Biology subjects

Robbins, A.

Publications and source records attributed to Robbins, A..

17 recordsLinked to original sources

bioRxiv2026

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↗

bioRxiv2026

Beyond the Final Layer: Evaluating Single-Cell Foundation Model Representations for Molecular Prediction

Single-cell foundation models (scFMs) are commonly benchmarked using final-layer embeddings, although useful depth may depend on the task. We evaluate Geneformer, scBERT, scGPT, and scFoundation as frozen feature extractors for cell-type and perturbation-response prediction using layer-wise probes, leave-one-dataset-out (LODO) selection, readout controls, representation diagnostics, centered kernel alignment (CKA), and retrieval/collapse analyses. Intermediate layers significantly improve cell-type accuracy for scGPT and scBERT in several settings, while Geneformer and scFoundation generally show performance comparable to their final layers. For perturbation prediction, LODO identifies layer 1 as an earliest-on-par candidate across all four models, without establishing universal superiority. Paired scGPT CLS and mean-pooling analyses show that readout affects preferred depth. CKA and representation metrics reveal model- and task-dependent geometric changes, while retrieval and collapse checks support the robustness of perturbation findings. We recommend reporting extraction depth, readout, selection protocol, and task-specific diagnostics. A validated non-final layer may also reduce computation, although efficiency was not directly benchmarked.

bioinformatics↗

bioRxiv2026

LIGER2: Scalable Single-Cell Integration with On-Disk Datasets

Correcting batch effects and integrating single-cell sequencing datasets has been a crucial step in large-scale biological studies. Many methods have been published for this task, and excel in various scenarios. Our previous work, LIGER, leveraging integrative non-negative matrix factorization (iNMF), stands out in providing an interpretable low-dimensional representation. To adapt to the modern need for integrating millions of cells, we developed a highly-optimized parallel factorization solution with on-demand loading from disk. The upgraded LIGER algorithm shows significant improvements in time and memory efficiency for single-cell data integration. We also developed a new downstream embedding alignment method significantly improved performance in conserving biological variation while still aligning corresponding cell types across datasets.

bioinformatics↗

bioRxiv2026

SpikeLab: Agentic tools for spike data analysis

Large language models have the potential to transform scientific research and analysis, but without domain-specific structure they produce silent methodological errors, unreported decisions, and irreproducible results. Here we present SpikeLab, a text-to-analysis framework for neural spike data that combines composable data structures with a skill-based agentic system enforcing bounded autonomy: mandatory use of expert-vetted methods, correctness over efficiency, and clarification-seeking on ambiguous requests. In a controlled benchmark on electrophysiology data, Sonnet 4.6 with SpikeLab produced correct and reproducible results across all tasks, outperforming both the unassisted Sonnet and the more capable Opus 4.6, which exhibited deterministic failures including ad hoc method invention, silent data reduction, and inconsistent experimental designs. We demonstrate versatility across in vivo mouse, human, and in vitro brain organoid recordings, and apply the framework to a pharmacological dose-response study spanning single-unit dynamics, pairwise network structure, burst-level temporal sequences, and latent population states, all through natural language prompts without writing analysis code.

neuroscience↗

bioRxiv2025

Reprogramming the Immune Suppressive Tumor Microenvironment in Glioma Enhances the Efficacy of Immune-Mediated Gene Therapy

Gliomas account for ~80% of primary malignant brain tumors. Many CNS WHO grade 2-3 and some grade 4 gliomas harbor mutant isocitrate dehydrogenase 1 (mIDH1), which causes a gain of function mutation (IDH1 R132H) leading to the production of 2-hydroxyglutarate (2HG). Mutant IDH1-induced 2HG, through epigenetic reprogramming elicits an immune-permissive tumor microenvironment (TME). An immunosuppressive mechanism in the glioma TME involves adenosine production via the ectoenzyme CD73. This study investigates mIDH1s influence on CD73 expression and adenosine levels. We demonstrate that mIDH1 glioma cells exhibit reduced CD73 expression, driven by DNA hypermethylation, leading to reduced adenosine levels. Since wtIDH1 gliomas have high CD73 expression, we evaluated CD73 blockade as an immunotherapy target. We show that CD73 inhibition used as monotherapy, did not improve survival in wtIDH1 glioma-bearing mice. However, when combined with immune-stimulatory Ad-TK (adenoviral vectors encoding herpes simplex virus thymidine kinase) and Ad-Flt3L (adenoviral vectors encoding FMS-like tyrosine kinase 3 ligand) gene therapy, CD73 blockade significantly enhanced therapeutic efficacy and increased anti-glioma effector T cell activity. These findings reveal that CD73 inhibition used in combination with immune stimulatory Ad-TK/Ad-Flt3L gene therapy may be an effective treatment for wtIDH1 gliomas, which could be readily translated to the clinical arena.

cancer biology↗

bioRxiv2025

DYRK1A ortholog mbk-1 knockout in Caenorhabditis elegans as a tool for genetics research of developmental disorders

Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a dosage sensitive gene located on human chromosome 21 (Hsa21) that contributes to phenotypes associated with developmental disorders like Down syndrome and DYRK1A haploinsufficiency syndrome. Complete genetic knockout of Dyrk1a from conception is embryonic lethal, presenting a barrier in its study. The mbk-1 gene in Caenorhabditis elegans has been identified as an ortholog to mammalian Dyrk1a, and genetic knockout of mbk-1 in C. elegans is not lethal. We hypothesized that deletion of the mbk-1 gene would alter chemosensory function, learning, and motility in C. elegans, and that these phenotypes would be recovered using a humanized DYRK1A replacement at the endogenous mbk-1 locus. Using behavioral preference index assays, analyses of locomotion, and learning in classical conditioning procedures, an mbk-1 knockout strain of C. elegans, EK228, was characterized to identify potential behavioral roles of mbk-1. Preference index assays assessing chemosensory capabilities determined that mbk-1 deletion yielded no detrimental effects. Thrashing and foraging behavior analyses uncovered significant deficits in movement in the EK228 C. elegans, which were not present in two mbk-1 replacement strains containing humanized DYRK1A, suggesting an essential role of mbk-1 in locomotion and motility. Lastly, classical conditioning revealed no significant deficits in the abilities of the EK228 strain in forming associative connections between stimuli. Overall, these results imply functional conservation of the mbk-1/DYRK family kinases, and provide support for the use of humanized replacement strains of C. elegans for the study of mammalian genes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/686526v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@13616f4org.highwire.dtl.DTLVardef@1d2d64org.highwire.dtl.DTLVardef@18f36a9org.highwire.dtl.DTLVardef@14da275_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract (Created with BioRender) C_FIG Article summaryThis work provides insight into evolutionarily conserved functions of the protein kinase DYRK1A, which is linked to developmental disorders including Down syndrome and DYRK1A syndrome. Caenorhabditis elegans with a genetic ablation of the DYRK1A ortholog, mbk-1, were used to examine potential roles in movement, chemosensing, and associative learning and memory, and demonstrated selective deficits in thrashing and foraging locomotion that were not observed in strains with mbk-1 replacement with humanized DYRK1A at the endogenous loci. The findings indicate a role of mbk-1 in C. elegans in adaptive movement, which may provide insight into some of the cellular and neural mechanisms being influenced by DYRK1A. Understanding of the protein kinase DYRK1A may help to elucidate novel therapeutic pathways for developmental disorders.

genetics↗

bioRxiv2025

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↗

bioRxiv2024

Pathological microcircuits initiate epileptiform events in patient hippocampal slices

How seizures begin at the level of microscopic neuronal circuits remains unknown. Advancements in high-density CMOS-based microelectrode arrays can be harnessed to study neuronal network activity with unprecedented spatial and temporal resolution. We use high-density electrophysiology recordings to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices exhibit network oscillations indicative of a reciprocally connected circuit, which is unexpected under normal physiological conditions. Future studies may apply this approach to elucidate the network signals that underlie seizure initiation.

neuroscience↗

bioRxiv2024

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↗

bioRxiv2024

RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies

With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms{+/-}1.5ms (mean{+/-}STD) after the waveform trough while the recording remains ongoing. RT-Sorts true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sorts performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sorts functionality on different types of recording hardware and electrode configurations.

neuroscience↗

bioRxiv2024

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↗

bioRxiv2023

Internet-connected cortical organoids for project-based stem cell and neuroscience education

The introduction of internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell-derived cortical organoids in two different settings: Using microscopy to monitor organoid growth in an introductory tissue culture course, and using high density multielectrode arrays to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training. HIGHLIGHTS- Development of cortical organoids as pedagogical tools for undergraduate education. - Organoids implemented in a tissue culture course through cloud-enabled microscopy. - Multielectrode arrays allow for live organoid manipulation in a mathematics course. - Students self-report increased interest in neuroscience and stem cells topics.

scientific communication and education↗

bioRxiv2023

Cooperative control of a DNA origami force sensor

Most biomolecular systems are dependent on a complex interplay of forces. Modern force spectroscopy techniques provide means of interrogating these forces. These techniques, however, are not optimized for studies in constrained or crowded environments as they typically require micron-scale beads in the case of magnetic or optical tweezers, or direct attachment to a cantilever in the case of atomic force microscopy. We implement a nanoscale force-sensing device using a DNA origami which is highly customizable in geometry, functionalization, and mechanical properties. The device, referred to as the NanoDyn, functions as a binary (open or closed) force sensor that undergoes a structural transition under an external force. The transition force is tuned with minor alterations of 1 to 3 DNA oligonucleotides and spans tens of picoNewtons (pN). This actuation of the NanoDyn is reversible and the design parameters strongly influence the efficiency of resetting the initial state, with higher stability devices ({gtrsim}10 pN) resetting more reliably during repeated force-loading cycles. Finally, we show that the opening force can be adjusted in real time by the addition of a single DNA oligonucleotide. These results establish the NanoDyn as a versatile force sensor and provide fundamental insights into how design parameters modulate mechanical and dynamic properties.

bioengineering↗

bioRxiv2022

DNA-caged Nanoparticles via Electrostatic Self-Assembly

DNA-modified nanoparticles enable DNA sensing and therapeutics in nanomedicine and are also crucial for nanoparticle self-assembly with DNA-based materials. However, methods to conjugate DNA to nanoparticle surfaces are limited, inefficient, and lack control. Inspired by DNA tile nanotechnology, we demonstrate a new approach to nanoparticle modification based on electrostatic attraction between negatively charged DNA tiles and positively charged nanoparticles. This approach does not disrupt nanoparticle surfaces and leverages the programmability of DNA nanotechnology to control DNA presentation. We demonstrated this approach using a variety of nanoparticles, including polymeric micelles, polystyrene beads, gold nanoparticles, and superparamagnetic iron oxide nanoparticles with sizes ranging from 5-20 nm in diameter. DNA cage formation was confirmed through transmission electron microscopy (TEM), neutralization of zeta potential, and a series of fluorescence experiments. DNA cages present "handle" sequences that can be used for reversible target attachment or self-assembly. Handle functionality was verified in solution, at the solid-liquid interface, and inside fixed cells, corresponding to applications in biosensing, DNA microarrays, and erasable immunocytochemistry. These experiments demonstrate the versatility of the electrostatic DNA caging approach and provide a new pathway to nanoparticle modification with DNA that will empower further applications of these materials in medicine and materials science.

bioengineering↗

bioRxiv2021

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↗

bioRxiv2021

Single-cell analyses of immune thrombocytopenic patients reveal multiorgan dissemination of high-affinity autoreactive plasma cells

The major therapeutic goal for immune thrombocytopenia (ITP) is to restore normal platelet counts using drugs to promote platelet production or by interfering with mechanisms responsible for platelet destruction. 80% of patients possess anti-integrin IIb{beta}3 (GPIIbIIIa) IgG autoantibodies causing platelet opsonization and phagocytosis. The spleen is considered the primary site of autoantibody production by autoreactive B cells and platelet destruction. The immediate failure in ~50% of patients to recover a normal platelet count after anti-CD20 Rituximab-mediated B cell depletion and splenectomy suggest that autoreactive, rituximab-resistant, IgG-secreting B cells (IgG-SC) reside in other anatomical compartments. We analyzed >3,300 single IgG-SC from spleen, bone marrow and/or blood of 27 patients with ITP revealing high inter-individual variability in affinity for GPIIbIIIa with variations over 3 logs. IgG-SC dissemination and range of affinities were however similar per patient. Longitudinal analysis of autoreactive IgG-SC upon treatment with anti-CD38 mAb daratumumab demonstrated variable outcomes, from complete remission to failure with persistence of high-affinity anti-GPIIbIIIa IgG-SC in the bone marrow. This study demonstrates the existence and dissemination of high-affinity autoreactive plasma cells in multiple anatomical compartments of patients with ITP that may cause the failure of current therapies.

immunology↗

bioRxiv2017

The Multiple Sclerosis Genomic Map: Role of peripheral immune cells and resident microglia in susceptibility

AbstractWe assembled and analyzed genetic data of 47,351 multiple sclerosis (MS) subjects and 68,284 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 independent associations within the extended MHC. We used an ensemble of methods to prioritize up to 551 potentially associated MS susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we do find enrichment for MS genes in these brain - resident immune cells. Thus, while MS is most likely initially triggered by perturbation of peripheral immune responses the functional responses of microglia and other brain cells are also altered and may have a role in targeting an autoimmune process to the central nervous system.\n\nOne Sentence SummaryWe report a detailed genetic and genomic map of multiple sclerosis, and describe the role of putatively affected genes in the peripheral immune system and brain resident microglia.

genetics↗