Detection of Somatic Mutations with ddPCR from Liquid Biopsy of Colorectal Cancer Patients

Liquid biopsy and cell-free DNA (cfDNA) show great promise in cancer diagnostics. In this study, we designed a custom droplet digital PCR (ddPCR) assay for the quantification and quality control of cfDNA isolated from serum. The assay was validated on a group of locally advanced colorectal cancer (CRC) patients and two control groups-patients with hemorrhoids and healthy individuals. The assay shows a high correlation with Qubit measurement (r = 0.976) but offers a higher dynamic range. Mean concentrations of cfDNA were 12.36 ng/mu L, 5.17 ng/mu L, and 0.29 ng/mu L for CRC, hemorrhoid patients, and healthy controls, respectively. The quality of cfDNA was assessed with the measurement of B-cell DNA contamination. On a subset of CRC patients, we compared the mutation status on KRAS (G12A, G12D, G12V, G13D) and BRAF (V600E) genes in the primary tumor and cfDNA isolated from the serum. A total of 70.6% of primary tumor samples were mutated, and the mean fractional abundance of mutations was 9.50%. The matching serum samples were mutated in 38% cases with an average fractional abundance of 0.23%. We conclude that any decisions based solely on the amount of cfDNA present in patient serum must be interpreted carefully and in the context of co-morbidities. This study explores the potential of ddPCR somatic mutations detection from liquid biopsy as a supplement to tissue biopsy in targeted personalized CRC patient management

Non-coding RNAs in preeclampsia—molecular mechanisms and diagnostic potential

Preeclampsia (PE) is a leading cause of maternal and neonatal morbidity and mortality worldwide. Defects in trophoblast invasion, differentiation of extravillous trophoblasts and spiral artery remodeling are key factors in PE development. Currently there are no predictive biomarkers clinically available for PE. Recent technological advancements empowered transcriptome exploration and led to the discovery of numerous non-coding RNA species of which microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the most investigated. They are implicated in the regulation of numerous cellular functions, and as such are being extensively explored as potential biomarkers for various diseases. Altered expression of numerous lncRNAs and miRNAs in placenta has been related to pathophysiological processes that occur in preeclampsia. In the following text we offer summary of the latest knowledge of the molecular mechanism by which lnRNAs and miRNAs (focusing on the chromosome 19 miRNA cluster (C19MC)) contribute to pathophysiology of PE development and their potential utility as biomarkers of PE, with special focus on sample selection and techniques for the quantification of lncRNAs and miRNAs in maternal circulation

Different approaches in microRNA analysis

MicroRNA might serve as a predictive biomarker for treatment response in stem cell treatment in knee osteoarthritis. Different sample types are going to be collected to enlighten the true biological role. MicroRNA analysis necessitates diverse approaches based on the sample type. In this study, we examined microRNA profiles in plasma samples, synovial fluid, and adipose-derived fat tissue. We conducted a comparative analysis of different microRNA analysis methods to assess the data. The first approach involved a series of steps, including adapter trimming, quality filtering, size filtering, and mapping of all reads to the human reference genome (GRCh38.p12). Subsequently, genome-mapped reads were aligned to known miRNA sequences from miRBase. Reads that did not match miRNAs were subjected to further classification using additional databases, such as RNAcentral. The second pipeline also encompassed adapter trimming, quality filtering, and size filtering. Additionally, it involved collapsing individual reads into repeat sequences, followed by alignment to the mature index of miRBase. Unaligned reads were classified as isomiRs based on their alignment to the hairpin index of miRBase. We processed sequences from three plasma samples, three adipose fat tissue samples, and three synovial fluid samples. Although there were slight variations in microRNA read counts, the average ratio between counts was 0.92 (SD=0.29). Notably, the second pipeline yielded higher read counts compared to the first pipeline. The results obtained from both microRNA bioinformatic pipelines demonstrated similar outcomes, suggesting that the choice of pipeline is unlikely to have a significant impact on the derived biological insights.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

Developing bioinformatics pipeline for processing environmental DNA metabarcoding sequencing data

Environmental DNA (eDNA) is DNA present in an environmental sample, originating from any biological material released from organisms living in that environment. This DNA can be isolated, amplified, sequenced, and analyzed in order to examine the taxonomic richness and abundance of different organism groups in the targeted environment. Methods of eDNA metabarcoding thus offer a unique opportunity to systematically streamline and scale-up regular biological assessments across many different environments of interest. Recently, as a part of the project funded by European structural and investment funds, Labena d.o.o. company established a modern laboratory in Zagreb focused on the research and provision of services in the field of eDNA. In collaboration with the Institute Ruđer Bošković we have been working on developing tests for analysis of water quality based on the eDNA and, as part of the standardization and optimization of sample-to-results eDNA analysis process, we developed a custom bioinformatics pipeline to facilitate efficient and effective eDNA sequencing data analysis. The pipeline was was written in Bash and utilizes several different algorithms to filter, trim, merge, denoise and classify targeted eDNA sequences. Python-based scripts which allow automatically download, filter, and format the data available on various online platforms were included in the pipeline to facilitate the curation of custom reference databases needed for taxonomic classification of targeted organism groups. User-friendly and interactive pipeline report generation, comprised of both wet- and dry-lab step-bystep sample statistics and graphical representations or the main results, is supported using Rmarkdown and Plotly and DataTables libraries. The pipeline is containerized in Docker, allowing for easier environment building and pipeline deployment.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

Single cell 3’ transcriptome profiling

Whole 3’ transcriptome profiling at the single cell level opens up new abilities for researchers to answer complex questions. Thousands of individual cells per sample are Barcoded separately to index the transcriptome of each cell individually. It is done by partitioning thousands of cells into nanoliter-scale Gel Beads-in-emulsion (GEMs), where cells are delivered at a limiting dilution, such that the majority (~90-99%) of generated GEMs contain no cell. The 16 bp 10x Barcode and 12 bp UMI are encoded in Read 1, while the poly(dT) primers are used in this protocol for generating Single Cell 3’ Gene Expression libraries. After GEM generation, copartitioned cells are lysed and reverse transcription (RT) was performed after which all cDNA from single cell share a common Barcode. Full-length cDNA was amplified via PCR to generate sufficient mass for library construction. This is followed by enzymatic fragmentation and size selection to optimize the cDNA amplicon size. Library construction was finished via End Repair, A-tailing, Adaptor Ligation, and PCR. P5, P7, i7 and i5 sample index, and TruSeq Read 2 (read 2 primer sequence) were added. TruSeq Read 1 and TruSeq Read 2 are standard Illumina sequencing primer sites used in paired-end sequencing. The library prepared in this way, containing the P5 and P7 primers, is ready for Illumina amplification.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

OligoPrime

With the increasing number of molecular biology techniques, large numbers of oligonucleotides are frequently involved in individual research projects. Thus, a dedicated electronic oligonucleotide management system is expected to provide several benefits such as increased oligonucleotide traceability, facilitated sharing of oligonucleotides between laboratories, and simplified (bulk) ordering of oligonucleotides. Herein, we describe OligoPrime, an information system for oligonucleotide management, which presents a computational support for all steps in an oligonucleotide lifecycle, namely, from its ordering and storage to its application, and disposal. OligoPrime is easy to use since it is accessible via a web browser and does not require any installation from the end user’s perspective. It allows filtering and search of oligonucleotides by various parameters, which include the exact location of an oligonucleotide, its sequence, and availability. The oligonucleotide database behind the system is shared among the researchers working in the same laboratory or research group. Users might have different roles which define the access permissions and range from students to researchers and primary investigators. Furthermore, OligoPrime is easy to manage and install and is based on open-source software solutions. Its code is freely available at https://github.com/OligoPrime. Moreover, an implementation of OligoPrime, which can be used for testing is available at http://oligoprime.xyz/. To our knowledge, OligoPrime is the only software solution dedicated specifically to oligonucleotide management. We strongly believe that it has a large potential to enhance the transparency of use and to simplify the management of oligonucleotides in academic laboratories and research groups