István Prazsák

Human spaceflight may perturb the gut microbiota, but densely sampled short missions remain poorly characterized. We profiled 27 phase-matched fecal samples from two astronauts during an 18-day International Space Station mission and one ground-based participant following the same daily schedule using Oxford Nanopore full-length 16S sequencing. Participant identity dominated genus-level Bray- Curtis variation (R2 = 0.489, p < 0.001). In astronaut-only community analyses, mission phase explained 23.4% of genus-level (p = 0.035) and 22.3% of species-level (p = 0.021) variation. Astronauts showed greater displacement from personal baselines than B1 (0.331 versus 0.171) and 1.58-fold higher volatility. Astronaut-only taxon models identified 2 of 81 genera and 5 of 139 species; Collinsella increased from quarantine to orbit (coefficient = 2.586, q = 0.037). Thus, the short-duration spaceflight interval was accompanied by individualized, temporally localized community and taxon shifts rather than uniform microbiota restructuring.

The canine gut microbiome serves as a key model for veterinary and human health research, but inconsistent findings arise due to methodological variations. This study presents a three-part dataset to clarify how DNA extraction, primer selection, and sequencing platforms influence microbial profiling. First, we performed ultra-deep sequencing of a single dog fecal sample using five DNA isolation kits, multiple library protocols, and four sequencing platforms (Illumina MiSeq/NovaSeq, ONT MinION, PacBio Sequel IIe), enabling direct comparisons of 16S rRNA and shotgun sequencing techniques. Second, we analyzed 40 fecal samples from eight co-housed dogs using Zymo High-Molecular-Weight (ZHMW) and Zymo MagBead (ZMB) extraction kits to assess longitudinal extraction-kit effects. Third, we evaluated three 16S primer systems (standard ONT, PacBio, and modified ONT with degenerate bases) using synthetic mock communities and human/canine fecal samples to quantify primer biases. By integrating synthetic and biological replicates, this dataset provides a standardized resource for benchmarking bioinformatics pipelines and improving cross-study comparability. The study generated 75.31GB of new sequencing data: 43.451GB from ZHMW-ZMB comparisons, 22.611GB for primer evaluations, and 9.191GB from the single-sample analysis. Combined with 31.51GB of prior data, the total dataset exceeds 1061GB, including all analytical outputs. These resources enhance methodological transparency and accuracy in canine gut microbiome research across diverse laboratory workflows.

A critical issue in microbiome research is the selection of reliable laboratory and bioinformatics pipelines. In the absence of generally accepted technical benchmarks and evaluation standards, comparing data generated by different studies becomes challenging. In this work, we carried out the most comprehensive study to date on this topic. We encompassed every stage of processing, from DNA extraction to computational assessment. We adopted four procedures for DNA purification, six for library construction, three for sequencing, and five for bioinformatics. Additionally, we used datasets published by others to corroborate our results. We introduced a software tool that distinctively delivers consistent results, irrespective of sample or dataset origins. This study underscores the importance of methodological optimization at the outset of research projects to ensure the reliability of results and their comparability with findings from other studies. Additionally, this study provides an optimized robust pipeline for gut microbiome analysis.

In the last couple of years, the rapid advances and decreasing costs of sequencing technologies have revolutionized transcriptomic research. Long-read sequencing (LRS) techniques are able to detect full-length RNA molecules in a single run without the need for additional assembly steps. LRS studies have revealed an unexpected transcriptomic complexity in a variety of organisms, including viruses. A number of transcripts with proven or putative regulatory role, mapping close to or overlapping the replication origins (Oris) and the nearby transcription activator genes, have been described in herpesviruses. In this study, we applied both newly generated and previously published LRS and short-read sequencing datasets to discover additional Ori-proximal transcripts in nine herpesviruses belonging to all of the three subfamilies (alpha, beta and gamma). We identified novel long non-coding RNAs (lncRNAs), as well as splice and length isoforms of mRNAs and lncRNAs. Furthermore, our analysis disclosed an intricate meshwork of transcriptional overlaps at the examined genomic regions. Our results suggest the existence of a ‘super regulatory center’, which controls both the replication and the global transcription through multilevel interactions between the molecular machineries.

The recent Monkeypox outbreak showed the importance of studying the basic biology of orthopoxviruses. However, the transcriptome of its causative agent has not been investigated before neither with short-, nor with long-read sequencing approaches. This Oxford Nanopore long-read RNA-Sequencing dataset fills this gap. Our direct cDNA and native RNA sequencing data enable the in-depth characterization of the transcriptomic architecture and dynamics of the gene expressions of monkeypox virus; and also the deeper understanding of the changes it causes in the host cells on a transcriptome level.

Background: Recent studies have disclosed the genome, transcriptome, and epigenetic compositions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the effect of viral infection on gene expression of the host cells. It has been demonstrated that, besides the major canonical transcripts, the viral genome also codes for noncanonical RNA molecules. While the structural characterizations have revealed a detailed transcriptomic architecture of the virus, the kinetic studies provided poor and often misleading results on the dynamics of both the viral and host transcripts due to the low temporal resolution of the infection event and the low virus/cell ratio (multiplicity of infection [MOI] = 0.1) applied for the infection. It has never been tested whether the alteration in the host gene expressions is caused by aging of the cells or by the viral infection. Findings: In this study, we used Oxford Nanopore's direct cDNA and direct RNA sequencing methods for the generation of a high-coverage, high temporal resolution transcriptomic dataset of SARS-CoV-2 and of the primate host cells, using a high infection titer (MOI = 5). Sixteen sampling time points ranging from 1 to 96 hours with a varying time resolution and 3 biological replicates were used in the experiment. In addition, for each infected sample, corresponding noninfected samples were employed. The raw reads were mapped to the viral and to the host reference genomes, resulting in 49,661,499 mapped reads (54,62 Gbs). The genome of the viral isolate was also sequenced and phylogenetically classified. Conclusions: This dataset can serve as a valuable resource for profiling the SARS-CoV-2 transcriptome dynamics, the virus–host interactions, and the RNA base modifications. Comparison of expression profiles of the host gene in the virally infected and in noninfected cells at different time points allows making a distinction between the effect of the aging of cells in culture and the viral infection. These data can provide useful information for potential novel gene annotations and can also be used for studying the currently available bioinformatics pipelines.

In this study, a structural profiling of equid alphaherpesvirus 1 (EHV-1) transcriptome was carried out using next-generation (Illumina) and third-generation (Oxford Nanopore Technologies) sequencing platforms. We annotated the canonical mRNA molecules and their isoforms, including transcript start and end site isoforms, and splice variants. Additionally, a number of putative 5′-truncated mRNAs containing shorter in-frame ORFs were detected. We also demonstrated that EHV-1 produces a high number of non-coding transcripts, including antisense and intergenic RNAs. One of the most remarkable features of the EHV-1 is the generation of abundant fusion transcripts some of which encoding chimeric polypeptides. We observed a higher number of splicing and transcriptional overlaps than in related viruses. Additionally, we found that many upstream genes of tandem gene clusters have their own transcript end sites (TESs) besides the co-terminal TESs, which is rare in other alphaherpesviruses. We show here that the replication origins (OriS and OriL) of the virus are co-localized with promoter sequences and overlap with specific RNA molecules. Furthermore, we discovered a novel non-coding RNA (designated as NOIR) that overlaps the 5′-ends of the longer transcript variants encoded by the two main transactivator genes ORF64 and 65 bracketing the OriL. These all suggest the existence of a central regulatory system which controls the genome-wide transcription and the replication through a mechanism based on the interference between the machineries carrying out the synthesis of DNA and RNA.

Vesicular stomatitis Indiana virus (VSIV) of genus Vesiculovirus, species IndianaVesiculovirus (formerly as Vesicular stomatitis virus, VSV) causes a disease in livestock that is very similar to the foot and mouth disease, thereby an outbreak may lead to significant economic loss. Long-read sequencing (LRS) -based approaches already reveal a hidden complexity of the transcriptomes in several viruses. This technique has been utilized for the sequencing of the VSIV genome, but our study is the first for the application of this technique for the profiling of the VSIV transcriptome. Since LRS is able to sequence full-length RNA molecules, it thereby provides more accurate annotation of the transcriptomes than the traditional short-read sequencing methods. The objectives of this study were to assemble the complete transcriptome of using nanopore sequencing, to ascertain cell-type specificity and dynamics of viral gene expression, and to evaluate host gene expression changes induced by the viral infection. We carried out a time-course analysis of VSIV gene expression in human glioblastoma and primate fibroblast cell lines using a nanopore-based LRS approach and applied both amplified and direct cDNA sequencing (as well as cap-selection) for a fraction of samples. Our investigations revealed that, although the VSIV genome is simple, it generates a relatively complex transcriptomic architecture. In this study, we also demonstrated that VSIV transcripts vary in structure and exhibit differential gene expression patterns in the two examined cell types.