Bioinformatics Research Articles

Identification and functional characterisation of a locus for target site integration in Fusariumgraminearum

BackgroundFusarium Head Blight (FHB) is a destructive floral disease of different cereal crops. The Ascomycete fungus Fusariumgraminearum (Fg) is one of the main causal agents of FHB in wheat and barley. The role(s) in virulence of Fg genes include genetic studies that involve the transformation of the fungus with different expression cassettes. We have observed in several studies where Fg genes functions were characterised that integration of expression cassettes occurred randomly. Random insertion of a cassette may disrupt gene expression and/or protein functions and hence the overall conclusion of the study. Target site integration (TSI) is an approach that consists of identifying a chromosomal region where the cassette can be inserted. The identification of a suitable locus for TSI in Fg would avert the potential risks of ectopic integration.ResultsHere, we identified a highly conserved intergenic region on chromosome 1 suitable for TSI. We named this intergenic region TSI locus 1. We developed an efficient cloning vector system based on the Golden Gate method to clone different expression cassettes for use in combination with TSI locus 1. We present evidence that integrations in the TSI locus 1 affects neither fungal virulence nor fungal growth under different stress conditions. Integrations at the TSI locus 1 resulted in the expression of different gene fusions. In addition, the activities of Fg native promoters were not altered by integration into the TSI locus 1. We have developed a bespoke bioinformatic pipeline to analyse the existence of ectopic integrations, cassette truncations and tandem insertions of the cassette that may occurred during the transformation process. Finally, we established a protocol to study protein secretion in wheat coleoptiles using confocal microscopy and the TSI locus 1.ConclusionThe TSI locus 1 can be used in Fg and potentially other cereal infecting Fusarium species for diverse studies including promoter activity analysis, protein secretion, protein localisation studies and gene complementation. The bespoke bioinformatic pipeline developed in this work together with PCR amplification of the insert could be an alternative to Southern blotting, the gold standard technique used to identify ectopic integrations, cassette truncations and tandem insertions in fungal transformation.

Exosomal small RNA profiling in first-trimester maternal blood explores early molecular pathways of preterm preeclampsia

IntroductionPreeclampsia (PE) is a severe obstetrical syndrome characterized by new-onset hypertension and proteinuria and it is often associated with fetal intrauterine growth restriction (IUGR). PE leads to long-term health complications, so early diagnosis would be crucial for timely prevention. There are multiple etiologies and subtypes of PE, and this heterogeneity has hindered accurate identification in the presymptomatic phase. Recent investigations have pointed to the potential role of small regulatory RNAs in PE, and these species, which travel in extracellular vesicles (EVs) in the circulation, have raised the possibility of non-invasive diagnostics. The aim of this study was to investigate the behavior of exosomal regulatory small RNAs in the most severe subtype of PE with IUGR.MethodsWe isolated exosomal EVs from first-trimester peripheral blood plasma samples of women who later developed preterm PE with IUGR (n=6) and gestational age-matched healthy controls (n=14). The small RNA content of EVs and their differential expression were determined by next-generation sequencing and further validated by quantitative real-time PCR. We also applied the rigorous exceRpt bioinformatics pipeline for small RNA identification, followed by target verification and Gene Ontology analysis.ResultsOverall, >2700 small RNAs were identified in all samples and, of interest, the majority belonged to the RNA interference (RNAi) pathways. Among the RNAi species, 16 differentially expressed microRNAs were up-regulated in PE, whereas up-regulated and down-regulated members were equally found among the six identified Piwi-associated RNAs. Gene ontology analysis of the predicted small RNA targets showed enrichment of genes in pathways related to immune processes involved in decidualization, placentation and embryonic development, indicating that dysregulation of the induced small RNAs is connected to the impairment of immune pathways in preeclampsia development. Finally, the subsequent validation experiments revealed that the hsa_piR_016658 piRNA is a promising biomarker candidate for preterm PE associated with IUGR.DiscussionOur rigorously designed study in a homogeneous group of patients unraveled small RNAs in circulating maternal exosomes that act on physiological pathways dysregulated in preterm PE with IUGR. Therefore, our small RNA hits are not only suitable biomarker candidates, but the revealed biological pathways may further inform us about the complex pathology of this severe PE subtype.

The genome and transcriptome of the snail Biomphalaria sudanica s.l.: immune gene diversification and highly polymorphic genomic regions in an important African vector of Schistosoma mansoni.

Control and elimination of schistosomiasis is an arduous task, with current strategies proving inadequate to break transmission. Exploration of genetic approaches to interrupt Schistosoma mansoni transmission, the causative agent for human intestinal schistosomiasis in sub-Saharan Africa and South America, has led to genomic research of the snail vector hosts of the genus Biomphalaria. Few complete genomic resources exist, with African Biomphalaria species being particularly underrepresented despite this being where the majority of S. mansoni infections occur. Here we generate and annotate the first genome assembly of Biomphalaria sudanica sensu lato, a species responsible for S. mansoni transmission in lake and marsh habitats of the African Rift Valley. Supported by whole-genome diversity data among five inbred lines, we describe orthologs of immune-relevant gene regions in the South American vector B. glabrata and present a bioinformatic pipeline to identify candidate novel pathogen recognition receptors (PRRs). De novo genome and transcriptome assembly of inbred B. sudanica originating from the shoreline of Lake Victoria (Kisumu, Kenya) resulted in a haploid genome size of ~ 944.2Mb (6,728 fragments, N50 = 1.067Mb), comprising 23,598 genes (BUSCO = 93.6% complete). The B. sudanica genome contains orthologues to all described immune genes/regions tied to protection against S. mansoni in B. glabrata, including the polymorphic transmembrane clusters (PTC1 and PTC2), RADres, and other loci. The B. sudanica PTC2 candidate immune genomic region contained many PRR-like genes across a much wider genomic region than has been shown in B. glabrata, as well as a large inversion between species. High levels of intra-species nucleotide diversity were seen in PTC2, as well as in regions linked to PTC1 and RADres orthologues. Immune related and putative PRR gene families were significantly over-represented in the sub-set of B. sudanica genes determined as hyperdiverse, including high extracellular diversity in transmembrane genes, which could be under pathogen-mediated balancing selection. However, no overall expansion in immunity related genes was seen in African compared to South American lineages. The B. sudanica genome and analyses presented here will facilitate future research in vector immune defense mechanisms against pathogens. This genomic/transcriptomic resource provides necessary data for the future development of molecular snail vector control/surveillance tools, facilitating schistosome transmission interruption mechanisms in Africa.

Next‐generation species delimitation and taxonomy: Implications for biogeography

AbstractAn accurate species‐level taxonomy is paramount for biogeographical research, and conversely, biogeographical data are of importance for species delimitation. We here review recent developments and future perspectives of taxonomy of direct relevance for biogeographers. The understanding that species are independently evolving segments of population‐level lineages, the rise of integrative approaches to delimit such lineages, and the advent of high‐throughput sequencing have considerably renewed the discipline of taxonomy. Using genome‐scale molecular datasets, the extent of admixture across hybrid zones can now be effectively assessed and the evolutionary independence of lineages inferred, leading to more reliable and comparable species delimitation criteria. Substantially divergent but admixing phylogeographical lineages can conveniently be named as subspecies, thus avoiding taxonomic oversplitting and taxonomic inflation. At the same time, comprehensive DNA barcoding and DNA metabarcoding efforts are uncovering an enormous proportion of undiscovered biotic diversity, and we encourage the development of bioinformatic pipelines that combine high‐throughput species discovery and delimitation with diagnosis and scientific naming, to approach a biotic inventory of the globe without abandoning the established Linnaean system.

Detection of resistance to macrolides and fluoroquinolones in Mycoplasma genitalium by targeted next-generation sequencing.

Mycoplasma genitalium is fastidious to culture, and its detection in human clinical specimens relies mainly on molecular methods. Phenotypic determination of antibiotic susceptibility for this bacterium is not a timely or feasible option for most clinical laboratories. This study sought to determine whether next-generation sequencing technologies can effectively be employed in determining genetic mutations associated with drug resistance in M. genitalium samples collected in Aptima Hologic tubes and possibly integrating them into viable workflows in public health laboratories. Following analysis by a custom-designed bioinformatics pipeline, at least one mutation/sample has been identified in 94/98 specimens in at least one of seven loci (macrolides: rrl, rplD, rplV; fluoroquinolones: parC, parE, gyrA, gyrB) described previously to be connected to antibiotic resistance. This method identified a total of 469 single nucleotide polymorphisms (SNPs) (452 mutations): 134 of 23S rRNA SNPs and 318 amino acid mutations: 114 substitutions and 204 synonymous; the turnaround time (sample to analyzed sequence) was typically 3 days. The assays and workflows described in this work demonstrated that the determination of a drug resistance profile for macrolides and fluoroquinolones of M. genitalium samples by using next-generation sequencing in clinical samples is a feasible approach that can be implemented in clinical laboratories, following thorough and extensive validation studies.IMPORTANCEThe mechanisms of drug resistance in Mycoplasma genitalium are complex and involve several genetic loci. The molecular methods for accurately characterizing resistance to fluoroquinolones and macrolides in this organism are often not available or approved for patient use and do not cover all genetic determinants. To this end, we propose a next-generation sequencing-based method with a turnaround time of 3 days that includes the investigation of all drug resistance loci of M. genitalium. Following adaptation, validation, and verification for routine clinical use, assays based on this method may yield molecular results that can be used to guide proper treatment regimens and for surveillance of drug resistance in the general population.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Genomic Analyses of Major SARS-CoV-2 Variants Predicting Multiple Regions of Pathogenic and Transmissive Importance.

The rapid evolution of SARS-CoV-2 has fueled its global proliferation since its discovery in 2019, with several notable variants having been responsible for increases in cases of coronavirus disease 2019 (COVID-19). Analyses of codon bias and usage in these variants between phylogenetic clades or lineages may grant insights into the evolution of SARS-CoV-2 and identify target codons indicative of evolutionary or mutative trends that may prove useful in tracking or defending oneself against emerging strains. We processed a cohort of 120 SARS-CoV-2 genome sequences through a statistical and bioinformatic pipeline to identify codons presenting evidence of selective pressure as well as codon coevolution. We report the identification of two codon sites in the orf8 and N genes demonstrating such evidence with real-world impacts on pathogenicity and transmissivity.

Orchid fruit and root movement analyzed using 2D photographs and a bioinformatics pipeline for processing sequential 3D scans.

Most studies of the movement of orchid fruits and roots during plant development have focused on morphological observations; however, further genetic analysis is required to understand the molecular mechanisms underlying this phenomenon. A precise tool is required to observe these movements and harvest tissue at the correct position and time for transcriptomics research. We utilized three-dimensional (3D) micro-computed tomography (CT) scans to capture the movement of fast-growing Erycina pusilla roots, and built an integrated bioinformatics pipeline to process 3D images into 3D time-lapse videos. To record the movement of slowly developing E. pusilla and Phalaenopsis equestris fruits, two-dimensional (2D) photographs were used. The E. pusilla roots twisted and resupinated multiple times from early development. The first period occurred in the early developmental stage (77-84 days after germination [DAG]) and the subsequent period occurred later in development (140-154 DAG). While E. pusilla fruits twisted 45° from 56-63 days after pollination (DAP), the fruits of P. equestris only began to resupinate a week before dehiscence (133 DAP) and ended a week after dehiscence (161 DAP). Our methods revealed that each orchid root and fruit had an independent direction and degree of torsion from the initial to the final position. Our innovative approaches produced detailed spatial and temporal information on the resupination of roots and fruits during orchid development.

Tumoral and stromal hMENA isoforms impact tertiary lymphoid structure localization in lung cancer and predict immune checkpoint blockade response in patients with cancer

Tertiary Lymphoid Structures (TLS) correlate with positive outcomes in patients with NSCLC and the efficacy of immune checkpoint blockade (ICB) in cancer. The actin regulatory protein hMENA undergoes tissue-specific splicing, producing the epithelial hMENA11a linked to favorable prognosis in early NSCLC, and the mesenchymal hMENAΔv6 found in invasive cancer cells and pro-tumoral cancer-associated fibroblasts (CAFs). This study investigates how hMENA isoforms in tumor cells and CAFs relate to TLS presence, localization and impact on patient outcomes and ICB response. Methods involved RNA-SEQ on NSCLC cells with depleted hMENA isoforms. A retrospective observational study assessed tissues from surgically treated N0 patients with NSCLC, using immunohistochemistry for tumoral and stromal hMENA isoforms, fibronectin, and TLS presence. ICB-treated patient tumors were analyzed using Nanostring nCounter and GeoMx spatial transcriptomics. Multiparametric flow cytometry characterized B cells and tissue-resident memory T cells (TRM). Survival and ICB response were estimated in the cohort and validated using bioinformatics pipelines in different datasets. Findings indicate that hMENA11a in NSCLC cells upregulates the TLS regulator LTβR, decreases fibronectin, and favors CXCL13 production by TRM. Conversely, hMENAΔv6 in CAFs inhibits LTβR-related NF-kB pathway, reduces CXCL13 secretion, and promotes fibronectin production. These patterns are validated in N0 NSCLC tumors, where hMENA11ahigh expression, CAF hMENAΔv6low, and stromal fibronectinlow are associated with intratumoral TLS, linked to memory B cells and predictive of longer survival. The hMENA isoform pattern, fibronectin, and LTβR expression broadly predict ICB response in tumors where TLS indicates an anti-tumor immune response. This study uncovers hMENA alternative splicing as an unexplored contributor to TLS-related Tumor Immune Microenvironment (TIME) and a promising biomarker for clinical outcomes and likely ICB responsiveness in N0 patients with NSCLC. This work is supported by AIRC (IG 19822), ACC (RCR-2019-23669120), CAL.HUB.RIA Ministero Salute PNRR-POS T4, "Ricerca Corrente" granted by the Italian Ministry of Health.

Spatial MS multiomics on clinical prostate cancer tissues.

Mass spectrometry (MS) and MS imaging (MSI) are used extensively for both the spatial and bulk characterization of samples in lipidomics and proteomics workflows. These datasets are typically generated independently due to different requirements for sample preparation. However, modern omics technologies now provide higher sample throughput and deeper molecular coverage, which, in combination with more sophisticated bioinformatic and statistical pipelines, make generating multiomics data from a single sample a reality. In this workflow, we use spatial lipidomics data generated by matrix-assisted laser desorption/ionization MSI (MALDI-MSI) on prostate cancer (PCa) radical prostatectomy cores to guide the definition of tumor and benign tissue regions for laser capture microdissection (LCM) and bottom-up proteomics all on the same sample and using the same mass spectrometer. Accurate region of interest (ROI) mapping was facilitated by the SCiLS region mapper software and dissected regions were analyzed using a dia-PASEF workflow. A total of 5525 unique protein groups were identified from all dissected regions. Lysophosphatidylcholine acyltransferase 1 (LPCAT1), a lipid remodelling enzyme, was significantly enriched in the dissected regions of cancerous epithelium (CE) compared to benign epithelium (BE). The increased abundance of this protein was reflected in the lipidomics data with an increased ion intensity ratio for pairs of phosphatidylcholines (PC) and lysophosphatidylcholines (LPC) in CE compared to BE.

Evaluating the regulatory function of non-coding autism-associated single nucleotide polymorphisms on gene expression in human brain tissue.

Common variants account for most of the estimated heritability associated with autism spectrum disorder (autism). Although several replicable single nucleotide polymorphisms (SNPs) for the condition have been detected using genome-wide association study (GWAS) methodologies, their pathophysiological relevance remains elusive. Examining this is complicated, however, as all detected loci are situated within non-coding regions of the genome. It is therefore likely that they possess roles of regulatory function as opposed to directly affecting gene coding sequences. To bridge the gap between SNP discovery and mechanistic insight, we applied a comprehensive bioinformatic pipeline to functionally annotate autism-associated polymorphisms and their non-coding linkage disequilibrium (i.e., non-randomly associated) partners. We identified 82 DNA variants of probable regulatory function that may contribute to autism pathogenesis. To validate these predictions, we measured the impact of 11 high-confidence candidates and their GWAS linkage disequilibrium partners on gene expression in human brain tissue from Autistic and non-Autistic donors. Although a small number of the surveyed variants exhibited measurable influence on gene expression as determined via quantitative polymerase chain reaction, these did not survive correction for multiple comparisons. Additionally, no significant genotype-by-diagnosis effects were observed for any of the SNP-gene associations. We contend that this may reflect an inability to effectively capture the modest, neurodevelopmental-specific impact of individual variants on biological dysregulation in available post-mortem tissue samples, as well as limitations in the existing autism GWAS data.

Exome sequencing improves the molecular diagnostics of paediatric unexplained neurodevelopmental disorders

BackgroundNeurodevelopmental disorders (NDDs) and/or associated multiple congenital abnormalities (MCAs) represent a genetically heterogeneous group of conditions with an adverse prognosis for the quality of intellectual and social abilities and common daily functioning. The rapid development of exome sequencing (ES) techniques, together with trio-based analysis, nowadays leads to up to 50% diagnostic yield. Therefore, it is considered as the state-of-the-art approach in these diagnoses.ResultsIn our study, we present the results of ES in a cohort of 85 families with 90 children with severe NDDs and MCAs. The interconnection of the in-house bioinformatic pipeline and a unique algorithm for variant prioritization resulted in a diagnostic yield of up to 48.9% (44/90), including rare and novel causative variants (41/90) and intragenic copy-number variations (CNVs) (3/90). Of the total number of 47 causative variants, 53.2% (25/47) were novel, highlighting the clinical benefit of ES for unexplained NDDs. Moreover, trio-based ES was verified as a reliable tool for the detection of rare CNVs, ranging from intragenic exon deletions (GRIN2A, ZC4H2 genes) to a 6-Mb duplication. The functional analysis using PANTHER Gene Ontology confirmed the involvement of genes with causative variants in a wide spectrum of developmental processes and molecular pathways, which form essential structural and functional components of the central nervous system.ConclusionTaken together, we present one of the first ES studies of this scale from the central European region. Based on the high diagnostic yield for paediatric NDDs in this study, 48.9%, we confirm trio-based ES as an effective and reliable first-tier diagnostic test in the genetic evaluation of children with NDDs.

Detecting horizontal gene transfer with metagenomics co-barcoding sequencing.

Horizontal gene transfer (HGT) is the process through which genetic information is transferred between different genomes and that played a crucial role in bacterial evolution. HGT can enable bacteria to rapidly acquire antibiotic resistance and bacteria that have acquired resistance is spreading within the microbiome. Conventional methods of characterizing HGT patterns include short-read metagenomic sequencing (short-reads mNGS), long-read sequencing, and single-cell sequencing. These approaches present several limitations, such as short-read fragments, high amounts of input DNA, and sequencing costs, respectively. Here, we attempt to circumvent present limitations to detect HGT by developing a metagenomics co-barcode sequencing workflow (MECOS) and applying it to the human and mouse gut microbiomes. In addition to that, we have over 10-fold increased contig length compared to short-reads mNGS; we also obtained exceeding 30 million paired reads with co-barcode information. Applying the novel bioinformatic pipeline, we integrated this co-barcoding information and the context information from long reads, and observed over 50-fold HGT events after we corrected the potential wrong HGT events. Specifically, we detected approximately 3,000 HGT blocks in individual samples, encompassing ~6,000 genes and ~100 taxonomic groups, including loci conferring tetracycline resistance through ribosomal protection. MECOS provides a valuable tool for investigating HGT and advance our understanding on the evolution of natural microbial communities within hosts.IMPORTANCEIn this study, to better identify horizontal gene transfer (HGT) in individual samples, we introduce a new co-barcoding sequencing system called metagenomics co-barcoding sequencing (MECOS), which has three significant improvements: (i) long DNA fragment extraction, (ii) a special transposome insertion, (iii) hybridization of DNA to barcode beads, and (4) an integrated bioinformatic pipeline. Using our approach, we have over 10-fold increased contig length compared to short-reads mNGS, and observed over 50-fold HGT events after we corrected the potential wrong HGT events. Our results indicate the presence of approximately 3,000 HGT blocks, involving roughly 6,000 genes and 100 taxonomic groups in individual samples. Notably, these HGT events are predominantly enriched in genes that confer tetracycline resistance via ribosomal protection. MECOS is a useful tool for investigating HGT and the evolution of natural microbial communities within hosts, thereby advancing our understanding of microbial ecology and evolution.

Deep mining of antibody phage-display selections using Oxford Nanopore Technologies and Dual Unique Molecular Identifiers

Antibody phage-display technology identifies antibody-antigen interactions through multiple panning rounds, but traditional screening gives no information on enrichment or diversity throughout the process. This results in the loss of valuable binders. Next Generation Sequencing can overcome this problem. We introduce a high accuracy long-read sequencing method based on the recent Oxford Nanopore Technologies (ONT) Q20+ chemistry in combination with dual unique molecular identifiers (UMIs) and an optimized bioinformatic analysis pipeline to monitor the selections. We identified binders from two single-domain antibody libraries selected against a model protein. Traditional colony-picking was compared with our ONT-UMI method. ONT-UMI enabled monitoring of diversity and enrichment before and after each selection round. By combining phage antibody selections with ONT-UMIs, deep mining of output selections is possible. The approach provides an alternative to traditional screening, enabling diversity quantification after each selection round and rare binder recovery, even when the dominating binder was >99% abundant. Moreover, it can give insights on binding motifs for further affinity maturation and specificity optimizations. Our results demonstrate a platform for future data guided selection strategies.

Bioinformatics and Systems Biology Approaches to Identify the Synergistic Effects of Alcohol Use Disorder on the Progression of Neurological Diseases

Clinical investigations showed that individuals with Alcohol Use Disorder (AUD) have worse Neurological Disease (ND) development, pointing to possible pathogenic relationships between AUD and NDs. It remains difficult to identify risk factors that are predisposing between AUD and NDs. In order to fix these issues, we created the bioinformatics pipeline and network-based approaches for employing unbiased methods to discover genes abnormally stated in both AUD and NDs and to pinpoint some of the common molecular pathways that might underlie AUD and ND interaction. We found 100 differentially expressed genes (DEGs) in both the AUD and ND patient’s tissue samples. The most important Gene Ontology (GO) terms and metabolic pathways, including positive control of cytotoxicity caused by T cells, proinflammatory responses, antigen processing and presentation, and platelet-triggered interactions with vascular and circulating cell pathways were then extracted using the overlapped DEGs. Protein-protein interaction analysis was used to identify hub proteins, including CCL2, IL1B, TH, MYCN, HLA-DRB1, SLC17A7, and HNF4A, in the pathways that have been reported as playing a function in these disorders. We determined several TFs (HNF4A, C4A, HLA-B, SNCA, HLA-DMB, SLC17A7, HLA-DRB1, HLA-C, HLA-A, and HLA-DPB1) and potential miRNAs (hsa-mir-34a-5p, hsa-mir-34c-5p, hsa-mir-449a, hsa-mir-155-5p, and hsa-mir-1-3p) were crucial for regulating the expression of AUD and ND which could serve as prospective targets for treatment. Our methodologies discovered unique putative biomarkers that point to the interaction between AUD and various neurological disorders, as well as pathways that could 1 day be the focus of therapeutic intervention.

Computational validation of clonal and subclonal copy number alterations from bulk tumor sequencing using CNAqc

Copy number alterations (CNAs) are among the most important genetic events in cancer, but their detection from sequencing data is challenging because of unknown sample purity, tumor ploidy, and general intra-tumor heterogeneity. Here, we present CNAqc, an evolution-inspired method to perform the computational validation of clonal and subclonal CNAs detected from bulk DNA sequencing. CNAqc is validated using single-cell data and simulations, is applied to over 4000 TCGA and PCAWG samples, and is incorporated into the validation process for the clinically accredited bioinformatics pipeline at Genomics England. CNAqc is designed to support automated quality control procedures for tumor somatic data validation.

Alzheimer DataLENS: An Open Data Analytics Portal for Alzheimer's Disease Research.

Recent Alzheimer's disease (AD) discoveries are increasingly based on studies from a variety of omics technologies on large cohorts. Currently, there is no easily accessible resource for neuroscientists to browse, query, and visualize these complex datasets in a harmonized manner. Create an online portal of public omics datasets for AD research. We developed Alzheimer DataLENS, a web-based portal, using the R Shiny platform to query and visualize publicly available transcriptomics and genetics studies of AD on human cohorts. To ensure consistent representation of AD findings, all datasets were processed through a uniform bioinformatics pipeline. Alzheimer DataLENS currently houses 2 single-nucleus RNA sequencing datasets, over 30 bulk RNA sequencing datasets from 19 brain regions and 3 cohorts, and 2 genome-wide association studies (GWAS). Available visualizations for single-nucleus data include bubble plots, heatmaps, and UMAP plots; for bulk expression data include box plots and heatmaps; for pathways include protein-protein interaction network plots; and for GWAS results include Manhattan plots. Alzheimer DataLENS also links to two other knowledge resources: the AD Progression Atlas and the Astrocyte Atlas. Alzheimer DataLENS is a valuable resource for investigators to quickly and systematically explore omics datasets and is freely accessible at https://alzdatalens.partners.org.

Pseudogenomic insights into the evolution of Mycobacterium ulcerans.

Buruli ulcer (BU) disease, caused by Mycobacterium ulcerans (MU), and characterized by necrotic ulcers is still a health problem in Africa and Australia. The genome of the bacterium has several pseudogenes due to recent evolutionary events and environmental pressures. Pseudogenes are genetic elements regarded as nonessential in bacteria, however, they are less studied due to limited available tools to provide understanding of their evolution and roles in MU pathogenicity. This study developed a bioinformatic pipeline to profile the pseudogenomes of sequenced MU clinical isolates from different countries. One hundred and seventy-two MU genomes analyzed revealed that pseudogenomes of African strains corresponded to the two African lineages 1 and 2. Pseudogenomes were lineage and location specific and African lineage 1 was further divided into A and B. Lineage 2 had less relaxation in positive selection than lineage 1 which may signify different evolutionary points. Based on the Gil-Latorre model, African MU strains may be in the latter stages of evolutionary adaption and are adapting to an environment rich in metabolic resources with a lower temperature and decreased UV radiation. The environment fosters oxidative metabolism and MU may be less reliant on some secondary metabolites. In-house pseudogenomes from Ghana and Cote d'Ivoire were different from other African strains, however, they were identified as African strains. Our bioinformatic pipeline provides pseudogenomic insights to complement other whole genome analyses, providing a better view of the evolution of the genome of MU and suggest an adaptation model which is important in understanding transmission. MU pseudogene profiles vary based on lineage and country, and an apparent reduction in insertion sequences used for the detection of MU which may adversely affect the sensitivity of diagnosis.

Computer aided aptamer selection for fabrication of electrochemical sensor to detect Aflatoxin B1

Aflatoxin B1 (AFB1) is a naturally occurring toxin produced by Aspergillus flavus and Aspergillus parasiticus. The AFB1 is classified as a potent carcinogen and poses significant health risks both to humans and animals. Early detection of the toxin in post-harvest agricultural products will save lives and promote healthy food production. In this study, stratified docking approach was utilized to screen and identify potential aptamers that can bind to AFB1. ssDNA sequences were acquired from the Mendeley dataset, secondary and tertiary structures were predicted through a series of bioinformatics pipelines. Further, the final DNA tertiary structures were minimized and SiteMap algorithm was used to probe and locate binding cavities. According to the final XP docking result, a 34 nt sequence (5′-ATCCTGTGAGGAATGCTCATGCATAGCAAGGGCT-3′) aptamer with a docking score of −5.959 kcal/mol was considered for 200 ns MD Simulation. Finally, the screened DNA-aptamer was immobilized over the gold surface based on Au-S chemistry and utilized for the detection of AFB1. The fabricated DNA-aptamer electrode demonstrated a good analytical performance including wide linear range (1.0 to 1000 ng L−1), detection limit (1.0 ng L−1), high stability, and reproducibility. Communicated by Ramaswamy H. Sarma

Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.

The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational approach or a golden standard for comparison. Hence, benchmarking the different tools depends highly on the input data, indicating that overfitting is still a massive problem. One of the solutions is to limit the scope and usage of specific tools. However, such limitations force researchers to walk on a tightrope between creating and using high-quality tools for a specific purpose and describing the complex alterations driving cancer. While the knowledge of cancer development increases daily, many bioinformatic pipelines rely on single nucleotide variants or alterations in a vacuum without accounting for cellular compartments, mutational burden or disease progression. Even within bioinformatics and computational cancer biology, the research fields work in silos, risking overlooking potential synergies or breakthroughs. Here, we provide an overview of databases and datasets for building or testing predictive cancer driver tools. Furthermore, we introduce predictive tools for driver genes, driver mutations, and the impact of these based on structural analysis. Additionally, we suggest and recommend directions in the field to avoid silo-research, moving towards integrative frameworks.