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Volume 20 Issue 9, September 2023

Voltage-imaging-guided single-cell transcriptomics

All-optical voltage imaging with Voltron-expressing neurons (orange cells) optogenetically stimulated with blue light. The neuronal signals are represented by the yellow lines.

See Csillag et al.

Image: Isabella Bizzozzero Hiriart. Cover Design: Thomas Phillips.

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  • They started their lab mid-COVID. The new principal investigator adventure is a roller-coaster ride with some unexpected surprises.

    • Vivien Marx
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  • Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry. —Richard Feynman

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  • Multiplexed spatial immunophenotyping has advanced our understanding of tissues in the context of homeostasis and disease. Two studies now provide additional tools to overcome challenges with multiplexed imaging: one procedure amplifies the detection of low-abundance antigens by integrating SABER and IMC technologies, and the other is an X-ray-based method that enables the non-destructive multiplexed detection of antigens in tissues at scalable resolution and speed.

    • Marieke E. Ijsselsteijn
    • Noel F. C. C. de Miranda
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  • Recently proposed computational approaches explore casual links between chromatin and transcriptional changes that are provided by single-cell multimodal sequencing to bridge the knowledge gap in transcriptional regulatory control.

    • Ivan G. Costa
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  • The conversion of biological molecules into digital signals through sequencing is a complex process that often generates substantial systematic background noise. This noise can obscure important biological insights. However, by precisely identifying and removing this noise, we can bring the true signal into focus and eliminate misleading results from downstream analyses.

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  • Single-cell perturbation screens are routinely conducted to study the effects of different perturbations on cellular state, yet such studies are easily confounded by nuisance sources of variation shared with control cells. We present a deep learning method that isolates perturbation-specific sources of variation, enabling a better understanding of the perturbation’s effects.

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  • We developed, characterized and validated nLight sensors, a new family of genetically encoded green and red fluorescent norepinephrine indicators based on an alpha-1 adrenergic receptor. nLight probes can detect norepinephrine in living animals with superior sensitivity, ligand specificity and temporal resolution as compared with previous tools.

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