Cellular immunotherapies encompass a broad and rapidly developing group of treatments comprising expanded and/or genetically engineered immune cells, which use the specific properties of human immune cells to counteract...Cellular immunotherapies encompass a broad and rapidly developing group of treatments comprising expanded and/or genetically engineered immune cells, which use the specific properties of human immune cells to counteract human immune-mediated disease. Initially approved for cancers of the B cell lineage, a growing arsenal of cellular immunotherapies are being applied to autoimmune diseases, including chimeric antigen receptor (CAR) T cells, chimeric autoantibody receptor T cells, regulatory T cells and CAR-engineered innate immune cells. These approaches represent a major shift in the way scientists and physicians pursue the treatment of human disease compared to standard immunosuppressive therapies. Here, we review the clinical progress of engineered cellular immunotherapies for autoimmunity. We focus on how antigenic target, engineered cell type, CAR design and treatment regimens affect the therapeutic efficacy and safety of these treatments and how these emerging clinical data can inform future directions in the field.
Tiesmeyer S, Müller-Bötticher N, Malt A
… +13 more, Ma L, Marco-Salas S, Kiessling P, Horn P, Guillot A, Kuemmerle LB, Tacke F, Theis FJ, Kuppe C, Nilsson M, Eils R, Long B, Ishaque N
Imaging-based spatially resolved transcriptomics can localize transcripts within tissue sections in three dimensions. However, cell segmentation, which assigns transcripts to cells, is usually performed in two dimensions...Imaging-based spatially resolved transcriptomics can localize transcripts within tissue sections in three dimensions. However, cell segmentation, which assigns transcripts to cells, is usually performed in two dimensions and spatial doublets in the vertical dimension result in segmented cells containing transcripts originating from multiple cell types. Here we present a computational tool called ovrlpy that identifies overlapping cells, tissue folds and inaccurate cell segmentation by analyzing transcript localization in three dimensions.
Nat Biotechnol
· 2026 May · PMID 41667710
·
Full text
Developmentally inspired kidney tissues derived from stem cells hold promise for future renal replacement tissue, but clinical translation is limited by variability in outcomes, absence of cell types, lack of functional...Developmentally inspired kidney tissues derived from stem cells hold promise for future renal replacement tissue, but clinical translation is limited by variability in outcomes, absence of cell types, lack of functional maturity and implausible scalability. Overcoming these may benefit from tissue engineering strategies that leverage processes for tissue construction that the embryonic kidney uses to achieve its diverse and parallelized functions. We present a 'developmental engineering' strategy in which spatial and temporal cues inspired by in vivo development guide multiscale structure formation in vitro. We highlight emerging tools in synthetic biology, spatial patterning and control over tissue microenvironments that can set initial and boundary conditions to instigate and guide the development of a desired 'motif'. We then present a vision for scalable developmental engineering by guiding and daisy-chaining tissue motifs, bridging discontinuities in self-organization via direct assembly. Although we articulate a blueprint for developmental engineering of translationally viable renal replacement tissues, the strategy is also applicable to other solid organs.
Chen G, Chung T, Liu Z
… +11 more, Li YR, Scott K, Zhao X, Carol J, Park S, Zhou Y, Kim WJ, Ge X, Colby GP, Li S, Chen J
Nat Biotechnol
· 2026 Mar · PMID 41667708
·
Full text
Conventional approaches for vascular graft stenosis diagnostics, including X-ray angiography, magnetic resonance imaging and Doppler ultrasound, although highly accurate, are cumbersome, used intermittently and often do...Conventional approaches for vascular graft stenosis diagnostics, including X-ray angiography, magnetic resonance imaging and Doppler ultrasound, although highly accurate, are cumbersome, used intermittently and often do not detect stenosis early enough, leading to diagnosis only after substantial narrowing. Here we report a magnetoelastic vascular graft (MVG) for post-implantation stenosis diagnosis that is hemodynamics-driven, biocompatible and waterproof. It enables wireless, real-time and continuous diagnosis of stenosis by converting arterial hemodynamics into high-fidelity electrical signals. The MVGs were scalably manufactured with customizable diameters and tested in vivo in the femoral arteries of rats and swine through microsurgical anastomosis. The anastomosed MVGs restored blood flow and identified the location and severity of induced stenosis through artificial intelligence-assisted analysis. Furthermore, a 4-month in vivo study in rats verified the stability and biocompatibility of the MVGs in the host, with no evident signs of an adverse immune response. The MVG is expected to advance existing vascular graft solutions and improve vascular disease management.
Manakongtreecheep K, Ctortecka C, Correa-Medero LO
… +22 more, Zhu T, Lippincott I, Lawrence GM, Howard A, Hernandez GM, Forman C, Duggan EC, Wilbrink MA, Verzani EK, Afeyan AB, Li J, Nesvizhskii AI, Oliveira G, Keskin DB, Ott PA, Clauser KR, Bakalar M, Sarkizova S, Hacohen N, Carr SA, Abelin JG, Wu CJ
Human leukocyte antigen (HLA)-bound tumor peptides can be routinely isolated from cancer samples and identified using mass spectrometry (MS). However, MS approaches can be stochastic or rely on spectral libraries, which...Human leukocyte antigen (HLA)-bound tumor peptides can be routinely isolated from cancer samples and identified using mass spectrometry (MS). However, MS approaches can be stochastic or rely on spectral libraries, which are not customarily available for individual-specific peptides, thus limiting the ability to discover novel peptides. Here, we introduce Pepyrus, which generates user-defined, individual-specific or disease-specific peptide libraries in Escherichia coli to improve the sensitivity and confidence of MS peptide identification, including lowly abundant neoantigens. Using Pepyrus-generated peptide libraries paired with an HLA-specific data-independent acquisition strategy, we recover >75% of the expected sequences per single injection for libraries of >10,000 peptides and identify 0.1 fmol of spiked-in peptides in a complex background. We apply Pepyrus to create personalized libraries, facilitating identification of clinically relevant HLA peptides, including several novel peptides from cell lines derived from persons with melanoma and renal cell carcinoma. Pepyrus enables identification of rare HLA-bound peptides and provides the ability to generate large training datasets to improve spectra, retention time and ion mobility prediction tools.
The directed evolution of biomolecules is an iterative process. Although advancements in language models have expedited protein evolution, effectively evolving RNA remains a challenge. RNA aptamers, selected for their bi...The directed evolution of biomolecules is an iterative process. Although advancements in language models have expedited protein evolution, effectively evolving RNA remains a challenge. RNA aptamers, selected for their binding properties, provide an ideal system to address this challenge, yet traditional aptamer discovery still relies on labor-intensive, multi-round screening. Here we introduce GRAPE-LM (generator of RNA aptamers powered by activity-guided evolution and language model), a generative artificial intelligence framework designed for the one-round evolution of RNA aptamers. GRAPE-LM integrates a transformer-based conditional autoencoder with nucleic acid language models and is guided by CRISPR-Cas-based aptamer screening data derived from intracellular environments. We validate GRAPE-LM on three disparate targets: the human T cell receptor CD3ε, the receptor-binding domain of the SARS-CoV-2 spike protein and the human oncogenic transcription factor c-Myc (an intracellular disordered protein). GRAPE-LM, informed with only a single round of CRISPR-Cas-based screening, successfully obtains RNA aptamers that outperform those driven from multiple rounds of human selection and optimization.
As some drugs have narrow therapeutic windows and high inter-patient exposure variability, they require concentration measurements to ensure their safe and effective dosing. To improve on the current practice of sparse b...As some drugs have narrow therapeutic windows and high inter-patient exposure variability, they require concentration measurements to ensure their safe and effective dosing. To improve on the current practice of sparse blood sampling, we are developing wearable 'patches' bearing electrochemical aptamer-based sensors on small, solid needles. Here we describe a pilot phase trial testing their safety and performance in six healthy human participants. The patches were found to be safe and nearly pain free, and they captured concentrations of vancomycin in the dermal interstitial fluid with 5-minute resolution over 24 hours, although, due to sensor degradation, we primarily describe data from the first 12 hours after insertion. Fitting interstitial fluid and plasma concentrations to compartmental pharmacokinetic models revealed distribution and clearance dynamics that are not detected with current sparse sampling approaches. Patches placed at different bodily sites exhibited consistent trends both within and across participants. With further testing and optimization, including real-time wireless data transmission, such patches could aid precision dosing of vancomycin and other drugs with narrow therapeutic windows. Australian New Zealand Clinical Trials Registry registration: ACTRN12622000280707 .
Plasmids are extrachromosomal DNA molecules that enable horizontal gene transfer in bacteria, often conferring advantages such as antibiotic resistance. Despite their importance, plasmids are underrepresented in genomic...Plasmids are extrachromosomal DNA molecules that enable horizontal gene transfer in bacteria, often conferring advantages such as antibiotic resistance. Despite their importance, plasmids are underrepresented in genomic databases because of challenges in assembling them, caused by mosaicism and microdiversity. Current plasmid assemblers rely on detecting circular paths in single-sample assembly graphs but face limitations because of graph fragmentation, entanglement and low coverage. We introduce PlasMAAG (plasmid and organism metagenomic binning using assembly-alignment graphs), a method to recover plasmids and cellular genomes from metagenomic samples. PlasMAAG complements assembly graph signals across samples by generating an 'assembly-alignment graph', which is used alongside common binning features for improved plasmid reconstruction. On synthetic benchmark datasets, PlasMAAG reconstructed 50-121% more near-complete plasmids than competing methods and improved the Matthews correlation coefficient of geNomad contig classification by 28-106%. On hospital sewage samples, PlasMAAG outperformed competing methods, reconstructing 33% more plasmid sequences. PlasMAAG enables the study of organism-plasmid associations and intraplasmid diversity across samples.
Nayfach S, Bhatnagar A, Novichkov A
… +12 more, Kim N, Hoffnagle AM, Hussain R, Estevam GO, Hill E, Ruffolo JA, Silverstein RA, Gallagher J, Kleinstiver BP, Meeske AJ, Cameron P, Madani A
CRISPR-Cas enzymes must recognize a protospacer-adjacent motif (PAM) to edit a genomic site, greatly limiting the range of targetable sequences in a genome. Although engineering strategies to alter PAM specificity exist,...CRISPR-Cas enzymes must recognize a protospacer-adjacent motif (PAM) to edit a genomic site, greatly limiting the range of targetable sequences in a genome. Although engineering strategies to alter PAM specificity exist, they typically require labor-intensive, iterative experimentation. We introduce an evolution-informed deep learning model, Protein2PAM, to efficiently guide the design of Cas protein variants tailored to recognize specific PAMs. Trained on a dataset of over 45,000 CRISPR-Cas PAMs, Protein2PAM rapidly and accurately predicts PAM specificity directly from Cas proteins across type I, II and V CRISPR-Cas systems. Using in silico mutagenesis, the model identifies residues critical for PAM recognition in Cas9 without using structural information. We use Protein2PAM to computationally evolve Nme1Cas9, generating variants with broadened PAM recognition and up to a 50-fold increase in PAM cleavage rates compared to the wild type in vitro. Our machine learning approach allows Cas enzymes to target sequences that were previously inaccessible because of PAM constraints, potentially increasing target flexibility in personalized genome editing.
Profiling protein abundance and dynamics at single-cell resolution in complex human tissues is challenging. Given the discordance between transcript and protein abundance observed in studies of the human cerebral cortex,...Profiling protein abundance and dynamics at single-cell resolution in complex human tissues is challenging. Given the discordance between transcript and protein abundance observed in studies of the human cerebral cortex, we developed an optimized workflow that combines label-free single-cell mass spectrometry with precise sample preparation to resolve quantitative proteomes of individual cells from the developing human brain. Our method achieves deep proteomic coverage (~800 proteins per cell) even in small immature prenatal human neurons (diameter ~7-10 μm, ~50 pg protein), capturing major brain cell types and enabling proteome-wide characterization at single-cell resolution. We document extensive transcriptome-proteome discordance across cell types, particularly in genes associated with neurodevelopmental disorders. Proteins exhibit markedly higher cell-type specificity than their mRNA counterparts, underscoring the importance of proteomic-level analysis. By reconstructing developmental trajectories from radial glia to excitatory neurons at the proteomic level, we identify dynamic, stage-specific protein co-expression modules and pinpoint the intermediate progenitor-to-neuron transition as a genetically vulnerable phase associated with autism.