Biology subjects

Gohl, D.

Publications and source records attributed to Gohl, D..

6 recordsLinked to original sources

bioRxiv2025

Sleeping Beauty mutagenesis identifies BACH2 and other regulators of CD8+T cell exhaustion, persistence in vivo, and CAR-T function under tumor-associated chronic antigen stimulation

Genes that enhance T cell function represent promising targets for improving engineered T cell therapies for cancer. While extensive CRISPR knockout screens have identified key genes enhancing T cell persistence, employing Sleeping Beauty (SB) insertional mutagenesis, which induces both gain-(GOF) and loss-of-function (LOF) mutations via the generation of fusion transcripts with endogenous genes, may uncover additional critical factors that previous approaches have overlooked. We developed transgenic mice carrying Doxycycline (Dox)-inducible SB mutagenesis system (DiSBey) in primary T cells. Using DiSBey, we conducted screens for genetic alterations enhancing T cell persistence under chronic antigen exposure. Specifically, CD8 T cells from Dox-fed DiSBey mice were subjected to repeated anti-CD3 stimulation over 18 days to mimic chronic antigenic stimulation. We then identified SB transposon genomic insertion sites and corresponding fusion transcripts from the persistent DiSBey CD8 T cells using enhanced-specificity tagmentation sequencing (esTag-seq) and RNA-seq, respectively. Under chronic stimulation, SB-mutagenized CD8 T cells exhibited improved persistence and reduced terminal exhaustion phenotype. Across six independent screens, we identified 38 genes that were recurrently targeted by the SB transposon T2/Onc2 and differentially expressed under chronic anti-CD3 stimulation stress. Among these, T2/Onc2 insertions into Bach2 and Elmo1 were repeatedly found at the genomic level and were associated with altered nascent transcript expression. Bach2, known as a key regulator of T cell memory formation and resistance to chronic viral infection but less characterized in engineered T cells for cancer therapy, was found to enhance in vivo tumor persistence in the B16-Ova tumor model. We showed that ectopic Bach2 expression levels influence engineered T cell differentiation lineage. A Bach2low signature allowed differentiation into both KLRG1 and CD62L phenotypes, whereas Bach2high restricted differentiation predominantly to the CD62L subset. Finally, in human CART19-28{zeta} cells, BACH2 overexpression enhanced cytotoxicity and improved tumor control following chronic cancer stimulation. Controllable SB mutagenesis using DiSBey mice provides a novel platform for functional screening of genes that improve T cell therapeutic phenotypes. Our findings highlight a dose-dependent role of BACH2 in enhancing the function of engineered T cells under conditions of chronic antigenic stimulation.

immunology↗

bioRxiv2023

Variability and Bias in Microbiome Metagenomic Sequencing: an Interlaboratory Study Comparing Experimental Protocols

BackgroundSeveral studies have documented the significant impact of methodological choices in microbiome analyses. The myriad of methodological options available complicate the replication of results and generally limit the comparability of findings between independent studies that use differing techniques and measurement pipelines. Here we describe the Mosaic Standards Challenge (MSC), an international interlaboratory study designed to assess the impact of methodological variables on the results. The MSC did not prescribe methods but rather asked participating labs to analyze 7 shared reference samples (5x human stool samples and 2x mock communities) using their standard laboratory methods. To capture the array of methodological variables, each participating lab completed a metadata reporting sheet that included 100 different questions regarding the details of their protocol. The goal of this study was to survey the methodological landscape for microbiome metagenomic sequencing (MGS) analyses and the impact of methodological decisions on metagenomic sequencing results. ResultsA total of 44 labs participated in the MSC by submitting results (16S or WGS) along with accompanying metadata; thirty 16S rRNA gene amplicon datasets and 14 WGS datasets were collected. The inclusion of two types of reference materials (human stool and mock communities) enabled analysis of both MGS measurement variability between different protocols using the biologically-relevant stool samples, and MGS bias with respect to ground truth values using the DNA mixtures. Owing to the compositional nature of MGS measurements, analyses were conducted on the ratio of Firmicutes: Bacteroidetes allowing us to directly apply common statistical methods. The resulting analysis demonstrated that protocol choices have significant effects, including both bias of the MGS measurement associated with a particular methodological choices, as well as effects on measurement robustness as observed through the spread of results between labs making similar methodological choices. In the analysis of the DNA mock communities, MGS measurement bias was observed even when there was general consensus among the participating laboratories. ConclusionThis study was the result of a collaborative effort that included academic, commercial, and government labs. In addition to highlighting the impact of different methodological decisions on MGS result comparability, this work also provides insights for consideration in future microbiome measurement study design.

microbiology↗

bioRxiv2023

A machine vision guided robot for fully automated embryonic microinjection

Microinjection is a widely used technique for transgenesis, mutagenesis, cell labeling, cryopreservation, and in vitro fertilization in multiple single and multicellular organisms. Microinjection requires specialized skills acquired for each target organism and involves rate limiting and labor-intensive preparatory steps. Here we constructed a machine vision (MV) guided generalized robot that fully automates the process of microinjection in fruit fly (Drosophila melanogaster) and zebrafish (Danio rerio) embryos. The robot uses machine learning (ML) models trained to detect individual embryos in images of agar plates, and models trained to identify specific anatomical locations within each embryo in 3D space using dual view microscopes. The robot uses this information to serially perform microinjection in each detected embryo without any human intervention. We constructed and used three such robots to automatically microinject tens of thousands of Drosophila and zebrafish embryos. We systematically optimized robotic microinjection for each species and validated the use of the robot by performing routine transgenesis with proficiency comparable to highly skilled human practitioners while achieving up to 4x increases in microinjection throughput in Drosophila. The automated microinjection robot was utilized to microinject pools of over 20,000 uniquely barcoded plasmids into 1,713 embryos in two days to rapidly generate more than 400 unique transgenic Drosophila lines. This high throughput microinjection experiment enabled a novel measurement of the number of independent germline integration events per successfully injected embryo. Finally, we showed that robotic microinjection of cryoprotective agents in zebrafish embryos significantly improves vitrification rates and survival of cryopreserved embryos post-thaw as compared to manual microinjection, opening the tantalizing possibility of large-scale cryobanking of aquatic species at an industrial scale. We anticipate that this versatile automated microinjection system can be applied to carry out microinjection for genome-wide manipulation and cryopreservation at scale in a wide range of other organisms.

genetics↗

bioRxiv2023

Deterministic Genetic Barcoding for Multiplexed Behavioral and Single-Cell Transcriptomic Studies

Advances in single-cell sequencing technologies have provided novel insights into the dynamics of gene expression throughout development, been used to characterize somatic variation and heterogeneity within tissues, and are currently enabling the construction of transcriptomic cell atlases. However, despite these remarkable advances, linking anatomical information to transcriptomic data and positively identifying the cell types that correspond to gene expression clusters in single-cell sequencing data sets remains a challenge. We describe a straightforward genetic barcoding approach that takes advantage of the powerful genetic tools available in Drosophila to allow in vivo tagging of defined cell populations. This method, called Targeted Genetically-Encoded Multiplexing (TaG-EM), involves inserting a DNA barcode just upstream of the polyadenylation site in a Gal4-inducible UAS-GFP construct so that the barcode sequence can be read out during single-cell sequencing, labeling a cell population of interest. By creating many such independently barcoded fly strains, TaG-EM will enable a number of potential applications that will improve the quality and information content of single-cell transcriptomic data including positive identification of cell types in cell atlas projects, identification of multiplet droplets, and barcoding of experimental timepoints, conditions, and replicates. Furthermore, we demonstrate that the barcodes from TaG-EM fly lines can be read out using next-generation sequencing to facilitate population-scale behavioral measurements. Thus, TaG-EM has the potential to enable large-scale behavioral screens in addition to improving the ability to reliably annotate cell atlas data, expanding the scope, and improving the robustness of single-cell transcriptomic experiments.

genomics↗

bioRxiv2019

Influence of genetic polymorphism on transcriptional enhancer activity in the malaria vector Anopheles coluzzii

Enhancers are cis-regulatory elements that control most of the developmental and spatial gene expression in eukaryotes. Genetic variation of enhancer sequences is known to influence phenotypes, but the effect of enhancer variation upon enhancer functional activity and downstream phenotypes has barely been examined in any species. In the African malaria vector, Anopheles coluzzii, we identified a pilot set of candidate enhancers in the proximity of genes relevant for immunity, insecticide resistance, and development. The candidate enhancers were functionally validated using luciferase reporter assays, and their activity was found to be essentially independent of their physical orientation, a typical property of enhancers. All of the enhancer intervals segregated genetically polymorphic alleles, which displayed significantly different levels of functional activity, and inactive null alleles were also observed. Deletion mutagenesis and functional testing revealed a modular structure of positive and negative regulatory elements within the tested enhancers. The enhancer alleles carry genetic polymorphisms that also segregate in wild A. coluzzii populations in West Africa, indicating that enhancer variants with likely phenotypic consequences are frequent in nature. These results demonstrate the feasibility of screening for naturally polymorphic A. coluzzii enhancers that underlie important aspects of malaria transmission and vector biology.

genetics↗

bioRxiv2018

Evaluating the information content of shallow shotgun metagenomics

Although microbial communities are associated with many aspects of human, environmental, plant, and animal health, there exists no cost-effective method for precisely characterizing species and genes present in such communities. While deep whole-genome shotgun (WGS) sequencing provides the highest-level of taxonomic and functional resolution, it is often prohibitively expensive for large-scale studies. The prevailing alternative, high-throughput 16S rRNA gene amplicon sequencing (16S), often does not resolve taxonomy past the genus level and provides only moderately accurate predictions of the functional profile; thus, there is currently no widely accepted approach to affordable, high-resolution, taxonomic and functional microbiome analysis. To address this technology gap, we evaluated the information content of shallow shotgun sequencing with as low as 0.5 million sequences per sample as an alternative to 16S sequencing for large human microbiome studies. We describe a library preparation protocol enabling shallow shotgun sequencing at approximately the same per-sample cost as 16S. We analyzed multiple real and simulated biological data sets, including two novel human stool samples with ultra-deep sequencing of 2.5 billion sequences per sample, and found that shallow shotgun recovers accurate species-level taxonomic and functional profiles of the human microbiome. We recognize and discuss some of the inherent limitations of shallow shotgun sequencing, and note that 16S sequencing remains a valuable and important method for taxonomic profiling of novel environments. Although deep WGS remains the gold standard for high-resolution microbiome analysis, we recommend that researchers consider shallow shotgun sequencing as a useful alternative to 16S for large-scale human microbiome research studies.

genomics↗