Search bioRxiv⌕ Search

Biology subjects

Zimak, J.

Publications and source records attributed to Zimak, J..

2 recordsLinked to original sources

A high throughput bispecific antibody discovery pipeline

Bispecific antibodies (BsAbs) represent an emerging class of immunotherapy but inefficiency in the current BsAb discovery paradigm has limited their broad clinical availability. Here we report a high throughput, agnostic, single-cell-based BsAb functional screening pipeline, comprising molecular and cell engineering for efficient generation of BsAb library cells, followed by functional interrogation at the single-cell level to identify and sort positive clones and downstream sequence identification with single-cell PCR and sequencing and functionality characterization. Using a CD19xCD3 bispecific T cell engager (BiTE) as a model system, we demonstrate that our single cell platform possesses a high throughput screening efficiency of up to one and half million variant library cells per run and can isolate rare functional clones at low abundance of 0.008%. Using a complex CD19xCD3 BiTE-expressing cell library with approximately 22,300 unique variants comprising combinatorially varied scFvs, connecting linkers and VL/VH orientations, we have identified 98 unique clones including extremely rare ones ([~] 0.001% abundance). We also discovered BiTEs that exhibit novel properties contradictory to conventional wisdom, including harboring rigid scFv connecting peptide linkers yet with in vitro cytotoxicity comparable to that of clinically approved Blinatumomab. Through sequencing analyses on sorted BiTE clones, we discovered multiple design variable preferences for functionality including the CD19VL-VH- CD3VH-VL and CD19VH-VL-CD3VH-VL arrangements being the most favored orientation. Sequence analysis further interrogated the sequence composition of the CDRH3 domain in scFvs and identified amino acid residues conserved for function. We expect our single cell platform to not only significantly increase the development speed of high quality of new BsAb therapeutics for cancer and other disorders, but also enable identifying generalizable design principles for new BsAbs and other immunotherapeutics based on an in-depth understanding of the inter-relationships between sequence, structure, and function.

bioengineering↗

Spatial transcriptomics using combinatorial fluorescence spectral and lifetime encoding, imaging and analysis

Multiplexed mRNA profiling in the spatial context provides important new information enabling basic research and clinical applications. Unfortunately, most existing spatial transcriptomics methods are limited due to either low multiplexing or assay complexity. Here, we introduce a new spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based target decoding. This technology is the first application combining the biophotonic techniques, Spectral and Fluorescence Lifetime Imaging and Microscopy (FLIM), to the field of spatial transcriptomics. By integrating the time dimension with conventional spectrum-based measurements, MOSAICA enables direct and highly-multiplexed in situ spatial biomarker profiling in a single round of staining and imaging while providing error correction removal of background autofluorescence. We demonstrate mRNA encoding using combinatorial spectral and lifetime labeling and target decoding and quantification using a phasor-based image segmentation and machine learning clustering technique. We then showcase MOSAICAs multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of only five fluorophores with facile error-correction and removal of autofluorescent moieties. MOSAICAs analysis is strongly correlated with sequencing data (Pearsons r = 0.9) and was further benchmarked using RNAscopeand LGC Stellaris. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues that have a high degree of tissue scattering and intrinsic autofluorescence, demonstrating the robustness of the approach. We then demonstrate simultaneous co-detection of protein and mRNA in colorectal cancer cells. MOSAICA represents a simple, versatile, and scalable tool for targeted spatial transcriptomics analysis that can find broad utility in constructing human cell atlases, elucidating biological and disease processes in the spatial context, and serving as companion diagnostics for stratified patient care.

bioengineering↗