatin remodeling factors trigger the senescence response. Overall, our study suggests that chromatin machinery controlling senescence reprogramming is significant in cancer stem cell formation.