SEARCH · Search bioRxiv

Results for “Bioinformatics”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30Linked to original sources

bioRxiv2022

A bioinformatics approach to systematically analyze the molecular patterns of monkeypox virus-host cell interactions

Monkeypox has been spreading worldwide since May 2022, when the World Health Organization (WHO) declared the outbreak of a "Public health emergency of international concern". The spread of monkeypox has posed a serious threat to the health of people all over the world but few studies have been carried out on it, and the molecular mechanism of monkeypox after infection remains unclear. We therefore implemented a transcriptome analysis to identify signaling pathways and biomarkers in monkeypox-infected cells to help understand monkeypox-host cell interactions. In this study, the dataset GSE36854 and GSE11234 were obtained from GEO. Among them, 84 significantly different genes were identified in the dataset GSE36854, followed by KEGG, GO analysis protein-protein interaction (PPI) construction and Hub gene extraction. We also analyzed the expression regulation patterns of hub genes and screened the drugs targeting the hub genes. The results showed that monkeypox-infected cells significantly activated the cellular immune response, and induced inflammatory response. IER3, IFIT2, IL11, ZC3H12A, EREG, IER2, NFKBIE, FST, IFIT1 and AREG were the top 10 hub genes, in which anti-viral gene IFIT1 and IFIT2 were significantly suppressed. AP-26113 and itraconazole promoting the expression of IFIT1 and IFIT2 may be used as new candidates for the treatment of monkeypox viral infection. Our results provide a new entry point for understanding the mode of interaction between monkeypox virus and its host.

microbiology↗

bioRxiv2022

Bioinformatics techniques for efficient structure prediction of SARS-CoV-2 protein ORF7a via structure prediction approaches

Protein is the building block for all organisms. Protein structure prediction is always a complicated task in the field of proteomics. DNA and protein databases can find the primary sequence of the peptide chain and even similar sequences in different proteins. Mainly, there are two methodologies based on the presence or absence of a template for Protein structure prediction. Template-based structure prediction (threading and homology modeling) and Template-free structure prediction (ab initio). Numerous web-based servers that either use templates or do not can help us forecast the structure of proteins. In this current study, ORF7a, a transmembrane protein of the SARS-coronavirus, is predicted using Phyre2, IntFOLD, and Robetta. The protein sequence is straightforwardly entered into the sequence bar on all three web servers. Their findings provided information on the domain, the region with the disorder, the global and local quality score, the predicted structure, and the estimated error plot. Our study presents the structural details of the SARS-CoV protein ORF7a. This immunomodulatory component binds to immune cells and induces severe inflammatory reactions.

microbiology↗

bioRxiv2023

A bioinformatics screen reveals Hox and chromatin remodeling factors at the Drosophila histone locus

Cells orchestrate histone biogenesis with strict temporal and quantitative control. To efficiently regulate histone biogenesis, the repetitive Drosophila melanogaster replication-dependent histone genes are arrayed and clustered at a single locus. Regulatory factors concentrate in a nuclear body known as the histone locus body (HLB), which forms around the locus. Historically, HLB factors are largely discovered by chance, and few are known to interact directly with DNA. It is therefore unclear how the histone genes are specifically targeted for unique and coordinated regulation. To expand the list of known HLB factors, we performed a candidate-based screen by mapping 30 publicly available ChIP datasets and 27 factors to the Drosophila histone gene array. We identified novel transcription factor candidates, including the Drosophila Hox proteins Ultrabithorax, Abdominal-A and Abdominal-B, suggesting a new pathway for these factors in influencing body plan morphogenesis. Additionally, we identified six other transcription factors that target the histone gene array: JIL-1, Hr78, the long isoform of fs(1)h as well as the generalized transcription factors TAF-1, TFIIB, and TFIIF. Our foundational screen provides several candidates for future studies into factors that may influence histone biogenesis. Further, our study emphasizes the powerful reservoir of publicly available datasets, which can be mined as a primary screening technique.

molecular biology↗

bioRxiv2023

A precision overview of genomic resistance screening in isolates of Mycobacterium tuberculosis using web-based bioinformatics tools.

Tuberculosis (TB) is among the most deadly diseases that affect worldwide, its impact is mainly due to the continuous emergence of resistant isolates during treatment due to the laborious process of resistance diagnosis, non-adherence to treatment and circulation of previously resistant isolates of Mycobacterium tuberculosis. The aim in this study was evaluate the performance and functionalities of web-based tools: Mykrobe, TB-profiler, PhyReSse, KvarQ, and SAM-TB for detecting resistance in isolate of Mycobacterium tuberculosis in comparison with conventional drug susceptibility tests. We used 88 M. tuberculosis isolates which were drug susceptibility tested and subsequently fully sequenced and web-based tools analysed. Statistical analysis was performed to determine the correlation between genomic and phenotypic analysis. Our data show that the main sub-lineage was LAM (44.3%) followed by X-type (23.0%) within isolates evaluated. Mykrobe has a higher correlation with DST (98% of agreement and 0.941Cohens Kappa) for global resistance detection, but SAM-TB, PhyReSse and Mykrobe had a better correlation with DST for first-line drug analysis individually. We have identified that 50% of mutations characterised by all web-based tools were canonical in rpoB, katG, embB, pncA, gyrA and rrs regions. Our findings suggest that SAM-TB, PhyReSse and Mykrobe were the web-based tools more efficient to determine canonical resistance-related mutations, however more analysis should be performed to improve second-line detection. The improvement of surveillance programs for the TB isolates applying WGS tools against first line drugs, MDR-TB and XDR-TB are priorities to discern the molecular epidemiology of this disease in the country. ImportanceTuberculosis, an infectious disease caused by Mycobacterium tuberculosis, which most commonly affects the lungs and is often spread through the air when infected people cough, sneeze, or spit. However, despite the existence of effective drug treatment, the patient adherence, long duration of treatment, and late diagnosis, have reduced the effectiveness of therapy and raised the drug resistance. The increase in resistant cases, added to the impact of the COVID-19 pandemic, have highlighted the importance of implementing efficient and timely diagnostic methodologies worldwide. The significance of our research is in evaluating and identifying the more efficient and friendly web-based tool to characterise the resistance in Mycobacterium tuberculosis by whole genome sequencing, which will allow apply it more routinely to improve TB strain surveillance programs locally.

microbiology↗

bioRxiv2023

Tumor microenvironment exploration and therapeutic target identification in bladder cancer based on Cuproptosis signature and chemotherapy-resistant model: results from bioinformatics and experimental validation

BackgroundThe discovery of cuproptosis provides a new way to make full use of the pathophysiological effects of copper for anticancer therapy and could help identify a therapeutic target in bladder cancer. MethodsIn this study, 411 BLCA tumor samples from the Cancer Genome Atlas (TCGA) cohort were obtained. Differentially expressed genes (DEGs) between chemotherapy-sensitive and chemotherapy-resistant mouse bladder cancers were also obtained. Sixteen genes were defined as cuproptosis-related genes (CRGs), and the cutoff score was calculated based on LASSO Cox regression. CCK-8 and Transwell assays were used to detect the migration and proliferation of 5637 and T24 cells, respectively. Liarozole dihydrochloride (L-D), a mild P450, inhibits the expression of CYP26B1. Multiple immunohistochemistry analyses were used to explore the association between the immune microenvironment and CRGs. ResultsA higher Cuproptosis score was significantly associated with worse overall survival in BLCA (p<0.0001, HR=2.32). Single-cell transcriptional data were used to assess the function of CYP26B1 and CYP26B1 may be negatively associated with DNA damage and repair. In vitro experiments indicated that overexpression of CYP26B1 enhanced the migration and proliferation of BLCA cells, while L-D inhibited the migration and proliferation of BLCA cells. A higher expression level of Dihydrolipoamide S-Succinyltransferase (DLST) serves could as a risk factor in patients treated with atezolizumab and higher expression of DLST suggest an immunosuppressive microenvironment. ConclusionsCYP26B1 may be a therapeutic target for bladder cancer, and the higher expression of DLST may suggest an immunosuppressive microenvironment in BLCA. Key MessagesCuproptosis may be associated with the chemotherapy-resistance of bladder cancer and our findings may provide new ideas for the treatment of bladder cancer.

genomics↗

bioRxiv2023

Bioinformatic and fine-scale chromosomal mapping uncover the essence and evolution of eliminated chromosomes in the Japanese hagfish, Eptatretus burgeri, through repetitive DNA family analysis

In the Japanese hagfish, Eptatretus burgeri, approximately 21% of the genomic DNA in germ cells (2n=52) consists of 16 chromosomes (eliminated [E]-chromosomes) that are eliminated from presumptive somatic cells (2n=36). To uncover the eliminated genome (E-genome), we have identified 16 eliminated repetitive DNA families from eight hagfish species, with 11 of these repeats being selectively amplified in the germline genome of E. burgeri. Furthermore, we have demonstrated that six of these sequences, namely EEEb1-6, are exclusively localized on all 16 E-chromosomes. This has led to the hypothesis that the eight pairs of E-chromosomes are derived from one pair of ancestral chromosomes via multiple duplication events over a prolonged evolutionary period. NGS analysis has recently facilitated the re-assembly of two distinct draft genomes of E. burgeri, derived from the testis and liver. This advancement allows for the prediction of not only nonrepetitive eliminated sequences but also over 100 repetitive and eliminated sequences, accomplished through K-mer-based analysis. In this study, we report four novel eliminated repetitive DNA sequences (designated as EEEb7-10) and confirm the relative chromosomal localization of all eliminated repeats (EEEb1-10) by fluorescence in situ hybridization (FISH). With the exception of EEEb10, all sequences were exclusively detected on EEEb1-positive chromosomes. Surprisingly, EEEb10 was detected as an intense signal on EEEb1-positive chromosomes and as a scattered signal on other chromosomes in germ cells. The study further divided the eight pairs of E-chromosomes into six groups based on the signal distribution of each DNA family, and fiber-FISH experiments showed that the EEEb2-10 family was dispersed in the EEEb1-positive extended chromatin fiber. These findings provide new insights into the mechanisms underlying chromosome elimination and the evolution of E-chromosomes, supporting our previous hypothesis.

molecular biology↗

bioRxiv2023

Bacteriocin Distribution Patterns in Enterococcus faecium and Enterococcus lactis: Bioinformatic Analysis Using a Tailored Genomics Framework

Multidrug-resistant Enterococcus faecium represent a major concern due to their ability to thrive in diverse environments and cause life-threatening infections. While antimicrobial resistance and virulence mechanisms have been extensively studied, the contribution of bacteriocins to E. faeciums adaptability remains poorly explored. E. faecium, within the Bacillota phylum, is a prominent bacteriocin producer. Here, we developed a tailored database of 76 Bacillota bacteriocins (217 sequences, including 40 novel bacteriocins) and applied it to uncover bacteriocin distribution patterns in 997 quality-filtered E. faecium and Enterococcus lactis (former E. faecium clade B) genomes. Curated using computational pipelines and literature mining, our database demonstrates superior precision versus leading public tools in identifying diverse bacteriocins. Distinct bacteriocin profiles emerged between E. faecium and E. lactis, highlighting species-specific adaptations. E. faecium strains from hospitalized patients were significantly enriched for bacteriocins as entA, bac43, bacAS5 and bacAS11. These bacteriocins strongly associated with antibiotic resistance, particularly vancomycin and ampicillin, and Inc18 rep2_pRE25-derivative plasmids, classically associated with vancomycin resistance transposons. Our integrated genomic and epidemiological analysis elucidates meaningful connections between bacteriocin determinants, antimicrobial resistance, mobile genetic elements, and ecological origins in E. faecium. This work significantly expands the knowledge on the understudied bacteriocin diversity in opportunistic enterococci, revealing their contribution to environmental adaptation. Further characterization of strain-level bacteriocin landscapes could inform strategies to combat high-risk clones. Overall, these insights provide a framework for unravelling bacteriocins therapeutic and biotechnological potential.

genomics↗

bioRxiv2023

Bioinformatic, enzymatic and structural characterization of Trichuris suis hexosaminidase HEX-2

Hexosaminidases are key enzymes in glycoconjugate metabolism and occur in all kingdoms of life. Here, we have investigated the phylogeny of the GH20 glycosyl hydrolase family in nematodes and identified a {beta}-hexosaminidase subclade only present in the Dorylaimia. We have expressed one of these, HEX-2 from Trichuris suis, a porcine parasite, and shown that it prefers an aryl {beta}-N-acetylgalactosaminide in vitro. HEX-2 has an almost neutral pH optimum and is best inhibited by GalNAc-isofagomine. Towards N-glycan substrates, it displays a preference for the removal of GalNAc residues from LacdiNAc motifs as well as the GlcNAc attached to the 1,3-linked core mannose. Thereby, it has a broader specificity than insect fused lobes (FDL) hexosaminidases, but one narrower than distant homologues from plants. Its X-ray crystal structure, the first of any subfamily 1 GH20 hexosaminidase to be determined, is closest to Streptococcus pneumoniae GH20C and the active site is predicted to be compatible with accommodating both GalNAc and GlcNAc. The new structure extends our knowledge about this large enzyme family, particularly as T. suis HEX-2 also possesses the key glutamate residue found in human hexosaminidases of either GH20 subfamily, including HEXD whose biological function remains elusive.

biochemistry↗

bioRxiv2023

Mice Models to Bioinformatics Methods Led to the Discovery of Antidiabetic Compounds in the F. racemosa Plant Extracts

One of the primary health issues caused by inadequate blood sugar regulation is Diabetes Mellitus (DM). Diabetes and its consequences remain clinically significant even with the development of oral hypoglycemic medications. Therefore, Ficus racemosa (F. racemosa) plant has been studied for assessing of its antidiabetic potential coupling with animal model and in silico experiments. Drug Alloxan (150 mg/kg) was injected to induce the experimental diabetes in Swiss Albino mice, and two doses methanol extract of the F. racemosa fruit (300 and 500 mg/kg) along with glibenclamide (5 mg/kg) were given orally. Oral Glucose Tolerance Test (OGTT) and acute toxicity were performed as well in both diabetic and non-diabetic mice. Later, in silico experiments including ADMET profiling, molecular docking and simulations were performed. The administration of a dosage less than 3000 mg/kg has been observed to be well-tolerated by mice, with no reported instances of mortality or adverse effects. Following oral administration for 7 days, the blood glucose level (BGL) was significantly decreased in mice model in both doses of extracts, indicating the effect of F. racemosa. Subsequent to this, molecular docking and simulations have indicated that the SIRT1 receptor exhibits a higher binding affinity towards four specific compounds, namely Friedelin, Lupeol Acetate, Gluanol, and Ferulic Acid, as indicated by the dynamics parameters and interacting residues. The current investigation provided evidence that the fruit extract of F. racemosa significantly mitigated the hyperglycemic impact. Moreover, a total of four substances have been found that play a crucial role in the mechanisms behind the reduction of diabetic effects. Hence, the current investigation could potentially serve as a viable therapeutic approach in the treatment of diabetes.

microbiology↗

bioRxiv2023

Integrated bioinformatics and wet-lab analysis revealed prominent inflammatory genes of Extracellular Matrix as prognostic biomarkers in patients with advance IBD requiring early surgery

BackgroundThe number of patients with inflammatory bowel disease (IBD) is increasing worldwide. Due to the fact that at the age of 20 to 30 years, this autoimmune disease is very common; Investigating and identifying prognostic biomarkers in advanced IBD is very important; Because according to the identification of these biomarkers, patients who need early surgery can be nominated and undergo surgery without wasting time and treatment costs. In this study, with the aim of identifying effective biomarkers involved in the inflammatory part of extracellular matrix (ECM) in the early surgery of IBD, separately from Crohns disease and ulcerative colitis. MethodIn this study, we examined 50 patients in both patient groups as well as the normal group. The expression of the nominated genes MASP2, DKC1, HNF4A, and STAT3 was analyzed using quantitative polymerase chain reaction (Q-PCR) and relative quantification was determined using the 2-{Delta}{Delta}Ct method. ROC curve analysis was performed to compare IBD (UC & CD) and normal for the investigated genes. The correlation between adhesion molecule gene expression and immunophenotype was analyzed. Also we comprehensively analyzed the genetic alteration, prognostic value and gene regulatory networks using multiple databases. ResultThe obtained results showed that MASP2 and DKC1 genes were significantly expressed in advanced UC patients, as well as HNF4A and STAT3 in advanced CD patients. ConclusionIt can be stated that the biomarker panel MASP2, DKC1, HNF4A, and STAT3 related to them have a significant prognostic role in the candidates of IBD patients for early surgery. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/570869v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@1f1de07org.highwire.dtl.DTLVardef@27db16org.highwire.dtl.DTLVardef@a095f2org.highwire.dtl.DTLVardef@d46c38_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2024

Genetic and bioinformatic analyses reveal transcriptional networks underlying dual genomic coordination of mitochondrial biogenesis

Mitochondrial biogenesis requires the expression of genes encoded by both the nuclear and mitochondrial genomes. However, aside from a handful transcriptional factors regulating specific subsets of mitochondrial genes, the overall architecture of the transcriptional control of mitochondrial biogenesis remains to be elucidated. The mechanisms coordinating these two genomes are largely unknown. We performed a targeted RNAi screen in developing eyes with reduced mitochondrial DNA content, anticipating a synergistic disruption of tissue development due to impaired mitochondrial biogenesis and mtDNA deficiency. Among 638 transcription factors annotated in Drosophila genome, 77 were identified as potential regulators of mitochondrial biogenesis. Utilizing published ChIP-seq data of positive hits, we constructed a regulatory network revealing the logic of the transcription regulation of mitochondrial biogenesis. Multiple transcription factors in core layers had extensive connections, collectively governing the expression of nearly all mitochondrial genes, whereas factors sitting on the top layer may respond to cellular cues to modulate mitochondrial biogenesis through the underlying network. CG1603, a core component of the network, was found to be indispensable for the expression of most nuclear mitochondrial genes, including those required for mtDNA maintenance and gene expression, thus coordinating nuclear genome and mtDNA activities in mitochondrial biogenies. Additional genetics analyses validated YL-1, a transcription factor upstream of CG1603 in the network, as a regulator controlling CG1603 expression and mitochondrial biogenesis.

genetics↗

bioRxiv2024

The Updated Mouse Universal Genotyping Array Bioinformatic Pipeline Improves Genetic QC in Laboratory Mice

The MiniMUGA genotyping array is a popular tool for genetic QC of laboratory mice and genotyping of samples from most types of experimental crosses involving laboratory strains, particularly for reduced complexity crosses. The content of the production version of the MiniMUGA array is fixed; however, there is the opportunity to improve arrays performance and the associated reports usefulness by leveraging thousands of samples genotyped since the initial description of MiniMUGA in 2020. Here we report our efforts to update and improve marker annotation, increase the number and the reliability of the consensus genotypes for inbred strains and increase the number of constructs that can reliably be detected with MiniMUGA. In addition, we have implemented key changes in the informatics pipeline to identify and quantify the contribution of specific genetic backgrounds to the makeup of a given sample, remove arbitrary thresholds, include the Y Chromosome and mitochondrial genome in the ideogram, and improve robust detection of the presence of commercially available substrains based on diagnostic alleles. Finally, we have made changes to the layout of the report, to simplify the interpretation and completeness of the analysis and added a table summarizing the ideogram. We believe that these changes will be of general interest to the mouse research community and will be instrumental in our goal of improving the rigor and reproducibility of mouse-based biomedical research.

genetics↗

bioRxiv2024

Antibacterial T6SS1 cluster identification and bioinformatics characterization of their putative effectors in Shiga toxin-producing Escherichia coli

Shiga toxing-producing Escherichia coli (STEC) O22:H8 strain is a serotype occasionally isolated in Argentinian cattle. Preliminary works showed that the cattle carrying STEC O22:H8 strains could not be experimentally colonized by EHEC O157:H7 strain. The type 6 secretion system (T6SS) is one of the most versatile virulence mechanisms involved in delivering effectors, particularly the T6SS1 translocate antibacterial toxins effectors during bacterial competition for niche-space. In this work, we could evidence the molecular bases of the success of STEC O22:H8 (154) strain during bacterial competition against EHEC O157:H7 strains. The genome sequence of STEC O22:H8 (154) allowed us to identify a complete T6SS1 cluster. In addition, we identify and characterized several putative T6SS1-antibacterial effectors encoded inside the T6SS1 clusters and in genomic pathogenic islands. Competition assays against EHEC O157:H7 strain confirmed the antibacterial activity of STEC O22:H8 (154) strain in vitro. Considering the absent of T6SS1 in STEC strains, we proposed the recent horizontal transfer acquisition and the most probably donor belong to the same Escherichia coli species. A safe STEC O22:H8 (154){Delta} stx would be used as a new strategy to fight STECs in bovine intestinal colonization, leading in a reduction in beef contamination and consequently HUS cases in humans.

microbiology↗

bioRxiv2024

Bioinformatic prediction and high throughput in vivo screening to identify cis-regulatory elements for the development of algal synthetic promoters

Algae biotechnology holds immense promise for revolutionizing the bioeconomy through the sustainable and scalable production of various bioproducts. However, its development has been hindered by the lack of advanced genetic tools. This study introduces a synthetic biology approach to develop such tools, focusing on the construction and testing of synthetic promoters. By analyzing conserved DNA motifs within the promoter regions of highly expressed genes across six different algal species, we identified cis-regulatory elements (CREs) associated with high transcriptional activity. Combining the algorithms POWRS, STREME and PhyloGibbs, we predicted 1511 CREs and inserted them into a minimal synthetic promoter sequence in 1, 2 or 3 copies, resulting in 4533 distinct synthetic promoters. These promoters were evaluated in vivo for their capacity to drive the expression of a transgene in a high-throughput manner through next-generation sequencing post antibiotic selection and fluorescence-activated cell sorting. To validate our approach, we sequenced hundreds of transgenic lines showing high GFP expression. Further, we individually tested fourteen identified promoters, revealing substantial increases in GFP expression--up to nine times higher than the baseline synthetic promoter, with five matching or even surpassing the performance of the native AR1 promoter. As a result of this study, we identified a catalog of CREs that can now be used to build superior synthetic algal promoters. More importantly, here we present a validated pipeline to generate building blocks for innovative synthetic genetic tools applicable to any algal species with a sequenced genome and transcriptome dataset. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/585996v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@1869cd4org.highwire.dtl.DTLVardef@a25d8dorg.highwire.dtl.DTLVardef@1abd96forg.highwire.dtl.DTLVardef@1501bc8_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2024

Identification of Candidate Diagnostic gene CDC25C for Trametinib-induced Cardiotoxicity by Integrating Bioinformatics and Machine Learning

Trametinib is a MEK inhibitor that has been shown to have considerable efficacy in retarding melanoma progression. However, the exact mechanism of cardiotoxicity induced by trametinib remains unclear. Our study was designed to investigate the underlying mechanisms by which trametinib-induced cardiotoxicity (TIC) might exist, offering novel perspectives and guidance for potential prediction, diagnosis, and treatment of TIC. The GSE217421 dataset indicated 574 up-regulated and 705 down-regulated DEGs. According to the KEGG analysis, these genes were implicated in several pathways and functions, including Cell Cycle, Axon Guidance, Cellular Senescence, and Dilated Cardiomyopathy. The GO analysis suggested their association with Mitotic Cell Cycle, Microtubule Cytoskeleton and Adenyl Nucleotide Binding. The hub genes (CDC25C) for TIC were screened through Multiple machine learning algorithms. Next, The expression level of CDC25C was verified using the GSE217423 validation set. Nomogram model based on CDC25C demonstrated excellent diagnostic capability according to three different evaluation measures. To further explore the regulatory mechanism of CDC25C in TIC, we constructed a multi-regulatory network using miRNAs-lncRNAs-TFs-CDC25C and conducted an immunoinfiltration analysis. Our study suggests that CDC25C may be a candidate diagnostic gene and a potential therapeutic target for the early occurrence and development of TIC. This provides new ideas for the prediction, diagnosis and treatment strategies for TIC.

cancer biology↗

bioRxiv2024

Characterization and bioinformatic filtering of ambient gRNAs in single-cell CRISPR screens using CLEANSER

Recent technological developments in single-cell RNA-seq CRISPR screens enable high-throughput investigation of the genome. Through transduction of a gRNA library to a cell population followed by transcriptomic profiling by scRNA-seq, it is possible to characterize the effects of thousands of genomic perturbations on global gene expression. A major source of noise in scRNA-seq CRISPR screens are ambient gRNAs, which are contaminating gRNAs that likely originate from other cells. If not properly filtered, ambient gRNAs can result in an excess of false positive gRNA assignments. Here, we utilize CRISPR barnyard assays to characterize ambient gRNA noise in single-cell CRISPR screens. We use these datasets to develop and train CLEANSER, a mixture model that identifies and filters ambient gRNA noise. This model takes advantage of the bimodal distribution between native and ambient gRNAs and includes both gRNA and cell-specific normalization parameters, correcting for confounding technical factors that affect individual gRNAs and cells. The output of CLEANSER is the probability that a gRNA-cell assignment is in the native distribution over the ambient distribution. We find that ambient gRNA filtering methods impact differential gene expression analysis outcomes and that CLEANSER outperforms alternate approaches by increasing gRNA-cell assignment accuracy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/611293v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@165c63dorg.highwire.dtl.DTLVardef@ba0e15org.highwire.dtl.DTLVardef@f2b12eorg.highwire.dtl.DTLVardef@14e6c86_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

FishPi: a bioinformatic prediction tool to link piRNA and transposable elements in zebrafish

BackgroundPiwi-interacting RNAs (piRNA)s are non-coding small RNAs that post-transcriptionally affect gene expression and regulation. Through complementary seed region binding with transposable elements (TEs), piRNAs protect the genome from transposition. A tool to link piRNAs with complementary TE targets will improve our understanding of the role of piRNAs in genome maintenance and gene regulation. Existing tools such as TEsmall can process sRNA-seq datasets to produce differentially expressed piRNAs, and piRScan developed for nematodes can link piRNAs and TEs but it requires knowledge about the target region of interest and works backwards. ResultsWe have therefore developed FishPi to predict the pairings between piRNA and TEs for available genomes from zebrafish, medaka and tilapia, with full user customisation of parameters including orientation of piRNA, mismatches in the piRNA seed binding to TE and scored output lists of piRNA-TE matches. FishPi works with individual piRNAs or a list of piRNA sequences in fasta format. The software focuses on the piRNA-TE seed region and analyses reference TEs for piRNA complementarity. TE type is examined, counted and stored to a dictionary, with genomic loci recorded. Any updates to piRNA-TE binding rules can easily be incorporated by changing the seed-region options in the graphic user-interface. FishPi provides a graphic interface using tkinter for the user to input piRNA sequences to generate comprehensive reports on piRNA-TE interactions. FishPi can easily be adapted to genomes from other species and taxa opening the interpretation of piRNA functionality to a wide community. ConclusionsUsers will gain insight into genome mobility and FishPi will help further our understanding of the biological role of piRNAs and their interaction with TEs in a similar way that public databases have improved the access to and the understanding of the role of small RNAs.

evolutionary biology↗

bioRxiv2024

Comparative analysis of Endoxifen, Tamoxifen and Fulvestrant: A Bioinformatics Approach to Uncover Mechanisms of Action in Breast Cancer

Breast cancer remains a significant health challenge, with estrogen receptor positive (ER+) subtypes being particularly prevalent forms of breast cancer. Current anti-estrogen therapies, such as tamoxifen and fulvestrant, have limitations, including partial agonist activity and resistance development, which evidence the need for more potent alternatives. Endoxifen, a metabolite of tamoxifen, has emerged as a promising breast cancer therapeutic candidate due to its superior anti-estrogenic effects and side effect profile. The omics signatures for endoxifen, tamoxifen and fulvestrant, obtained from publicly available datasets, were aggregated and harmonized by means of the PandaOmics platform, a commercially available target-discovery platform using multiple AI engines including generative pretrained transformers. Pathway enrichment analyses provided insight into these agents mechanisms of action (MOA) in breast cancer. The analyses revealed unexpected variances in several key pathways from expected interactions via estrogen-dependent and independent effects. All three drugs downregulated estrogen signaling and cell cycle-related pathways, such as E2F targets, G2-M checkpoints, Myc targets, and mitotic spindle, and stimulated apoptosis. Fulvestrant and tamoxifen activated pro-inflammatory and immune pathways and perturbed epithelial-mesenchymal transition (EMT). Endoxifen perturbed the PI3K/Akt/mTORC1 pathway, pursuant to distinct molecular mechanisms compared to its parent compound, tamoxifen, and fulvestrant. In summary, advanced AI-driven methodologies demonstrate the capacity to analyze multi-omics data in a comparative way to advance the understanding of endocrine therapy mechanisms in breast cancer. This insight into the distinct effects of endoxifen, tamoxifen, and fulvestrant may aid in selecting the most effective therapies for specific indications and in identifying drug-specific biomarkers.

cancer biology↗