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Biology subjects

Salama, S. R.

Publications and source records attributed to Salama, S. R..

17 recordsLinked to original sources

A foundation model for brain organoid network dynamics uncovers intrinsic computation and convergent disease phenotypes

Brain organoids develop self-organizing neural networks that can be used to model neurodevelopment and disease. Here we introduce PULSE, a foundation model developed using over 900 hours of high-density microelectrode array recordings of in vitro and ex vivo neural tissue. We show that this single model can address two open questions: how disease-associated variants alter network development, and how naive circuits encode information. PULSE revealed accelerated network maturation in held-out human 16p11.2-deletion organoids. It also revealed a change in network coordination shared with SHANK3 deficiency. Because organoids develop without sensory input, they let us ask how circuits encode information before any representation is learned. Closed-loop control of a virtual inverted pendulum engaged existing spontaneous activity patterns rather than creating new ones. PULSE provides a common reference frame for neural circuits across genotypes, protocols and tasks.

neuroscience↗

Microfluidic Control of Dorsal-Ventral Patterning Within a Single Forebrain Organoid

How distinct regional identities emerge within a single developing brain remains poorly understood. Current in vitro models address this by fusing independently generated organoids, but this introduces variability in size, maturation state, and connectivity, confounding the study of regionalization itself. Here, we present a microfluidic platform that supports the co-development of different tissue identities within a single, continuous 3D culture domain. The device integrates controlled microfluidic flow with real-time fluorescence imaging, providing stable perfusion and high-resolution tracking of molecular transport without the need for embedded sensors or disruptive sampling. By delivering SAG, a Sonic hedgehog pathway agonist, to one surface of mouse forebrain organoids, we induced spatially segregated ventral (Nkx2.1+) and dorsal (Pax6+) domains within a unified tissue architecture. Controlled morphogen delivery is sufficient to drive region-specific fate specification without organoid fusion, offering a practical, scalable alternative for studying tissue regionalization in vitro.

bioengineering↗

The diploid reference genome of a human embryonic stem cell line

Advances in DNA sequencing and assembly technologies are spurring a shift from haploid reference genomes to sample-specific diploid assemblies. Here, we generated the first telomere-to-telomere (T2T) diploid reference for the widely used human embryonic stem cell (hESC) line, H9 (WAe009-A). This haplotype-resolved assembly is highly accurate with comprehensive annotation of genes, segmental duplications, methylation, and chromatin conformation. Pangenomic and phased-locus inference point to H9s mixed ancestry with a predominant European component. H9-specific genomic features include near-perfect telomeres [~]1.65-fold longer than other T2T assemblies, consistent with telomerase activity during pluripotency; chromosome 17 inversions that can predispose offspring to neurological syndromes; and expansions of ncRNA clusters, with overall genomic stability maintained despite extensive culturing. Mapping multi-omic datasets to the genome, we demonstrate the power of this resource for allele-specific, high-precision transcriptomic, genetic, and epigenetic analyses, with far-reaching implications for human development and disease.

genomics↗

A Modular In-Incubator Microscope for Longitudinal Live Cell Microscopy

Longitudinal live cell imaging is valuable for characterizing dynamic morphological and phenotypic changes in biological systems. However, conventional approaches rely on manual microscope operation, which is labor-intensive, limits imaging frequency, and disrupts the cellular environment. These constraints reduce scalability, increase experimental variability, and restrict both the duration and temporal resolution of continuous imaging. Although automated imaging platforms partially address these limitations, existing solutions are often constrained by the cost, footprint, and inflexibility of in-incubator microscopes or stage-top incubators. Here, we present an automated in-incubator epifluorescence microscope designed for long-term operation. The system features a modular architecture with optional multi-fluorescence imaging, automated plate scanning, configurable light sources, and compatibility with multiple plate formats, including integration with fluidic automation devices. By positioning the light sources and control electronics outside the incubator, the platform improves thermal stability and long-term operational reliability. This approach enables continuous, high-frequency imaging over extended durations, providing a source of rich data for quantifying time-dependent tissue phenotypes, morphological remodeling, and transient biological processes.

bioengineering↗

Self-Organizing Neural Networks in Organoids Reveal Principles of Forebrain Circuit Assembly

The mouse cortex is a canonical model for studying how functional neural networks emerge, yet it remains unclear which topological features arise from intrinsic cellular organization versus external regional cues. Mouse forebrain organoids provide a powerful system to investigate these intrinsic mechanisms. We generated dorsal (DF) and ventral (VF) forebrain organoids from mouse pluripotent stem cells and tracked their development using longitudinal electrophysiology. DF organoids showed progressively stronger network-wide correlations, while VF organoids developed more refined activity patterns, enhanced small-world topology, and increased modular organization. These differences emerged without extrinsic inputs and may be driven by the increased generation of Pvalb+ interneurons in VF organoids. Our findings demonstrate how variations in cellular composition influence the self-organization of neural circuits, establishing mouse forebrain organoids as a tractable platform to study how neuronal populations shape cortical network architecture.

neuroscience↗

Identification of Specialized tRNA Expression in Early Human Brain Development

Abstract/SummaryTransfer RNAs (tRNAs) are traditionally known for their role in protein translation, yet recent discoveries highlight their broader functions in gene regulation, particularly through tRNA-derived small RNAs (tDRs). Previous studies demonstrated the importance of one unique ArgUCU tRNA isodecoder in mouse neural development, yet potential function(s) of tDRs derived from this and all other tRNAs remain largely unexplored in human brain development. In this study, we employed cerebral cortex organoid models and AlkB-facilitated RNA methylation sequencing (ARM-seq) to profile tDRs across distinct stages of early human cerebral cortex development. Our analysis reveals dynamic expression patterns of diverse tDR groups derived from a wide range of isodecoders, with several distinct groups showing neural-specific expression. Computational analyses of these tDRs identified sequence motifs in over-represented tRNAs and enrichment for particular RNA modifications, giving initial clues to traits that define the pool of tDRs enriched during neural development. This expanded catalog of tDRs provides a framework for future studies on tRNA function in brain development and offers a deeper understanding of the complexity of tDR dynamics in neural differentiation.

developmental biology↗

Interspecies Organoids Reveal Human-Specific Molecular Features of Dopaminergic Neuron Development and Vulnerability

The disproportionate expansion of telencephalic structures during human evolution involved tradeoffs that imposed greater connectivity and metabolic demands on midbrain dopaminergic neurons. Despite the central role of dopaminergic neurons in human-enriched disorders, molecular specializations associated with human-specific features and vulnerabilities of the dopaminergic system remain unexplored. Here, we establish a phylogeny-in-a-dish approach to examine gene regulatory evolution by differentiating pools of human, chimpanzee, orangutan, and macaque pluripotent stem cells into ventral midbrain organoids capable of forming long-range projections, spontaneous activity, and dopamine release. We identify human-specific gene expression changes related to axonal transport of mitochondria and reactive oxygen species buffering and candidate cis- and trans-regulatory mechanisms underlying gene expression divergence. Our findings are consistent with a model of evolved neuroprotection in response to tradeoffs related to brain expansion and could contribute to the discovery of therapeutic targets and strategies for treating disorders involving the dopaminergic system.

evolutionary biology↗

Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization

Electrophysiology offers a high-resolution method for real-time measurement of neural activity. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage and of substantial complexity for extracting neural features and network dynamics. Analysis is often demanding due to the need for multiple software tools with different runtime dependencies. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the services and algorithms to serve as scalable and flexible building blocks within the pipeline. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings to show that this pipeline simplifies the data analysis process and facilitates understanding neuronal activity.

neuroscience↗

A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies

The analysis of tissue cultures, particularly brain organoids, requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated protocols were validated in maintaining robust neural activity throughout the experiment. The automated system enabled hourly electrophysiology recordings for the 7-day studies. Median neural unit firing rates increased for every sample and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect firing rate. Furthermore, performing media exchange during a recording showed no acute effects on firing rate, enabling the use of this automated platform for reagent screening studies.

neuroscience↗

Modulation of neuronal activity in cortical organoids with bioelectronic delivery of ions and neurotransmitters

Precise modulation of brain activity is fundamental for the proper establishment and maturation of the cerebral cortex. To this end, cortical organoids are promising tools to study circuit formation and the underpinnings of neurodevelopmental disease. However, the ability to manipulate neuronal activity with high temporal resolution in brain organoids remains limited. To overcome this challenge, we introduce a bioelectronic approach to control cortical organoid activity with the selective delivery of ions and neurotransmitters. Using this approach, we sequentially increased and decreased neuronal activity in brain organoids with the bioelectronic delivery of potassium ions (K+) and {gamma}-aminobutyric acid (GABA), respectively, while simultaneously monitoring network activity. This works highlights bioelectronic ion pumps as tools for high-resolution temporal control of brain organoid activity toward precise pharmacological studies that can improve our understanding of neuronal function.

bioengineering↗

Modular automated microfluidic cell culture platform reduces glycolytic stress in cerebral cortex organoids

Organ-on-a-chip systems combine microfluidics, cell biology, and tissue engineering to culture 3D organ-specific in vitro models that recapitulate the biology and physiology of their in vivo counterparts. Here, we have developed a multiplex platform that automates the culture of individual organoids in isolated microenvironments at user-defined media flow rates. Programmable workflows allow the use of multiple reagent reservoirs that may be applied to direct differentiation, study temporal variables, and grow cultures long term. Novel techniques in polydimethylsiloxane (PDMS) chip fabrication are described here that enable features on the upper and lower planes of a single PDMS substrate. RNA sequencing (RNA-seq) analysis of automated cerebral cortex organoid cultures shows benefits in reducing glycolytic and endoplasmic reticulum stress compared to conventional in vitro cell cultures.

bioengineering↗

Internet of Things Architecture for High Throughput Biology

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

bioengineering↗

Light-weight Electrophysiology Hardware and Software Platform for Cloud-Based Neural Recording Experiments

ObjectiveNeural 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. ApproachWe developed Piphys, an inexpensive open source neurophysiological recording platform that consists both hardware and software. It is easily accessed and controlled via a standard web interface through Internet of Things (IoT) protocols. Main ResultsWe used a Raspberry Pi as the primary processing device and 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 real-time neural activity. SignificanceThe 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.

bioengineering↗

Establishing Cerebral Organoids as Models of Human-Specific Brain Evolution

Direct comparisons of human and non-human primate brain tissue have the potential to reveal molecular pathways underlying remarkable specializations of the human brain. However, chimpanzee tissue is largely inaccessible during neocortical neurogenesis when differences in brain size first appear. To identify human-specific features of cortical development, we leveraged recent innovations that permit generating pluripotent stem cell-derived cerebral organoids from chimpanzee. First, we systematically evaluated the fidelity of organoid models to primary human and macaque cortex, finding organoid models preserve gene regulatory networks related to cell types and developmental processes but exhibit increased metabolic stress. Second, we identified 261 genes differentially expressed in human compared to chimpanzee organoids and macaque cortex. Many of these genes overlap with human-specific segmental duplications and a subset suggest increased PI3K/AKT/mTOR activation in human outer radial glia. Together, our findings establish a platform for systematic analysis of molecular changes contributing to human brain development and evolution.

developmental biology↗

Structurally conserved primate lncRNAs are transiently expressed during human cortical differentiation and influence cell type specific genes

The cerebral cortex has expanded in size and complexity in primates, yet the underlying molecular mechanisms are obscure. We generated cortical organoids from human, chimpanzee, orangutan, and rhesus pluripotent stem cells and sequenced their transcriptomes at weekly time points for comparative analysis. We used transcript structure and expression conservation to discover thousands of expressed long non-coding RNAs (lncRNAs). Of 2,975 human, multi-exonic lncRNAs, 2,143 were structurally conserved to chimpanzee, 1,731 to orangutan, and 1,290 to rhesus. 386 human lncRNAs were transiently expressed (TrEx) and a similar expression pattern was often observed in great apes (46%) and rhesus (31%). Many TrEx lncRNAs were associated with neuroepithelium, radial glia, or Cajal-Retzius cells by single cell RNA-sequencing. 3/8 tested by ectopic expression showed [≥]2-fold effects on neural genes. This rich resource of primate expression data in early cortical development provides a framework for identifying new, potentially functional lncRNAs.

neuroscience↗

Human-specific NOTCH-like genes in a region linked to neurodevelopmental disorders affect cortical neurogenesis

Genetic changes causing dramatic brain size expansion in human evolution have remained elusive. Notch signaling is essential for radial glia stem cell proliferation and a determinant of neuronal number in the mammalian cortex. We find three paralogs of human-specific NOTCH2NL are highly expressed in radial glia cells. Functional analysis reveals different alleles of NOTCH2NL have varying potencies to enhance Notch signaling by interacting directly with NOTCH receptors. Consistent with a role in Notch signaling, NOTCH2NL ectopic expression delays differentiation of neuronal progenitors, while deletion accelerates differentiation. NOTCH2NL genes provide the breakpoints in typical cases of 1q21.1 distal deletion/duplication syndrome, where duplications are associated with macrocephaly and autism, and deletions with microcephaly and schizophrenia. Thus, the emergence of hominin-specific NOTCH2NL genes may have contributed to the rapid evolution of the larger hominin neocortex accompanied by loss of genomic stability at the 1q21. 1 locus and a resulting recurrent neurodevelopmental disorder.

neuroscience↗

Distinct epigenetic shift in a subset of Glioma CpG island methylator phenotype (G-CIMP) during tumor recurrence

Histomorphology and current grading schemes are unable to predict glioma relapse and malignant tumor progression. We reported that the IDH-mutant associated Glioma-CpG Island Methylator Phenotype (G-CIMP) can be further divided into two clinically distinct subtypes independent of histopathological grading (G-CIMP-high and -low) with evidence of correlation with tumor progression. Here we performed a comprehensive epigenomic analysis of 74 longitudinally collected glioma samples (grade II-IV) to understand malignant recurrence from G-CIMP-high to G-CIMP-low. G-CIMP-low recurrence appeared in 12% of all gliomas and resemble IDH-wildtype primary glioblastoma. G-CIMP-low recurrence can be characterized by distinct epigenetic changes at candidate functional tissue enhancers with AP-1/SOX binding elements, stem cell-like epigenomic phenotype, and genomic instability. Finally, we defined a set of candidate biomarker signatures that predict recurrence of G-CIMP-low with clinically relevance on patient outcomes. Our study provides opportunity for refined clinical trial designs and therapeutic targets that limit progression to more aggressive G-CIMP-low phenotype.\n\nHIGHLIGHTSO_LIIndolent G-CIMP-high progresses to aggressive G-CIMP-low phenotype\nC_LIO_LIIncidence of G-CIMP-low recurrent tumors are 3 times greater than G-CIMP-low primary\nC_LIO_LIG-CIMP-low recurrent tumors share epigenomic features with IDH-wildtype primary GBM\nC_LIO_LIPredictive biomarkers of G-CIMP-low progression at primary diagnosis\nC_LI

cancer biology↗