In vivo Pooled Screening: A Scalable Tool to Study the Complexity of Aging and Age-Related Disease

Abstract

Biological aging, and the diseases of aging, occur in a complex in vivo environment, driven by multiple interacting processes. A convergence of recently developed technologies has enabled in vivo pooled screening: direct administration of a library of different perturbations to a living animal, with a subsequent readout that distinguishes the identity of each perturbation and its effect on individual cells within the animal. Such screens hold promise for efficiently applying functional genomics to aging processes in the full richness of the in vivo setting. In this review, we describe the technologies behind in vivo pooled screening, including a range of options for delivery, perturbation and readout methods, and outline their potential application to aging and age-related disease. We then suggest how in vivo pooled screening, together with emerging innovations in each of its technological underpinnings, could be extended to shed light on key open questions in aging biology, including the mechanisms and limits of epigenetic reprogramming and identifying cellular mediators of systemic signals in aging.

Keywords: aging models; animal models; barcoding; direct in vivo screening; gene therapy; in vivo; pooled screening; single cell sequencing.

FIGURE 1

Complexity of aging is overlooked by in vitro models: Aging in vivo exposes cells to diverse stimuli, which drive and regulate the aging process. Most of these stimuli, including signals from other cells and organs, are absent in vitro. This can in some cases be addressed with specialized growth conditions (e.g. in hydrogels), or by co-culturing 2 cell types. But no current system addresses all of these factors, let alone factors we have yet to discover. This motivates the study of aging in its natural, in vivo, environment.

FIGURE 2

The process of an in vivo pooled screen. In vivo pooled screens require careful choices at five key steps of the process. To illustrate this in practice, we include the decision-process for a hypothetical screen setup inspired by a published in vitro screen (Theodoris et al., 2020): The screen looks for treatments for aortic valve disease caused by Notch1 loss of function. Since mechanical forces affect the disease, an ideal model would have heart size and structure similar to humans, e.g. a Notch1 loss of function pig model. To find potential therapies, the screen could focus on secreted ligands, which could be developed as biologics. Suitable barcodes and a fluorescent reporter would also be included in perturbation constructs. Cardiomyocytes are non-replicating and can be transduced well by adeno-associated virus, but no serotype exists that targets these cells without transducing e.g. the liver. Thus intracardiac injection would best limit the perturbations to cardiomyocytes. Previous work had identified a gene network characteristic of disease, so measuring the transcriptomic state of perturbed cells would be the ideal readout. For cardiomyocytes, single-nucleus sequencing is likely to yield better quality data than whole-cell sequencing. This means that the library should be constructed with a nuclear-localized reporter. Additional considerations are noted in the figure, and discussed in the text.

FIGURE 3

Key differences between pooled and traditional in vivo testing: In non-pooled in vivo experiments, animal-to-animal variability in phenotypes of interest and in response to perturbation necessitates using large cohorts. With in vivo pooled screening, the effect of perturbations is measured relative to unperturbed cells in the same animal, side-stepping inter-animal phenotypic variability. Because large cohorts are not required, the most relevant species and/or animals with spontaneous age-related disease can be used in place of commonly available models.