Dynamic change of the human gastrointestinal microbiome in relation to mucosal barrier effects during chemotherapy and immune ablative intervention

Numerous studies have demonstrated that the gastrointestinal tract (GIT) microbiota plays important roles for the human host. Since the GIT microbiota interfaces with the immune system and represents a first line of defense against infectious agents, interest has grown in whether the GIT microbiota may influence the outcome of different anticancer treatments. In this study, the GIT of pediatric patients with different cancer types as well as adult patients with hematologic malignancies undergoing an allogeneic hematopoietic stem cell transplantation were sampled throughout their treatment. In order to deeply profile not only the composition of the community, but also the functional capacity and expression, recently developed wet- and dry-lab methodologies for integrated multi-omic analyses were applied. The trajectories of the prokaryotic and microeukaryotic GIT communities of the patients were described in detail using 16S, 18S rRNA gene amplicon sequencing, as well as metagenomic and metatranscriptomic shotgun sequencing. Indeed, changes in the GIT microbiome in response to treatment were detected. Some changes that are generally thought to be detrimental for human health were detected during treatment, such as a decrease in alpha-diversity, a decrease in relative abundance of bacteria associated with health-promoting properties (such as Blautia spp., Roseburia spp. and Faecalibacterium spp.), as well as an increase in the relative abundance of antibiotic resistance genes. These changes were more pronounced in the adult hematology patients than in the pediatric patients, which is likely due to the more intensive treatment. Some observations need further investigation in order to explain their implication in human health. For example, in the pediatric patients, lower relative abundance of Akkermansia muciniphila was associated with mucositis and functional gene categories that are linked to bacteriophages or the bacterial defense mechanism against bacteriophages were associated with the overall status of the patient and mucositis development. Importantly, in both cohorts, high inter-individual but also high intra-individual variation in the prokaryotic communities were detected while the microeukaryotic community did not exhibit drastic changes. In conclusion, the employed integrated multi-omics analysis allowed detailed profiling of the GIT community including archaea, bacteria, eukaryotes and viruses as well as the functional potential including antibiotic resistance genes. In the future, analysis of the individual-specific processes within the GIT microbial community of patients throughout treatment might allow to adjust therapy regimens accordingly and improve the overall outcome of the therapy

WOFEX 2021 : 19th annual workshop, Ostrava, 1th September 2021 : proceedings of papers

The workshop WOFEX 2021 (PhD workshop of Faculty of Electrical Engineer-ing and Computer Science) was held on September 1st September 2021 at the VSB – Technical University of Ostrava. The workshop offers an opportunity for students to meet and share their research experiences, to discover commonalities in research and studentship, and to foster a collaborative environment for joint problem solving. PhD students are encouraged to attend in order to ensure a broad, unconfined discussion. In that view, this workshop is intended for students and researchers of this faculty offering opportunities to meet new colleagues.Ostrav

Development of an integrated omics in silico workflow and its application for studying bacteria-phage interactions in a model microbial community

Microbial communities are ubiquitous and dynamic systems that inhabit a multitude of environments. They underpin natural as well as biotechnological processes, and are also implicated in human health. The elucidation and understanding of these structurally and functionally complex microbial systems using a broad spectrum of toolkits ranging from in situ sampling, high-throughput data generation ("omics"), bioinformatic analyses, computational modelling and laboratory experiments is the aim of the emerging discipline of Eco-Systems Biology. Integrated workflows which allow the systematic investigation of microbial consortia are being developed. However, in silico methods for analysing multi-omic data sets are so far typically lab-specific, applied ad hoc, limited in terms of their reproducibility by different research groups and suboptimal in the amount of data actually being exploited. To address these limitations, the present work initially focused on the development of the Integrated Meta-omic Pipeline (IMP), a large-scale reference-independent bioinformatic analyses pipeline for the integrated analysis of coupled metagenomic and metatranscriptomic data. IMP is an elaborate pipeline that incorporates robust read preprocessing, iterative co-assembly, analyses of microbial community structure and function, automated binning as well as genomic signature-based visualizations. The IMP-based data integration strategy greatly enhances overall data usage, output volume and quality as demonstrated using relevant use-cases. Finally, IMP is encapsulated within a user-friendly implementation using Python while relying on Docker for reproducibility. The IMP pipeline was then applied to a longitudinal multi-omic dataset derived from a model microbial community from an activated sludge biological wastewater treatment plant with the explicit aim of following bacteria-phage interaction dynamics using information from the CRISPR-Cas system. This work provides a multi-omic perspective of community-level CRISPR dynamics, namely changes in CRISPR repeat and spacer complements over time, demonstrating that these are heterogeneous, dynamic and transcribed genomic regions. Population-level analysis of two lipid accumulating bacterial species associated with 158 putative bacteriophage sequences enabled the observation of phage-host population dynamics. Several putatively identified bacteriophages were found to occur at much higher abundances compared to other phages and these specific peaks usually do not overlap with other putative phages. In addition, there were several RNA-based CRISPR targets that were found to occur in high abundances. In summary, the present work describes the development of a new bioinformatic pipeline for the analysis of coupled metagenomic and metatranscriptomic datasets derived from microbial communities and its application to a study focused on the dynamics of bacteria-virus interactions. Finally, this work demonstrates the power of integrated multi-omic investigation of microbial consortia towards the conversion of high-throughput next-generation sequencing data into new insights

Development of the High Resolution Melt (HRM) method to detect the HLA-B*58:01 allele in order to prevent allopurinol-associated drug hypersensitivity

The HLA-B*58:01 allele was identified as a genetic marker for allopurinol-induced severe cutaneous adverse drug reactions (SCARs) in gout patients. Malaysia has a high frequency of 10.4% of the HLA-B*58:01 allele in allopurinol-induced SCARs patients. However, the strength of association of the HLA-B*58:01 allele to allopurinol-induced SCARs still need to be further validated in Malaysian pharmacogenetics studies. This project aims to develop a new, cost-effective, user-friendly and rapid method of screening for this allele by using the High Resolution Melt (HRM) method. The HRM method was used for its ability of reference curve-based targeted genotyping, where a positive control’s melt curve is used as a reference for screening of unknown samples. A gout cohort (n=145) and a healthy volunteers cohort (n=145), matched for age, gender and ethnicity, were used for the HRM screening. The HRM method showed a sensitivity of 0%, specificity of 57%, positive predictive value of 0% and negative predictive value of 57%, due to the presence of significant limiting factors. Several significant limitations were met in this study, starting with the slow sample collection, low number of SCARs samples, positive control’s heterozygosity, low primer specificity and the high level of polymorphism in the HLAB*58:01 allele. Moreover, the Sanger sequencing and NGS methods were used to validate the HRM method and delve into the complexity of the HLA-B alleles’ role in Malaysians. The newer theory of the presence of numerous HLA-B alleles as pharmacogenetic markers in populations was also investigated. HLA-B*58:01 was seen as a strong genetic marker in mild allopurinol-induced hypersensitivities and SCARs by Sanger sequencing. HLA-B*58:01 positive samples identified by Sanger sequencing had high frequencies of 32.1% for two different alleles; HLA-B*58:01:01 and HLA-B*35:01:01. Moreover, healthy volunteer samples showed high frequencies of 28.5% for HLA-B*58:01:01 and HLA-B*35:01:01 alleles. Hence, all these aforementioned HLA-B alleles are identified as potential pharmacogenetic markers in Malaysia. Next Generation Sequencing (NGS) was performed on 6 gout samples and 3 Malaysian specific SNPs (rs11423052, rs151341211 and rs9279154) were identified for the HLA-B*58:01 allele. Future studies need to focus on SNPs amplification in order to fully exploit the HRM method’s strengths as a screening method

Development of the High Resolution Melt (HRM) method to detect the HLA-B*58:01 allele in order to prevent allopurinol-associated drug hypersensitivity

The HLA-B*58:01 allele was identified as a genetic marker for allopurinol-induced severe cutaneous adverse drug reactions (SCARs) in gout patients. Malaysia has a high frequency of 10.4% of the HLA-B*58:01 allele in allopurinol-induced SCARs patients. However, the strength of association of the HLA-B*58:01 allele to allopurinol-induced SCARs still need to be further validated in Malaysian pharmacogenetics studies. This project aims to develop a new, cost-effective, user-friendly and rapid method of screening for this allele by using the High Resolution Melt (HRM) method. The HRM method was used for its ability of reference curve-based targeted genotyping, where a positive control’s melt curve is used as a reference for screening of unknown samples. A gout cohort (n=145) and a healthy volunteers cohort (n=145), matched for age, gender and ethnicity, were used for the HRM screening. The HRM method showed a sensitivity of 0%, specificity of 57%, positive predictive value of 0% and negative predictive value of 57%, due to the presence of significant limiting factors. Several significant limitations were met in this study, starting with the slow sample collection, low number of SCARs samples, positive control’s heterozygosity, low primer specificity and the high level of polymorphism in the HLAB*58:01 allele. Moreover, the Sanger sequencing and NGS methods were used to validate the HRM method and delve into the complexity of the HLA-B alleles’ role in Malaysians. The newer theory of the presence of numerous HLA-B alleles as pharmacogenetic markers in populations was also investigated. HLA-B*58:01 was seen as a strong genetic marker in mild allopurinol-induced hypersensitivities and SCARs by Sanger sequencing. HLA-B*58:01 positive samples identified by Sanger sequencing had high frequencies of 32.1% for two different alleles; HLA-B*58:01:01 and HLA-B*35:01:01. Moreover, healthy volunteer samples showed high frequencies of 28.5% for HLA-B*58:01:01 and HLA-B*35:01:01 alleles. Hence, all these aforementioned HLA-B alleles are identified as potential pharmacogenetic markers in Malaysia. Next Generation Sequencing (NGS) was performed on 6 gout samples and 3 Malaysian specific SNPs (rs11423052, rs151341211 and rs9279154) were identified for the HLA-B*58:01 allele. Future studies need to focus on SNPs amplification in order to fully exploit the HRM method’s strengths as a screening method