Biology subjects

Goetz, B. M.

Publications and source records attributed to Goetz, B. M..

3 recordsLinked to original sources

bioRxiv2025

Shedding dynamics of a DNA virus population during acute and long-term persistent infection

Although much is known of the molecular mechanisms of virus infection within cells, substantially less is understood about within-host infection. Such knowledge is key to understanding how viruses take up residence and transmit infectious virus, in some cases throughout the life of the host. Here, using murine polyomavirus (muPyV) as a tractable model, we monitor parallel infections of thousands of differentially barcoded viruses within a single host. In individual mice, we show that numerous viruses (>2600) establish infection and are maintained for long periods post-infection. Strikingly, a low level of many different barcodes is shed in urine at all times post-infection, with a minimum of at least 80 different barcodes present in every sample throughout months of infection. During the early acute phase, bulk shed virus genomes derive from numerous different barcodes. This is followed by long term persistent infection detectable in diverse organs. Consistent with limited productive exchange of virus genomes between organs, each displays a unique pattern of relative barcode abundance. During the persistent phase, constant low-level shedding of typically hundreds of barcodes is maintained but is overlapped with rare, punctuated shedding of high amounts of one or a few individual barcodes. In contrast to the early acute phase, these few infrequent highly shed barcodes comprise the majority of bulk shed genomes observed during late times of persistent infection, contributing to a stark decrease in bulk barcode diversity that is shed over time. These temporally shifting patterns, which are conserved across hosts, suggest that polyomaviruses balance continuous transmission potential with reservoir-driven high-level reactivation. This offers a mechanistic basis for polyomavirus ubiquity and long-term persistence, which are typical of many DNA viruses. Author Summary / ImportancePolyomavirus infections, mostly benign but potentially fatal for immunocompromised individuals, undergo acute and long-term persistent infections. Typically, polyomavirus-associated diseases arise due to virus infection occurring in the context of a persistently infected individual. However, little is understood regarding the mechanisms of how polyomaviruses establish, maintain, and reactivate from persistent infection. We developed a non-invasive virus shedding assay combining barcoded murine polyomavirus, massively parallel sequencing technology, and novel computational approaches to track long-term infections in mice. We expect these methods to be of use not only to the study of DNA viruses but also for understanding persitent infection of diverse microbes. The study revealed organ-specific virus reservoirs and two distinct shedding patterns: constant low-level shedding of numerous barcodes and episodic high-level shedding of few barcodes. Over time, the diversity of shed barcodes decreased substantially. These findings suggest a persistent low-level infection in multiple reservoirs, with occasional bursts of replication in a small subset of infected cells. This combination of broad reservoirs and varied shedding mechanisms may contribute to polyomavirus success in transmission and maintaining long-term infections.

pathology↗

bioRxiv2022

Interpreting and de-noising genetically engineered barcodes in a DNA virus

The concept of a nucleic acid barcode applied to pathogen genomes is easy to grasp and the many possible uses are straightforward. But implementation may not be easy, especially when growing through multiple generations or assaying the pathogen long-term. The potential problems include: the barcode might alter fitness, the barcode may accumulate mutations, and construction of the marked pathogens may result in unintended barcodes that are not as designed. Here, we generate approximately 5000 randomized barcodes in the genome of the prototypic small DNA virus murine polyomavirus. We describe the challenges faced with interpreting the barcode sequences obtained from the library. Our Illumina NextSeq sequencing recalled much greater variation in barcode sequencing reads than the expected 5000 barcodes - necessarily stemming from the Illumina library processing and sequencing error. Using data from defined control virus genomes cloned into plasmid backbones we develop a vetted post-sequencing method to cluster the erroneous reads around the true virus genome barcodes. These findings may foreshadow problems with randomized barcodes in other microbial systems and provide a useful approach for future work utilizing nucleic acid barcoded pathogens.

microbiology↗

bioRxiv2019

Molecular Profiling to Infer Neuronal Cell Identity: Lessons from small ganglia of the Crab Cancer borealis

Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: if cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell type classification, we performed two forms of transcriptional profiling - RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from two small crustacean networks: the stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbiased clustering analyses and supervised machine learning to determine how accurately functionally-defined neuron types can be classified by expression profile alone. Our results demonstrate that expression profile is able to capture neuronal identity most accurately when combined with multimodal information that allows for post-hoc grouping so analysis can proceed from a supervised perspective. Solely unsupervised clustering can lead to misidentification and an inability to distinguish between two or more cell types. Therefore, our study supports the general utility of cell identification by transcriptional profiling, but adds a caution: it is difficult or impossible to know under what conditions transcriptional profiling alone is capable of assigning cell identity. Only by combining multiple modalities of information such as physiology, morphology or innervation target can neuronal identity be unambiguously determined.\n\nSIGNIFICANCE STATEMENTSingle cell transcriptional profiling has become a widespread tool in cell identification, particularly in the nervous system, based on the notion that genomic information determines cell identity. However, many cell type classification studies are unconstrained by other cellular attributes (e.g., morphology, physiology). Here, we systematically test how accurately transcriptional profiling can assign cell identity to well-studied anatomically- and functionally-identified neurons in two small neuronal networks. While these neurons clearly possess distinct patterns of gene expression across cell types, their expression profiles are not sufficient to unambiguously confirm their identity. We suggest that true cell identity can only be determined by combining gene expression data with other cellular attributes such as innervation pattern, morphology, or physiology.

neuroscience↗