Biology subjects

Moos, P.

Publications and source records attributed to Moos, P..

4 recordsLinked to original sources

bioRxiv2026

DS5: An Open-Source Framework for Standardized High-Throughput Drug Screening Data Storage, Analysis, and Drug Prioritization

Background. High-throughput drug screening (HTS) is increasingly used in precision oncology across cell lines, patient-derived models such as organoids (PDO) and xenograft organoids (PDxO), and ex vivo patient samples, with multiple active clinical trials incorporating HTS for individualizing treatment. Yet HTS efforts predominantly rely on ad hoc, spreadsheet-based workflows, with no standardized infrastructure for storing, analyzing, and comparing screens across patients, cohorts, or institutions, limiting reproducibility and slowing clinical data exchange. Existing tools address isolated pieces of the workflow, handling either data management or analysis and visualization, but none integrate standardized storage, reproducible dose-response analysis, individualized drug prioritization, and clinician and molecular tumor board friendly reporting in a single open-source framework. Results. We present DS5, an open-source Python framework that operates on an HDF5-based DS5 file format that unifies standardized storage, quality control, dose-response analysis, cohort-level drug prioritization, and automated reporting in a single lightweight package. DS5 enforces raw-data immutability, integrates RxNorm-based drug name standardization, and scales from small clinical cohorts to large pharmacogenomics datasets on a standard laptop. We validated DS5 against two public benchmarks spanning over 428,000 drug, cell line pairs, recovering published LN IC50 values from GDSC2 (Pearson r = 0.973) and Emax values from CTRP (r = 0.961). Using a published breast cancer PDxO dataset (45 compounds by 16 models), we reproduced GR-based profiles via a custom-metric extension and used DS5's cohort-level prioritization to predict in vivo tumor response with ROC AUC = 0.907 across 30 drug PDX pairs. Finally, we demonstrate the utilities of DS5 in an ongoing pediatric brain tumor precision oncology initiative, where its cohort-normalized drug rankings and automated reports directly support molecular tumor board discussions. Conclusion. DS5 provides the cancer basic and translational research community with a standardized file format and reproducible computational analysis methods to support functional drug screening experiments; and its reporting features facilitate bridging raw drug screening measurements to translational decisions. DS5 is released open-source under the permissible MIT license.

bioinformatics↗

bioRxiv2026

Single-nucleus transcriptomics reveal stress-related prefrontal activation in Tourette disorder

Tourette disorder (TD) is a neurodevelopmental condition with a robust genetic basis, characterized by multiple motor and vocal tics. Tics arise from dysfunction within cortico-striatal-thalamo-cortical circuits, with pathological evidence largely implicating striatal interneuron deficits and microglial activation. Recently, the largest genome-wide association study (GWAS) meta-analysis of TD identified polygenic risk enrichment in Brodmann area 9 (BA9), corresponding to the dorsolateral prefrontal cortex (DLPFC), a region implicated in executive control and tic suppression. However, the molecular landscape of BA9 in TD remains unexplored. Here, we performed single-nucleus RNA sequencing of postmortem BA9 from five males with TD and five matched controls, yielding 72,340 nuclei across neuronal and glial populations. While cell-type proportions were preserved, transcriptional remodeling was pervasive. In particular, biosynthetic and translational programs were upregulated across microglia, interneurons, oligodendrocytes, and superficial- and middle-layer excitatory neurons. Most cell types showed enrichment for glucocorticoid-responsive and immediate early gene modules consistent with stress-associated transcriptional activation. Finally, cross-regional comparison with striatal datasets revealed conservation of microglial and oligodendrocyte programs. These findings point to extensive transcriptional reprogramming in the DLPFC of individuals with TD, characterized by stress-associated activation, most strongly in oligodendrocytes and neurons.

neuroscience↗

bioRxiv2024

Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotype and phenotype in chronic lymphocytic leukemia

Brutons tyrosine kinase (BTK) inhibitors are effective for the treatment of chronic lymphocytic leukemia (CLL) due to BTKs role in B cell survival and proliferation. Treatment resistance is most commonly caused by the emergence of the hallmark BTKC481S mutation that inhibits drug binding. In this study, we aimed to investigate whether the presence of additional CLL driver mutations in cancer subclones harboring a BTKC481S mutation accelerates subclone expansion. In addition, we sought to determine whether BTK-mutated subclones exhibit distinct transcriptomic behavior when compared to other cancer subclones. To achieve these goals, we employ our recently published method (Qiao et al. 2024) that combines bulk DNA sequencing and single-cell RNA sequencing (scRNA-seq) data to genotype individual cells for the presence or absence of subclone-defining mutations. While the most common approach for scRNA-seq includes short-read sequencing, transcript coverage is limited due to the vast majority of the reads being concentrated at the priming end of the transcript. Here, we utilized MAS-seq, a long-read scRNAseq technology, to substantially increase transcript coverage across the entire length of the transcripts and expand the set of informative mutations to link cells to cancer subclones in six CLL patients who acquired BTKC481S mutations during BTK inhibitor treatment. We found that BTK-mutated subclones often acquire additional mutations in CLL driver genes, leading to faster subclone proliferation. When examining subclone-specific gene expression, we found that in one patient, BTK-mutated subclones are transcriptionally distinct from the rest of the malignant B cell population with an overexpression of CLL-relevant genes.

genomics↗

bioRxiv2021

HIV-1 provirus transcription and translation in macrophages differs from macrophages containing pre-integrated cDNA complexes and requires E2F transcriptional programs

HIV-1 cDNA pre-integration complexes have been shown to persist for weeks in macrophages and to be transcriptionally active. Early and late gene transcripts are produced, along with some viral proteins, yet whole virus is not. While previous work has focused on the transcription and translation of HIV-1 genes; our understanding of cellular milieu that accompanies viral production is incomplete. We have used an in vitro system to model HIV-1 infection of macrophages, and single cell RNA sequencing (scRNA-seq) to compare the transcriptomes of uninfected cells, cells harboring pre-integration HIV-1 complexes (PIC) and those containing integrated provirus and actively making late HIV proteins. These are also compared to control cells, not exposed to virus. Several observations provide new perspective on the effects of HIV-1 transcription from pre-integrated cDNA versus from integrated provirus. First, HIV-1 transcript levels do not necessarily correlate with virus production, cells harboring PIC cDNA have transcript loads comparable to cells transcribing from provirus and making p24, mCherry, and vpu proteins. Second, all HIV-1 transcripts are easily detectable in abundance from PIC cDNA transcription, as is the case with cells transcribing from provirus, although the frequency of PIC cells with detectable gag-pol, tat, env, and nef transcripts is higher than the corresponding frequencies observed for "Provirus cells". Third, the background transcriptomes of cells harboring pre- integrated HIV-1 cDNA are not otherwise detectably altered from cells not containing any HIV- 1 transcript. Fourth, integration and production of p24, mCherry, and Vpu proteins is accompanied by a switch from transcriptomes characterized by NFkB and AP-1 promoted transcription to a transcriptome characterized by E2F family transcription products. While some of these observations may seem heretical, single cell analysis provides a more nuanced understanding of PIC cDNA transcription and the transcriptomic changes that support HIV-1 protein production from integrated provirus. Author SummarySingle cell analysis is able to distinguish between HIV-1 infected macrophage cells that are transcribing pre-integrated HIV-1 cDNA and those transcribing HIV-1 provirus. Only cells transcribing HIV-1 provirus are making p24, marker mCherry and Vpu proteins, which corresponds with a change in the host cells background transcriptome from one expressing viral restriction and immunological response genes to one that is expressing genes associated with cell replication and oxidative phosphorylation.

microbiology↗