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Genome-wide post-transcriptional regulation of bovine mammary gland response to Streptococcus uberis

Tabashiri R, Sharifi S, Pakdel A, Bakhtiarizadeh MR, Pakdel MH, Tahmasebi A, et al.

J Appl Genet, 2022 Dec;63(4):771-782.
PMID: 36066834 DOI: 10.1007/s13353-022-00722-y

MicroRNAs (miRNAs) as post-transcriptionally regulators of gene expression have been shown to be critical regulators to fine-tuning immune responses, besides their criteria for being an ideal biomarker. The regulatory role of miRNAs in responses to most mastitis-causing pathogens is not well understood. Gram-positive Streptococcus uberis (Str. uberis), the leading pathogen in dairy herds, cause both clinical and subclinical infections. In this study, a system biology approach was used to better understand the main post-transcriptional regulatory functions and elements of bovine mammary gland response to Str. uberis infection. Publicly available miRNA-Seq data containing 50 milk samples of the ten dairy cows (five controls and five infected) were retrieved for this current research. Functional enrichment analysis of predicted targets revealed that highly confident responsive miRNAs (4 up- and 19 downregulated) mainly regulate genes involved in the regulation of transcription, apoptotic process, regulation of cell adhesion, and pro-inflammatory signaling pathways. Time series analysis showed that six gene clusters significantly differed in comparisons between Str. uberis-induced samples with controls. Additionally, other bioinformatic analysis, including upstream network analysis, showed essential genes, including TP53 and TGFB1 and some small molecules, including glucose, curcumin, and LPS, commonly regulate most of the downregulated miRNAs. Upregulated miRNAs are commonly controlled by the most important genes, including IL1B, NEAT1, DICER1 enzyme and small molecules including estradiol, tamoxifen, estrogen, LPS, and epigallocatechin. Our study used results of next-generation sequencing to reveal key miRNAs as the main regulator of gene expression responses to a Gram-positive bacterial infection. Furthermore, by gene regulatory network (GRN) analysis, we can introduce the common upregulator transcription factor of these miRNAs. Such milk-based miRNA signature(s) would facilitate risk stratification for large-scale prevention programs and provide an opportunity for early diagnosis and therapeutic intervention.
Correction to: Genome‑wide post‑transcriptional regulation of bovine mammary gland response to Streptococcus uberis

Tabashiri R, Sharifi S, Pakdel A, Bakhtiarizadeh MR, Pakdel MH, Tahmasebi A, et al.

J Appl Genet, 2022 Dec;63(4):817.
PMID: 36125735 DOI: 10.1007/s13353-022-00724-w
Fulltext Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts

Callari M, Batra AS, Batra RN, Sammut SJ, Greenwood W, Clifford H, et al.

BMC Genomics, 2018 01 05;19(1):19.
PMID: 29304755 DOI: 10.1186/s12864-017-4414-y

BACKGROUND: Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human.
RESULTS: In this study we generated Whole Exome Sequencing (WES), Reduced Representation Bisulfite Sequencing (RRBS) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA and from a cohort of human breast cancers and their derived PDTXs. We show that using an In silico Combined human-mouse Reference Genome (ICRG) for alignment discriminates between human and mouse reads with up to 99.9% accuracy and decreases the number of false positive somatic mutations caused by misalignment by >99.9%. We also derived a model to estimate the human DNA content in independent PDTX samples. For RNA-seq and RRBS data analysis, the use of the ICRG allows dissecting computationally the transcriptome and methylome of human tumour cells and mouse stroma. In a direct comparison with previously reported approaches, our method showed similar or higher accuracy while requiring significantly less computing time.
CONCLUSIONS: The computational pipeline we describe here is a valuable tool for the molecular analysis of PDTXs as well as any other mixture of DNA or RNA species.
Fulltext Molecular landscape of immune pressure and escape in aplastic anemia

Pagliuca S, Gurnari C, Hercus C, Hergalant S, Nadarajah N, Wahida A, et al.

Leukemia, 2023 Jan;37(1):202-211.
PMID: 36253429 DOI: 10.1038/s41375-022-01723-w

Idiopathic aplastic anemia (IAA) pathophysiology is dominated by autoreactivity of human leukocyte antigen (HLA)-restricted T-cells against antigens presented by hematopoietic stem and progenitor cells (HSPCs). Expansion of PIGA and HLA class I mutant HSPCs have been linked to immune evasion from T-cell mediated pressures. We hypothesized that in analogy with antitumor immunity, the pathophysiological cascade of immune escape in IAA is initiated by immunoediting pressures and culminates with mechanisms of clonal evolution characterized by hits in immune recognition and response genes. To that end, we studied the genetic and transcriptomic make-up of the antigen presentation complexes in a large cohort of patients with IAA and paroxysmal nocturnal hemoglobinuria (PNH) by using single-cell RNA, high throughput DNA sequencing and single nucleotide polymorphism (SNP)-array platforms. At disease onset, HSPCs displayed activation of selected HLA class I and II-restricted mechanisms, without extensive inhibition of immune checkpoint apparatus. Using a newly implemented bioinformatic framework we found that not only class I but also class II genes were often impaired by acquisition of genetic aberrations. We also demonstrated the presence of novel somatic alterations in immune genes possibly contributing to the evasion from the autoimmune T-cells. In contrast, these hits were absent in myeloid neoplasia. These aberrations were not mutually exclusive with PNH and did not correlate with the accumulation of myeloid-driver hits. Our findings shed light on the mechanisms of immune activation and escape in IAA and define alternative modes of clonal hematopoiesis.
Fulltext Leukemia relapse via genetic immune escape after allogeneic hematopoietic cell transplantation

Pagliuca S, Gurnari C, Hercus C, Hergalant S, Hong S, Dhuyser A, et al.

Nat Commun, 2023 May 31;14(1):3153.
PMID: 37258544 DOI: 10.1038/s41467-023-38113-4

Graft-versus-leukemia (GvL) reactions are responsible for the effectiveness of allogeneic hematopoietic cell transplantation as a treatment modality for myeloid neoplasia, whereby donor T- effector cells recognize leukemia neoantigens. However, a substantial fraction of patients experiences relapses because of the failure of the immunological responses to control leukemic outgrowth. Here, through a broad immunogenetic study, we demonstrate that germline and somatic reduction of human leucocyte antigen (HLA) heterogeneity enhances the risk of leukemic recurrence. We show that preexistent germline-encoded low evolutionary divergence of class II HLA genotypes constitutes an independent factor associated with disease relapse and that acquisition of clonal somatic defects in HLA alleles may lead to escape from GvL control. Both class I and II HLA genes are targeted by somatic mutations as clonal selection factors potentially impairing cellular immune responses and response to immunomodulatory strategies. These findings define key molecular modes of post-transplant leukemia escape contributing to relapse.
Fulltext Leukemia relapse via genetic immune escape after allogeneic hematopoietic cell transplantation

Pagliuca S, Gurnari C, Hercus C, Hergalant S, Hong S, Dhuyser A, et al.

Res Sq, 2023 Apr 05.
PMID: 37066269 DOI: 10.21203/rs.3.rs-2773498/v1

Graft-versus-leukemia (GvL) reactions are responsible for the effectiveness of allogeneic hematopoietic cell transplantation as a treatment modality for myeloid neoplasia, whereby donor T- effector cells recognize leukemia neoantigens. However, a substantial fraction of patients experience relapses because of the failure of the immunological responses to control leukemic outgrowth. Here, through a broad immunogenetic study, we demonstrate that germline and somatic reduction of human leucocyte antigen (HLA) heterogeneity enhances the risk of leukemic recurrence. We show that preexistent germline-encoded low evolutionary divergence of class II HLA genotypes constitutes an independent factor associated with disease relapse and that acquisition of clonal somatic defects in HLA alleles may lead to escape from GvL control. Both class I and II HLA genes are targeted by somatic mutations as clonal selection factors potentially impairing cellular immune reactions and response to immunomodulatory strategies. These findings define key molecular modes of post-transplant leukemia escape contributing to relapse.
Fulltext BioHackathon 2015: Semantics of data for life sciences and reproducible research

Vos RA, Katayama T, Mishima H, Kawano S, Kawashima S, Kim JD, et al.

F1000Res, 2020;9:136.
PMID: 32308977 DOI: 10.12688/f1000research.18236.1

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.