Thomas Haynes Hutson

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Natural and targeted circuit reorganization after spinal cord injury

Mark Andrew Anderson, Quentin Barraud, Jocelyne Bloch, Grégoire Courtine, Matthieu Pierre Gautier, Thomas Haynes Hutson, Claudia Kathe, Jordan Squair

The authors summarize changes in circuits after spinal cord injury and current strategies to target these circuits in order to improve recovery, but also advocate for new concepts of reorganizing circuits informed by multi-omic single-cell atlases. A spinal cord injury disrupts communication between the brain and the circuits in the spinal cord that regulate neurological functions. The consequences are permanent paralysis, loss of sensation and debilitating dysautonomia. However, the majority of circuits located above and below the injury remain anatomically intact, and these circuits can reorganize naturally to improve function. In addition, various neuromodulation therapies have tapped into these processes to further augment recovery. Emerging research is illuminating the requirements to reconstitute damaged circuits. Here, we summarize these natural and targeted reorganizations of circuits after a spinal cord injury. We also advocate for new concepts of reorganizing circuits informed by multi-omic single-cell atlases of recovery from injury. These atlases will uncover the molecular logic that governs the selection of 'recovery-organizing' neuronal subpopulations, and are poised to herald a new era in spinal cord medicine.

NATURE PORTFOLIO2022

Confronting false discoveries in single-cell differential expression

Mark Andrew Anderson, Quentin Barraud, Grégoire Courtine, Matthieu Pierre Gautier, Rémi Bernard René Hudelle, Thomas Haynes Hutson, Nicholas David James, Claudia Kathe, Gioele La Manno, Michael Alexander Skinnider, Jordan Squair

Differential expression analysis of single-cell transcriptomics allows scientists to dissect cell-type-specific responses to biological perturbations. Here, the authors show that many commonly used methods are biased and can produce false discoveries. Differential expression analysis in single-cell transcriptomics enables the dissection of cell-type-specific responses to perturbations such as disease, trauma, or experimental manipulations. While many statistical methods are available to identify differentially expressed genes, the principles that distinguish these methods and their performance remain unclear. Here, we show that the relative performance of these methods is contingent on their ability to account for variation between biological replicates. Methods that ignore this inevitable variation are biased and prone to false discoveries. Indeed, the most widely used methods can discover hundreds of differentially expressed genes in the absence of biological differences. To exemplify these principles, we exposed true and false discoveries of differentially expressed genes in the injured mouse spinal cord.

NATURE PORTFOLIO2021

Editorial: Biochemical and genetic tools to investigate the underlying mechanisms and treatment of sensorimotor pathologies

Natural and targeted circuit reorganization after spinal cord injury

Confronting false discoveries in single-cell differential expression

Editorial: Biochemical and genetic tools to investigate the underlying mechanisms and treatment of sensorimotor pathologies

Natural and targeted circuit reorganization after spinal cord injury

Confronting false discoveries in single-cell differential expression