Combinatorial programming of human neuronal progenitors using magnetically-guided stoichiometric mRNA delivery

  1. Sayyed M Azimi
  2. Steven D Sheridan
  3. Mostafa Ghannad-Rezaie
  4. Peter M Eimon
  5. Mehmet Fatih Yanik  Is a corresponding author
  1. Massachusetts Institute of Technology, United States

Abstract

Identification of optimal transcription-factor expression patterns to direct cellular differentiation along a desired pathway presents significant challenges. We demonstrate massively combinatorial screening of temporally-varying mRNA transcription factors to direct differentiation of neural progenitor cells using a dynamically-reconfigurable magnetically-guided spotting technology for localizing mRNA, enabling experiments on millimetre size spots. In addition, we present a time-interleaved delivery method that dramatically reduces fluctuations in the delivered transcription-factor copy-numbers per cell. We screened combinatorial and temporal delivery of a pool of midbrain-specific transcription factors to augment the generation of dopaminergic neurons. We show that the combinatorial delivery of LMX1A, FOXA2 and PITX3 is highly effective in generating dopaminergic neurons from midbrain progenitors. We show that LMX1A significantly increases TH-expression levels when delivered to neural progenitor cells either during proliferation or after induction of neural differentiation, while FOXA2 and PITX3 increase expression only when delivered prior to induction, demonstrating temporal dependence of factor addition.

Data availability

All data generated or analyzed during this study are included in the manuscript and supporting files.

Article and author information

Author details

  1. Sayyed M Azimi

    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Steven D Sheridan

    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Mostafa Ghannad-Rezaie

    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Peter M Eimon

    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0447-517X
  5. Mehmet Fatih Yanik

    Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, United States
    For correspondence
    yanik@ethz.ch
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8963-2893

Funding

NIH Office of the Director

  • Mehmet Fatih Yanik

David and Lucile Packard Foundation

  • Mehmet Fatih Yanik

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Sacha B Nelson, Brandeis University, United States

Version history

  1. Received: September 26, 2017
  2. Accepted: April 30, 2018
  3. Accepted Manuscript published: May 1, 2018 (version 1)
  4. Version of Record published: May 18, 2018 (version 2)

Copyright

© 2018, Azimi et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,519
    views
  • 205
    downloads
  • 6
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Sayyed M Azimi
  2. Steven D Sheridan
  3. Mostafa Ghannad-Rezaie
  4. Peter M Eimon
  5. Mehmet Fatih Yanik
(2018)
Combinatorial programming of human neuronal progenitors using magnetically-guided stoichiometric mRNA delivery
eLife 7:e31922.
https://doi.org/10.7554/eLife.31922

Share this article

https://doi.org/10.7554/eLife.31922

Further reading

    1. Neuroscience
    Songyao Zhang, Tuo Zhang ... Tianming Liu
    Research Article

    Cortical folding is an important feature of primate brains that plays a crucial role in various cognitive and behavioral processes. Extensive research has revealed both similarities and differences in folding morphology and brain function among primates including macaque and human. The folding morphology is the basis of brain function, making cross-species studies on folding morphology important for understanding brain function and species evolution. However, prior studies on cross-species folding morphology mainly focused on partial regions of the cortex instead of the entire brain. Previously, our research defined a whole-brain landmark based on folding morphology: the gyral peak. It was found to exist stably across individuals and ages in both human and macaque brains. Shared and unique gyral peaks in human and macaque are identified in this study, and their similarities and differences in spatial distribution, anatomical morphology, and functional connectivity were also dicussed.

    1. Neuroscience
    Avani Koparkar, Timothy L Warren ... Lena Veit
    Research Article

    Complex skills like speech and dance are composed of ordered sequences of simpler elements, but the neuronal basis for the syntactic ordering of actions is poorly understood. Birdsong is a learned vocal behavior composed of syntactically ordered syllables, controlled in part by the songbird premotor nucleus HVC (proper name). Here, we test whether one of HVC’s recurrent inputs, mMAN (medial magnocellular nucleus of the anterior nidopallium), contributes to sequencing in adult male Bengalese finches (Lonchura striata domestica). Bengalese finch song includes several patterns: (1) chunks, comprising stereotyped syllable sequences; (2) branch points, where a given syllable can be followed probabilistically by multiple syllables; and (3) repeat phrases, where individual syllables are repeated variable numbers of times. We found that following bilateral lesions of mMAN, acoustic structure of syllables remained largely intact, but sequencing became more variable, as evidenced by ‘breaks’ in previously stereotyped chunks, increased uncertainty at branch points, and increased variability in repeat numbers. Our results show that mMAN contributes to the variable sequencing of vocal elements in Bengalese finch song and demonstrate the influence of recurrent projections to HVC. Furthermore, they highlight the utility of species with complex syntax in investigating neuronal control of ordered sequences.