Biology subjects

Ramirez, C. A.

Publications and source records attributed to Ramirez, C. A..

2 recordsLinked to original sources

bioRxiv2024

Synaptic plasticity in human thalamocortical assembloids

Synaptic plasticities, such as long-term potentiation (LTP) and depression (LTD), tune synaptic efficacy and are essential for learning and memory. Current studies of synaptic plasticity in humans are limited by a lack of adequate human models. Here, we modeled the thalamocortical system by fusing human induced pluripotent stem cell-derived thalamic and cortical organoids. Single-nucleus RNA-sequencing revealed that most cells in mature thalamic organoids were glutamatergic neurons. When fused to form thalamocortical assembloids, thalamic and cortical organoids formed reciprocal long-range axonal projections and reciprocal synapses detectable by light and electron microscopy, respectively. Using whole-cell patch-clamp electrophysiology and two-photon imaging, we characterized glutamatergic synaptic transmission. Thalamocortical and corticothalamic synapses displayed short-term plasticity analogous to that in animal models. LTP and LTD were reliably induced at both synapses; however, their mechanisms differed from those previously described in rodents. Thus, thalamocortical assembloids provide a model system for exploring synaptic plasticity in human circuits. HighlightsO_LIHuman thalamic organoids consist of mostly glutamatergic projection neurons. C_LIO_LIThalamocortical assembloids form reciprocal glutamatergic synapses. C_LIO_LISynapses are functional and undergo short-term plasticity resembling animal models. C_LIO_LILong-term potentiation and depression reveal mechanisms distinct from rodents. C_LI eTOCHuman organoids are often used to model diseases with synaptic pathology; however, few studies have examined synaptic function via single-cell or single-synapse recordings. Patton et al. fused human thalamic and cortical organoids into assembloids to examine synaptic transmission and short- and long-term synaptic plasticity in human thalamocortical and corticothalamic circuits. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/578421v2_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@21546org.highwire.dtl.DTLVardef@c2ba28org.highwire.dtl.DTLVardef@4bc28aorg.highwire.dtl.DTLVardef@1d12a98_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2020

Accurate neoantigen prediction depends on mutation position relative to patient allele-specific MHC anchor location

Neoantigens are novel peptide sequences resulting from sources such as somatic mutations in tumors. Upon loading onto major histocompatibility complex (MHC) molecules, they can trigger recognition by T cells. Accurate neoantigen identification is thus critical for both designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly predicting whether the presenting peptide sequence can successfully induce an immune response. As the majority of somatic mutations are single nucleotide variants, changes between wildtype and mutated peptides are typically subtle and require cautious interpretation. A potentially underappreciated variable in neoantigen-prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patients specific MHC molecules. While a subset of peptide positions are presented to the T-cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T-cell responses. We computationally predicted high probability anchor positions for different peptide lengths for 328 common HLA alleles and identified unique anchoring patterns among them. Analysis of 923 tumor samples shows that 6-38% of neoantigen candidates are potentially misclassified and can be rescued using allelespecific knowledge of anchor positions. A subset of anchor results were orthogonally validated using protein crystallography structures. Representative anchor trends were experimentally validated using peptide-MHC stability assays and competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, we hope to formalize, streamline and improve the identification process for relevant clinical studies. One Sentence SummaryNeoantigen prediction accuracy is significantly influenced by the mutation position within the neoantigen and its relative position to the patients allele-specific MHC anchor locations.

bioinformatics↗