Biology subjects

Schroth, G. P.

Publications and source records attributed to Schroth, G. P..

9 recordsLinked to original sources

bioRxiv2026

CellCage™ Technology Enables High-throughput Isolation of Defined Cell Combinations to Resolve the Determinants of CAR-T mediated Cytotoxicity

Understanding the cellular determinants of CAR-T cell-mediated cytotoxicity at the single-cell level remains a critical challenge in developing effective cellular immunotherapies. Conventional bulk co-culture assays provide only population-level measurements of cytotoxic activity and cannot resolve the functional heterogeneity of individual effector-target interactions. Here, we demonstrate the Cellanome platform, which enables the formation of CellCage Enclosures (CCEs) through spatially controlled photopolymerization, as a tool for high-resolution, high-throughput characterization of CAR-T cell-mediated cytotoxicity. By isolating defined effector-target combinations within individual CCEs and coupling encapsulation with longitudinal time-lapse imaging and automated image analysis, we resolve cytotoxic activity across thousands of individually tracked CCEs. Using anti-CD19 CAR-T effectors and NALM6-GFP targets, we show that individual CD8+ CAR-T effectors exhibit substantial functional heterogeneity, with serial killing capacity, effector-target contact dynamics, and intrinsic motility each independently correlating with cytotoxic potency. Cytotoxic efficacy scaled positively with effector number, and CD4+ T helper cells augmented CD8+-mediated killing in a dose-dependent manner, providing direct evidence for cooperative T cell behavior during tumor cell clearance. Extending the platform to a solid tumor model using AIC100 anti-ICAM-1 CAR-T cells and HeLa-GFP targets, we show that individual AIC100 effectors are insufficient to mediate effective killing, while multi-effector CCEs exhibit robust cytotoxicity scaling with effector abundance and CD4+:CD8+ composition. These data establish the Cellanome platform as a broadly applicable system for dissecting the determinants of CAR-T cell cytotoxicity at single-cell resolution, with direct translational relevance to the optimization of cellular immunotherapy.

immunology↗

bioRxiv2022

Rational probe design for efficient rRNA depletion and improved metatranscriptomic analysis of human microbiomes

BackgroundThe microbiota that colonize the human gut and other tissues are dynamic, varying both in composition and functional state between individuals and over time. In studying the function of the human microbiome and the mechanisms of microbiota-mediated phenotypes, gene expression measurements provide additional insights to DNA-based measurements of microbiome composition. However, efficient and unbiased removal of microbial ribosomal RNA (rRNA) presents a barrier to acquiring metatranscriptomic data, as rRNA typically accounts >90% of total RNA in microbial cells. ResultsHere we describe a probe set that achieves efficient enzymatic rRNA removal of complex human-associated microbial communities. We demonstrate that the custom probe set can be further refined through an iterative design process to efficiently deplete rRNA from a range of human microbiome samples, including adult and infant gut, as well as oral and vaginal communities. Using synthetic nucleic acid spike-ins, we show that the rRNA depletion process does not introduce substantial quantitative error in the resulting gene expression profiles. Successful rRNA depletion allows for efficient characterization of taxonomic and functional profiles, including during the development of the human gut microbiome. ConclusionsThe pan-human microbiome enzymatic rRNA depletion probes described here provide a powerful tool for studying the transcriptional dynamics and function of the human microbiome.

genomics↗

bioRxiv2022

Evaluation of an optimized protocol and Illumina ARTIC V4 primer pool for sequencing of SARS-CoV-2 using COVIDSeq™ and DRAGEN™ COVID Lineage App workflow

Next-Generation Sequencing based genomic surveillance has been widely implemented for identification and tracking of emerging SARS-CoV-2 variants to guide the Public Health response to the COVID-19 pandemic. Amplicon-based assays, such as the Illumina(R) COVIDSeq Test (RUO) and COVIDSeq Assay (RUO), enable scalable sequencing of SARS-CoV-2, leveraging V3 and V4 primer designs from the ARTIC community and DRAGEN COVID Lineage App analysis available on Illumina BaseSpace. We report here a comparison of COVIDSeq performance for SARS-CoV-2 genome reporting using the ARTIC V3 based primer pool (including primers for human control genes) that is provided with the COVIDSeq kit versus the ARTIC V4 based Illumina COVIDSeq V4 primer pool, using an optimized protocol and DRAGEN COVID Lineage App analysis. The data indicates that both primer pools enable robust reporting of SARS-CoV-2 variants. The Illumina COVIDSeq V4 primer pool has superior performance for SARS-CoV-2 genome reporting, particularly in samples with low virus load, and is therefore the recommended primer pool for genomic surveillance of SARS-CoV-2 for research use using COVIDSeq.

genomics↗

bioRxiv2021

Performance of RNA purification kits and blood collection tubes in the Extracellular RNA Quality Control (exRNAQC) study

The use of blood-based extracellular RNA (cell-free RNA; exRNA) as clinical biomarker requires the implementation of a validated procedure for sample collection, processing, and profiling. So far, no study has systematically addressed the pre-analytical variables affecting transcriptome analysis of exRNAs. In the exRNAQC study, we evaluated ten blood collection tubes, three time intervals between blood draw and downstream processing, and eight RNA purification methods using the supplier-specified minimum and maximum biofluid input volumes. The impact of these pre-analytics on deep transcriptome profiling of both small and messenger RNA from healthy donors plasma or serum was assessed for each pre-analytical variable separately and for interactions between a selected set of pre-analytics, resulting in 456 extracellular transcriptomes. Making use of 189 synthetic spike-in RNAs, the processing and analysis workflow was controlled. When comparing blood collection tubes, so-called preservation tubes do not stabilize exRNA well, and result in variable RNA concentration and sensitivity (i.e., the number of detected RNAs) over time, as well as compromised reproducibility. We also document large differences in RNA purification kit performance in terms of sensitivity, reproducibility, and observed transcriptome complexity, and demonstrate interactions between specific blood collection tubes, purification kits and time intervals. Our results are summarized in 11 performance metrics that enable an informed selection of the most optimal sample processing workflow for a given experiment. In conclusion, we put forward robust quality control metrics for exRNA quantification methods with validated standard operating procedures (SOPs), representing paramount groundwork for future exRNA-based precision medicine applications.

genomics↗

bioRxiv2020

Multi-Platform Assessment of DNA Sequencing Performance using Human and Bacterial Reference Genomes in the ABRF Next-Generation Sequencing Study

Massively parallel DNA sequencing is a critical tool for genomics research and clinical diagnostics. Here, we describe the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Phase II Study to measure quality and reproducibility of DNA sequencing. Replicates of human and bacterial reference DNA samples were generated across multiple sequencing platforms, including well-established technologies such as Illumina, ThermoFisher Ion Torrent, and Pacific Biosciences, as well as emerging technologies such as BGI, Genapsys, and Oxford Nanopore. A total of 202 datasets were generated to investigate the performance of a total of 16 sequencing platforms, including mappability of reads, coverage and error rates in difficult genomic regions, and detection of small-scale polymorphisms and large-scale structural variants. This study provides a comprehensive baseline resource for continual benchmarking as chemistries, methods, and platforms evolve for DNA sequencing.

genomics↗

bioRxiv2019

Charting extracellular transcriptomes in The Human Biofluid RNA Atlas

Extracellular RNAs present in biofluids have emerged as potential biomarkers for disease. Where most studies focus on plasma or serum, other biofluids may contain more informative RNA molecules, depending on the type of disease. Here, we present an unprecedented atlas of messenger, circular and small RNA transcriptomes of a comprehensive collection of 20 different human biofluids. By means of synthetic spike-in controls, we compared RNA content across biofluids, revealing a more than 10 000-fold difference in RNA concentration. The circular RNA fraction is increased in nearly all biofluids compared to tissues. Each biofluid transcriptome is enriched for RNA molecules derived from specific tissues and cell types. In addition, a subset of biofluids, including stool, sweat, saliva and sputum, contains high levels of bacterial RNAs. Our atlas enables a more informed selection of the most relevant biofluid to monitor particular diseases. To verify the biomarker potential in these biofluids, four validation cohorts representing a broad spectrum of diseases were profiled, revealing numerous differential RNAs between case and control subjects. Taken together, our results reveal novel insights in the RNA content of human biofluids and may serve as a valuable resource for future biomarker studies. All spike-normalized data is publicly available in the R2 web portal and serve as a basis to further explore the RNA content in biofluids.

genomics↗

bioRxiv2019

The RNA Atlas, a single nucleotide resolution map of the human transcriptome

The human transcriptome consists of various RNA biotypes including multiple types of non-coding RNAs (ncRNAs). Current ncRNA compendia remain incomplete partially because they are almost exclusively derived from the interrogation of small- and polyadenylated RNAs. Here, we present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogeneous collection of nearly 300 human tissues and cell lines. We report on thousands of novel RNA species across all major RNA biotypes, including a hitherto poorly-cataloged class of non-polyadenylated single-exon long non-coding RNAs. In addition, we exploit intron abundance estimates from total RNA-sequencing to test and verify functional regulation by novel non-coding RNAs. Our study represents a substantial expansion of the current catalogue of human ncRNAs and their regulatory interactions. All data, analyses, and results are available in the R2 web portal and serve as a basis to further explore RNA biology and function.

genetics↗

bioRxiv2019

Integrated RNA and metabolite profiling of urine liquid biopsies for prostate cancer biomarker discovery

Sensitive and specific diagnostic and prognostic biomarkers for prostate cancer (PCa) are urgently needed. Urine samples are a non-invasive means to obtain abundant and readily accessible \"liquid biopsies\". Herein we used urine liquid biopsies to identify and characterize a novel group of urine-enriched RNAs and metabolites in PCa patients and normal individuals with or without benign prostatic disease. Differentially expressed RNAs were identified in urine samples by deep sequencing and metabolites in urine were measured by mass spectrometry. The mRNA and metabolite profiles were distinct in patients with benign and malignant disease. Integrated analysis of urinary gene expression and metabolite signatures unveiled an aberrant glutamate metabolism and tricarboxylic acid (TCA) cycle node in prostate cancer-derived cells. Functional validation supports a role for glutamate metabolism and glutamate oxaloacetate transaminase 1 (GOT1)-dependent redox balance in prostate cancer, which can be exploited for novel biomarkers and therapies.

cancer biology↗

bioRxiv2019

Dedifferentiation orchestrated through remodeling of the chromatin landscape defines PSEN1 mutation-induced Alzheimer's Disease

Early-Onset Familial Alzheimers Disease (EOFAD) is a dominantly inherited neurodegenerative disorder elicited by mutations in the PSEN1, PSEN2, and APP genes1. Hallmark pathological changes and symptoms observed, namely the accumulation of misfolded Amyloid-{beta} (A{beta}) in plaques and Tau aggregates in neurofibrillary tangles associated with memory loss and cognitive decline, are understood to be temporally accelerated manifestations of the more common sporadic Late-Onset Alzheimers Disease. The complete penetrance of EOFAD-causing mutations has allowed for experimental models which have proven integral to the overall understanding of AD2. However, the failure of pathology-targeting therapeutic development suggests that the formation of plaques and tangles may be symptomatic and not describe the etiology of the disease3,4. Here, we use an integrative, multi-omics approach and systems-level analysis in hiPSC-derived neurons to generate a mechanistic disease model for EOFAD. Using patient-specific cells from donors harboring mutations in PSEN1 differentiated into neurons, we characterize the disease-related gene expression and chromatin accessibility changes by RNA- Seq, ATAC-Seq, and histone methylation ChIP-Seq. We show that the defining disease-causing mechanism of EOFAD is dedifferentiation, primarily through the REST-mediated repression of neuronal lineage specification gene programs and the activation of non-specific germ layer precursor gene programs concomitant with modifications in chromatin accessibility. These gene signature profiles and changes in chromatin topology illustrate that EOFAD neurons traverse the chromatin landscape from an ectodermal origin to a mixed germ lineage state. Further, a reanalysis of existing transcriptomic data from PSEN1 patient brain samples demonstrates that the mechanisms identified in our experimental system recapitulate EOFAD in the human brain. Our results comprise a disease model which describes the mechanisms culminating in dedifferentiation that precede amyloid and tau pathology formation and engender neurodegeneration.

neuroscience↗