Abstract CRISPR-based genetic perturbation screens paired with single-cell transcriptomic readouts (Perturb-seq) offer a powerful tool for interrogating biological systems. Yet the resulting datasets are heterogeneous—particularly in vivo—and currently used cell-level perturbation labels reflect only CRISPR guide RNA exposure rather than perturbation state; further, many perturbations have a minimal effect on gene expression. For perturbations that do alter the transcriptomic state of cells, intracellular guide RNA abundance exhibits a dose-response association with perturbation efficacy. We combine (i) per-perturbation, expression-only classifiers trained with non-negative negative–unlabeled (nnNU) risk to yield calibrated scores reflecting the perturbation state of single cells and (ii) a monotone guide abundance prior to yield a per-cell pseudo-posterior that supports both assignment of perturbation probability and selection of affected gene features. To obtain a low-dimensional representation that allows for the accurate reconstruction of gene-level marginals for counterfactual decoding, we train an autoencoder with a quantile–hurdle reconstruction loss and feature-weighted emphasis on perturbation-affected genes. The result is a perturbation-aware latent embedding amenable to downstream trajectory modeling (e.g., optimal transport or flow matching) and a principled probability of perturbation for each non-control cell derived jointly from its guide counts and transcriptome.

Authors Florian Hugi, Tanmay Tanna, Randall J. Platt, Gunnar Rätsch

Submitted NeurIPS 2025 AI4D3

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Abstract Engineered microbes show potential for diagnosing and treating diseases. In this issue of Cell Host & Microbe, Zou et al. develop an “intelligent” bacterial strain that detects and monitors an inflammation biomarker in the gut and responds by releasing an immunomodulator, thereby combining diagnosis and therapy for intestinal inflammation.

Authors Tanmay Tanna, Randall J. Platt

Submitted Cell Host and Microbe

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Authors Mariia Y Cherepkova, Tanmay Tanna, Randall J Platt

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Abstract Transcriptional recording by CRISPR spacer acquisition from RNA endows engineered Escherichia coli with synthetic memory, which through Record-seq reveals transcriptome-scale records. Microbial sentinels that traverse the gastrointestinal tract capture a wide range of genes and pathways that describe interactions with the host, including quantitative shifts in the molecular environment that result from alterations in the host diet, induced inflammation, and microbiome complexity. We demonstrate multiplexed recording using barcoded CRISPR arrays, enabling the reconstruction of transcriptional histories of isogenic bacterial strains in vivo. Record-seq therefore provides a scalable, noninvasive platform for interrogating intestinal and microbial physiology throughout the length of the intestine without manipulations to host physiology and can determine how single microbial genetic differences alter the way in which the microbe adapts to the host intestinal environment.

Authors Florian Schmidt, Jakob Zimmermann, Tanmay Tanna, Rick Farouni, Tyrell Conway, Andrew J Macpherson, and Randall J Platt

Submitted Science

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Abstract Advances in synthetic biology and microbiology have enabled the creation of engineered bacteria which can sense and report on intracellular and extracellular signals. When deployed in vivo these whole-cell bacterial biosensors can act as sentinels to monitor biomolecules of interest in human health and disease settings. This is particularly interesting in the context of the gut microbiota, which interacts extensively with the human host throughout time and transit of the gut and can be accessed from feces without requiring invasive collection. Leveraging rational engineering approaches for genetic circuits as well as an expanding catalog of disease-associated biomarkers, bacterial biosensors can act as non-invasive and easy-to-monitor reporters of the gut. Here, we summarize recent engineering approaches applied in vivo in animal models and then highlight promising technologies for designing the next generation of bacterial biosensors.

Authors Tanmay Tanna, Raghavendra Ramachanderan, Randall J Platt

Submitted Current Opinion in Microbiology

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Abstract It is difficult to elucidate the transcriptional history of a cell using current experimental approaches, as they are destructive in nature and therefore describe only a moment in time. To overcome these limitations, we recently established Record-seq, a technology that enables transcriptional recording by CRISPR spacer acquisition from RNA. The recorded transcriptomes are recovered by SENECA, a method that selectively amplifies expanded CRISPR arrays, followed by deep sequencing. The resulting CRISPR spacers are aligned to the host genome, thereby enabling transcript quantification and associated analyses. Here, we describe the experimental procedures of the Record-seq workflow as well as subsequent data analysis. Beginning with the experimental design, Record-seq data can be obtained and analyzed within 1–2 weeks.

Authors Tanmay Tanna, Florian Schmidt, Mariia Y. Cherepkova, Michal Okoniewski, Randall J. Platt

Submitted Nature Protocols

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