Biology subjects

Parekh, U.

Publications and source records attributed to Parekh, U..

6 recordsLinked to original sources

bioRxiv2025

ADAPT-M: A workflow for rapid, quantitative in vitro measurements of enriched protein libraries

Protein-protein interactions underpin most cellular interactions, and engineered binders present powerful tools for probing biology and developing novel therapeutics. One bottleneck in binder generation is the scalable, quantitative characterization of these interactions. We present ADAPT-M (Affinity Determination by Adaptation of ProTein binders for Microfluidics), a streamlined workflow that connects yeast surface display (YSD) with in vitro affinity and kinetic measurements using the high-throughput STAMMPPING microfluidic platform. ADAPT-M quantifies Kds and dissociation kinetic parameters for hundreds of enriched protein variants in under one week without requiring hands-on protein purification. We applied ADAPT-M to a computationally designed library targeting the SARS-CoV-2 Omicron BA.1 receptor binding domain, successfully recovering and measuring Kds for most highly enriched YSD variants. Measurements correlate strongly with biolayer interferometry and yeast titration assays. ADAPT-M further enabled selection of lead candidates for structural and mutational analysis, which revealed designed paratopes were preserved despite binding to off-target epitopes. By bridging YSD screening and in vitro validation, ADAPT-M accelerates protein binder discovery and supports data-driven protein engineering.

biophysics↗

bioRxiv2025

Integrative spatial and multi-omic profiling in bladder cancer links L1 retrotransposition to extrachromosomal DNA, genomic instability, and viral mimicry response

Bladder cancer is one of the most frequent cancers and shows high recurrence rates. Despite recent advances, key knowledge gaps remain in understanding the molecular mechanisms of disease progression, which would support the development of early detection methods and effective personalized treatments. We apply integrated multi-omics and spatial analyses in a cohort of 49 bladder cancer patients to comprehensively profile genetic, epigenetic, transcriptomic, and spatial features of bladder cancer, alongside cell-free DNA blood analysis. Combining low-pass whole-genome cell-free DNA sequencing, Oxford Nanopore long-read tumor DNA sequencing, RNA-sequencing, and spatial transcriptomics, we provide insights into molecular alterations driving bladder cancer. We show frequent somatic LINE-1 (L1) insertions, with up to more than 500 insertions per tumor. We find that L1 insertions are active and occur early in bladder cancer development. We link aberrant somatic L1 insertion in bladder cancer with downstream genomic rearrangements and chromosomal instability, with an excess of structural variants and extrachromosomal DNA (ecDNA) in patients with particularly high L1 counts. By detecting ecDNA within tissue architecture using spatial transcriptomics, we identify the localization of ecDNA to distinct spatial clusters with differential expression of APOBEC3B and immune response pathways. These results, combined with replication timing analysis and gene set enrichment analysis (GSEA), offer evidence for the previously hypothesized viral mimicry response to L1 retrotransposition, mediated via APOBEC3B-editing, the cGAS-STING pathway, and RIG-I and MDA5 responses.

cancer biology↗

bioRxiv2024

A general platform for targeting MHC-II antigens via a single loop

Class-II major histocompatibility complexes (MHC-IIs) are central to the communications between CD4+ T cells and antigen presenting cells (APCs), but intrinsic structural features associated with MHC-II make it difficult to develop a general targeting system with high affinity and antigen specificity. Here, we introduce a protein platform, Targeted Recognition of Antigen-MHC Complex Reporter for MHC-II (TRACeR-II), to enable the rapid development of peptide-specific MHC-II binders. TRACeR-II has a small helical bundle scaffold and uses an unconventional mechanism to recognize antigens via a single loop. This unique antigen-recognition mechanism renders this platform highly versatile and amenable to direct structural modeling of the interactions with the antigen. We demonstrate that TRACeR-II binders can be rapidly evolved across multiple alleles, while computational protein design can produce specific binding sequences for a SARS-CoV-2 peptide of unknown complex structure. TRACeR-II sheds light on a simple and straightforward approach to address the MHC peptide targeting challenge, without relying on combinatorial selection on complementarity determining region (CDR) loops. It presents a promising basis for further exploration in immune response modulation as well as a broad range of theragnostic applications.

bioengineering↗

bioRxiv2023

HIPSD&R-seq enables scalable genomic copy number and transcriptome profiling

Single-cell DNA-sequencing (scDNA-seq) enables decoding somatic cancer variation. Existing methods are hampered by low throughput or cannot be combined with transcriptome sequencing in the same cell. We propose HIPSD&R-seq (HIgh-throughPut Single-cell Dna and Rna-seq), a scalable yet simple assay to profile low-coverage DNA and RNA in thousands of cells in parallel. Our approach builds on an accessible modification of the 10X Genomics platform for scATAC and multiome profiling. In applications to human cell models and primary tissue, we demonstrate the feasibility to detect rare clones and we combine the assay with combinatorial indexing to profile over 16,000 cells.

cancer biology↗

bioRxiv2022

Deep Generative Design of Epitope-Specific Binding Proteins by Latent Conformation Optimization

AO_SCPLOWBSTRACTC_SCPLOWDesigning de novo binding proteins against arbitrary epitopes using a single scaffold, as seen with natural antibodies, remains an unsolved challenge in protein design. Current design methods are unable to capture the structural dynamics of flexible loops nor search loop conformational space in a principled way. Here we present Sculptor, a deep generative design algorithm that creates epitope-specific protein binders. The Sculptor algorithm constitutes a joint search over the positions, interactions, and generated conformations of a fold, and crafts a backbone to complement a user-specified epitope. Sequences are designed onto generated backbones using a combination of a residue-wise interaction database, a convolutional sequence design module, and Rosetta. Instead of relying on static structures, we capture the local conformational landscape of a single fold using molecular dynamics, and demonstrate that a model trained on such dense conformational data can generate backbones tailor-fit to an epitope. We use Sculptor to design binders against a conserved epitope on venom toxins implicated in neuromuscular paralysis, and obtain a multi-toxin binder from a small naive library - a promising step towards creating broadly neutralizing binders. This study constitutes a novel application of deep generative modeling for epitope-targeted design, leveraging conformational dynamics to achieve function.

biochemistry↗

bioRxiv2021

Charting oncogenicity of genes and variants across lineages via multiplexed screens in teratomas

Deconstructing tissue-specific effects of genes and variants on proliferative advantage is critical to understanding cellular transformation and to systematic selection of cancer therapeutics. Dissecting these specificities at scale requires integrated methods for multiplexed genetic screens tracking fitness across time, across human cell types, and in a suitable cellular niche since functional differences also depend on physiological cues. Towards this, we present a novel approach, harnessing single-cell cancer driver screens in teratomas coupled with hit enrichment by serial teratoma reinjection, to simultaneously screen drivers across multiple lineages in vivo. Using this system, we analyzed population shifts and lineage-specific enrichment for 51 cancer associated genes and gene variants, profiling over 100,000 cells spanning over 20 lineages, across two rounds of serially injected teratomas. We confirmed that c-MYC alone or combined with myristoylated AKT1 potently drives proliferation in progenitor neural lineages, demonstrating signatures of malignancy. These drivers directed teratoma development to lineages representative of pediatric tumors such as medulloblastoma and rhabdomyosarcoma. Additionally, mutant MEK1S218D/S222D provides a proliferative advantage in mesenchymal lineages like fibroblasts. Our method provides a powerful new platform for multi-lineage longitudinal study of oncogenesis.

systems biology↗