Biology subjects

Trypsteen, W.

Publications and source records attributed to Trypsteen, W..

7 recordsLinked to original sources

bioRxiv2026

Introducing the digital PCR data essentials standard to harmonize data structure for clinical and research use

Digital PCR (dPCR) is a powerful technology for absolute quantification of nucleic acids, valued for its accuracy, sensitivity, and repeatability. Yet, the commercialization of different instruments with proprietary software has introduced challenges to data analysis, interoperability, and comparability. Therefore, we present the Digital PCR Data Essentials Standard (DDES) - a lightweight, human- and machine-readable, and cross-platform data standard developed in collaboration with the dPCR community. The standard consists of three file types designed to enable both manual inspection and automated analysis: (i) a main file summarizing experiment and reaction-level (meta-)data; (ii) an assay file describing targets and detection chemistry, and (iii) intensity files capturing partition-level raw fluorescence data per reaction. DDES supports a wide range of current dPCR applications, including singleplex and multiplex assays, endpoint and real-time readouts, and will be curated to implement future dPCR developments. By harmonizing the data structure, DDES lays out the foundation for FAIR dPCR data practices and supports improved software compatibility, collaborative and reproducible research, and future dPCR data repositories.

bioinformatics↗

bioRxiv2024

Coordinated regulation by lncRNAs results in tight lncRNA-target couplings

The determination of long non-coding RNA (lncRNA) function is a major challenge in RNA biology with applications to basic, translational, and medical research [1-7]. Our efforts to improve the accuracy of lncRNA-target inference identified lncRNAs that coordinately regulate both the transcriptional and post-transcriptional processing of their targets. Namely, these lncRNAs may regulate the transcription of their target and chaperone the resulting message until its translation, leading to tightly coupled lncRNA and target abundance. Our analysis suggested that hundreds of cancer genes are coordinately and tightly regulated by lncRNAs and that this unexplored regulatory paradigm may propagate the effects of non-coding alterations to effectively dysregulate gene expression programs. As a proof-of-principle we studied the regulation of DICER1 [8, 9]--a cancer gene that controls microRNA biogenesis--by the lncRNA ZFAS1, showing that ZFAS1 activates DICER1 transcription and blocks its post-transcriptional repression to phenomimic and regulate DICER1 and its target microRNAs.

bioinformatics↗

bioRxiv2023

Flexible Methods for Standard Error Calculation in digital PCR Experiments

Digital PCR (dPCR) is a highly accurate and precise technique for the quantification of target nucleic acid(s) in a biological sample. This digital quantification relies on the binomial or Poisson distribution to estimate the amount of target molecules based on positive and negative partitions. However, the implementation of these distributions require adherence to underlying assumptions that are often neglected, leading to a suboptimal (too optimistic) variance estimation of the target concentration, especially when considering the multiple sources of variation in experimental dPCR setups. Moreover, these parametric methods cannot be easily used for downstream statistical inference when more advanced analysis are required, such as for copy number variation. We evaluated the performance of three new statistical methods (BootsVar, NonPVar, BinomVar) in both simulations and real-life datasets for target and variance estimation in dPCR setups while taking into account a combination of commonly observed sources of experimental variability that can interfere with the underlying assumptions of the current parametric methods. The results demonstrate the capability of the new methods for variance estimation and present a more accurate reflection of the true variability over the classical binomial approach. In addition, these statistical methods are flexible and generic in the way that they work well for the variance estimation of non-linear statistics that work with ratios (e.g. CNV) and for multiplex dPCR setups. In this study, we provide guidelines when to use the binomial-assumption based methods and when the non-parametric one is better to achieve more accurate variance estimates.

bioinformatics↗

bioRxiv2023

Integrative assessment of total and intact HIV-1 reservoir by a five-region multiplexed Rainbow digital PCR assay

Persistent latent reservoirs of intact HIV-1 proviruses, capable of rebounding despite suppressive ART, hinder efforts towards an HIV-1 cure. Hence, assays specifically quantifying intact proviruses are crucial to assess the impact of curative interventions. Clinical trials have utilized two recent assays: intact proviral DNA assay (IPDA) and Q4PCR. While IPDA is more sensitive due to amplifying short fragments, it may overestimate intact fractions by relying only on two small regions. Q4PCR is sequencing-based and its performance might be subjected to bias against full-length proviruses. Leveraging digital PCR (dPCR) advancements, we developed the Rainbow 5-plex proviral HIV-1 DNA assay, assessing it with standard materials and samples from 69 PLWH. The Rainbow assay proved equally sensitive but more specific than IPDA, is not subjected to bias against full-length proviruses, enabling high-throughput quantification of total and intact reservoir size. This innovation offers potential for targeted evaluation and monitoring of rebound-competent reservoirs, contributing to HIV-1 management and cure strategies. TeaserThe 5 color HIV-1 Rainbow digital PCR assay offers a multi-level view on the HIV reservoir in one snapshot reaction.

molecular biology↗

bioRxiv2021

A 3'-end capture sequencing method for high-throughput targeted gene expression profiling

Molecular phenotyping through shallow 3-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long non-coding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3-end library preparation with 3-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3-end RNA-sequencing, 3-end capture sequencing resulted in a more than 100-fold enrichment of target gene abundance while conserving relative inter-gene and inter-sample abundances. 3-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.

genomics↗

bioRxiv2020

Recurrent chromosomal imbalances provide selective advantage to human embryonic stem cells under enhanced replicative stress conditions

Human embryonic stem cells (hESCs) and embryonal tumors share a number of common features including a compromised G1/S checkpoint. Consequently, these rapidly dividing hESCs and cancer cells undergo elevated levels of replicative stress which is known to induce genomic instability causing chromosomal imbalances. In this context, it is of interest that long-term in vitro cultured hESCs exhibit a remarkable high incidence of segmental DNA copy number gains, some of which are also highly recurrent in certain malignancies such as 17q gain (17q+). The selective advantage of DNA copy number changes in these cells has been attributed to several underlying processes including enhanced proliferation. We hypothesized that these recurrent chromosomal imbalances become rapidly embedded in the cultured hESCs through a replicative stress driven Darwinian selection process. To this end, we compared the effect of hydroxyurea induced replicative stress versus normal growth conditions in an equally-mixed cell population of isogenic euploid and 17q+ hESCs. We could show that 17q+ hESCs rapidly overtook normal hESCs. Our data suggest that recurrent chromosomal segmental gains provide a proliferative advantage to hESCs under increased replicative stress, a process that may also explain the highly recurrent nature of certain imbalances in cancer.

cancer biology↗

bioRxiv2020

When DNA gets in the way in RNA-seq experiments, a sequel

Using a newly developed method dubbed SILVER-Seq--enabling extracellular RNA sequencing (exRNA-seq) directly from a small volume of human serum or plasma-- Yan et al. recently reported in Current Biology a potential exRNA biomarker for the early diagnosis of Alzheimers disease [1]. After the publication of the initial paper describing the SILVER-Seq method [2], we reported our concern regarding potential DNA contamination in their datasets [3]. Although the authors replied they were able to successfully treat RNA samples with DNase to avoid such contamination, they did not address our observations of the majority of reads without evidence of being derived from RNA, nor documented verified absence of DNA after DNase treatment [4]. To assess whether the newly data generated may suffer from DNA contamination, we downloaded the publicly available sequencing data and evaluated two quality control metrics (i.e., fraction of exonic and splice reads), which were not reported in the paper. We found that both quality metrics were much lower than expected for RNA-seq data (6.28% exonic and 0.478% splice reads), in line with our previous findings on the first SILVER-Seq paper. These observations suggest the data and results presented by Yan et al. are affected by DNA contamination, an issue that may be inherent to the SILVER-Seq technology.

molecular biology↗