Individual human cortical progenitors can produce excitatory and inhibitory neurons.

The cerebral cortex is a cellularly complex structure comprising a rich diversity of neuronal and glial cell types. Cortical neurons can be broadly categorized into two classes-excitatory neurons that use the neurotransmitter glutamate, and inhibitory interneurons that use γ-aminobutyric acid (GABA). Previous developmental studies in rodents have led to a prevailing model in which excitatory neurons are born from progenitors located in the cortex, whereas cortical interneurons are born from a separate population of progenitors located outside the developing cortex in the ganglionic eminences1-5. However, the developmental potential of human cortical progenitors has not been thoroughly explored. Here we show that, in addition to excitatory neurons and glia, human cortical progenitors are also capable of producing GABAergic neurons with the transcriptional characteristics and morphologies of cortical interneurons. By developing a cellular barcoding tool called 'single-cell-RNA-sequencing-compatible tracer for identifying clonal relationships' (STICR), we were able to carry out clonal lineage tracing of 1,912 primary human cortical progenitors from six specimens, and to capture both the transcriptional identities and the clonal relationships of their progeny. A subpopulation of cortically born GABAergic neurons was transcriptionally similar to cortical interneurons born from the caudal ganglionic eminence, and these cells were frequently related to excitatory neurons and glia. Our results show that individual human cortical progenitors can generate both excitatory neurons and cortical interneurons, providing a new framework for understanding the origins of neuronal diversity in the human cortex.

Thalamocortical organoids enable in vitro modeling of 22q11.2 microdeletion associated with neuropsychiatric disorders.

Thalamic dysfunction has been implicated in multiple psychiatric disorders. We sought to study the mechanisms by which abnormalities emerge in the context of the 22q11.2 microdeletion, which confers significant genetic risk for psychiatric disorders. We investigated early stages of human thalamus development using human pluripotent stem cell-derived organoids and show that the 22q11.2 microdeletion underlies widespread transcriptional dysregulation associated with psychiatric disorders in thalamic neurons and glia, including elevated expression of FOXP2. Using an organoid co-culture model, we demonstrate that the 22q11.2 microdeletion mediates an overgrowth of thalamic axons in a FOXP2-dependent manner. Finally, we identify ROBO2 as a candidate molecular mediator of the effects of FOXP2 overexpression on thalamic axon overgrowth. Together, our study suggests that early steps in thalamic development are dysregulated in a model of genetic risk for schizophrenia and contribute to neural phenotypes in 22q11.2 deletion syndrome.

Fate mapping of neural stem cell niches reveals distinct origins of human cortical astrocytes.

Progenitors of the developing human neocortex reside in the ventricular and outer subventricular zones (VZ and OSVZ, respectively). However, whether cells derived from these niches have similar developmental fates is unknown. By performing fate mapping in primary human tissue, we demonstrate that astrocytes derived from these niches populate anatomically distinct layers. Cortical plate astrocytes emerge from VZ progenitors and proliferate locally, while putative white matter astrocytes are morphologically heterogeneous and emerge from both VZ and OSVZ progenitors. Furthermore, via single-cell sequencing of morphologically defined astrocyte subtypes using Patch-seq, we identify molecular distinctions between VZ-derived cortical plate astrocytes and OSVZ-derived white matter astrocytes that persist into adulthood. Together, our study highlights a complex role for cell lineage in the diversification of human neocortical astrocytes.

IoT cloud laboratory: Internet of Things architecture for cellular biology.

The Internet of Things (IoT) provides a simple framework to control online devices easily. IoT is now a commonplace tool used by technology companies but is rarely used in biology experiments. IoT can benefit cloud biology research through alarm notifications, automation, and the real-time monitoring of experiments. We developed an IoT architecture to control biological devices and implemented it in lab experiments. Lab devices for electrophysiology, microscopy, and microfluidics were created from the ground up to be part of a unified IoT architecture. The system allows each device to be monitored and controlled from an online web tool. We present our IoT architecture so other labs can replicate it for their own experiments.

Light-weight electrophysiology hardware and software platform for cloud-based neural recording experiments.

Objective.Neural activity represents a functional readout of neurons that is increasingly important to monitor in a wide range of experiments. Extracellular recordings have emerged as a powerful technique for measuring neural activity because these methods do not lead to the destruction or degradation of the cells being measured. Current approaches to electrophysiology have a low throughput of experiments due to manual supervision and expensive equipment. This bottleneck limits broader inferences that can be achieved with numerous long-term recorded samples.Approach.We developed Piphys, an inexpensive open source neurophysiological recording platform that consists of both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols.Main results.We used a Raspberry Pi as the primary processing device along with an Intan bioamplifier. We designed a hardware expansion circuit board and software to enable voltage sampling and user interaction. This standalone system was validated with primary human neurons, showing reliability in collecting neural activity in near real-time.Significance.The hardware modules and cloud software allow for remote control of neural recording experiments as well as horizontal scalability, enabling long-term observations of development, organization, and neural activity at scale.

Human microglia states are conserved across experimental models and regulate neural stem cell responses in chimeric organoids.

Microglia are resident macrophages in the brain that emerge in early development and respond to the local environment by altering their molecular and phenotypic states. Fundamental questions about microglia diversity and function during development remain unanswered because we lack experimental strategies to interrogate their interactions with other cell types and responses to perturbations ex vivo. We compared human microglia states across culture models, including cultured primary and pluripotent stem cell-derived microglia. We developed a "report card" of gene expression signatures across these distinct models to facilitate characterization of their responses across experimental models, perturbations, and disease conditions. Xenotransplantation of human microglia into cerebral organoids allowed us to characterize key transcriptional programs of developing microglia in vitro and reveal that microglia induce transcriptional changes in neural stem cells and decrease interferon signaling response genes. Microglia additionally accelerate the emergence of synchronized oscillatory network activity in brain organoids by modulating synaptic density.

Evolutionary Expansion of Human Cerebellar Germinal Zones.

Haldipur et al. explored the developmental origins of the human cerebellum, which has gained growing appreciation for its involvement in human cognition. The authors discovered human-unique expansion and maintenance of cerebellar germinal zones, reminiscent of processes in the developing human cerebral cortex necessary for generating expanded neuronal populations.

Revealing architectural order with quantitative label-free imaging and deep learning.

We report quantitative label-free imaging with phase and polarization (QLIPP) for simultaneous measurement of density, anisotropy, and orientation of structures in unlabeled live cells and tissue slices. We combine QLIPP with deep neural networks to predict fluorescence images of diverse cell and tissue structures. QLIPP images reveal anatomical regions and axon tract orientation in prenatal human brain tissue sections that are not visible using brightfield imaging. We report a variant of U-Net architecture, multi-channel 2.5D U-Net, for computationally efficient prediction of fluorescence images in three dimensions and over large fields of view. Further, we develop data normalization methods for accurate prediction of myelin distribution over large brain regions. We show that experimental defects in labeling the human tissue can be rescued with quantitative label-free imaging and neural network model. We anticipate that the proposed method will enable new studies of architectural order at spatial scales ranging from organelles to tissue.

Microscopy is central to biological research and has enabled scientist to study the structure and dynamics of cells and their components within. Often, fluorescent dyes or trackers are used that can be detected under the microscope. However, this procedure can sometimes interfere with the biological processes being studied. Now, Guo, Yeh, Folkesson et al. have developed a new approach to examine structures within tissues and cells without the need for a fluorescent label. The technique, called QLIPP, uses the phase and polarization of the light passing through the sample to get information about its makeup. A computational model was used to decode the characteristics of the light and to provide information about the density and orientation of molecules in live cells and brain tissue samples of mice and human. This way, Guo et al. were able to reveal details that conventional microscopy would have missed. Then, a type of machine learning, known as 'deep learning', was used to translate the density and orientation images into fluorescence images, which enabled the researchers to predict specific structures in human brain tissue sections. QLIPP can be added as a module to a microscope and its software is available open source. Guo et al. hope that this approach can be used across many fields of biology, for example, to map the connectivity of nerve cells in the human brain or to identify how cells respond to infection. However, further work in automating other aspects, such as sample preparation and analysis, will be needed to realize the full benefits.

Development and Arealization of the Cerebral Cortex.

Adult cortical areas consist of specialized cell types and circuits that support unique higher-order cognitive functions. How this regional diversity develops from an initially uniform neuroepithelium has been the subject of decades of seminal research, and emerging technologies, including single-cell transcriptomics, provide a new perspective on area-specific molecular diversity. Here, we review the early developmental processes that underlie cortical arealization, including both cortex intrinsic and extrinsic mechanisms as embodied by the protomap and protocortex hypotheses, respectively. We propose an integrated model of serial homology whereby intrinsic genetic programs and local factors establish early transcriptomic differences between excitatory neurons destined to give rise to broad "proto-regions," and activity-dependent mechanisms lead to progressive refinement and formation of sharp boundaries between functional areas. Finally, we explore the potential of these basic developmental processes to inform our understanding of the emergence of functional neural networks and circuit abnormalities in neurodevelopmental disorders.