Biology subjects

Makar, A. N.

Publications and source records attributed to Makar, A. N..

3 recordsLinked to original sources

bioRxiv2026

A Context-Aware Single-Cell Proteomics Analysis pipeline.

Single-cell proteomics (SCP) by mass spectrometry can now quantify hundreds to thousands of proteins per cell, but the field still lacks standardised analytical pipelines that accommodate the diversity of instruments, sample preparation workflows and biological contexts encountered in practice. Existing workflows, largely adapted from single-cell transcriptomics, do not account for the informative missingness, pervasive ambient protein contamination and limited feature space that distinguish proteomic from transcriptomic data. In addition, cell type annotation remains a manual bottleneck that is subjective, difficult to reproduce and hard to scale. Here we present an end-to-end pipeline that integrates adaptive quality control, entropy-guided iterative batch correction, multi-modal marker discovery that exploits detection patterns unique to proteomics, and context-aware annotation by large language models (LLMs) coupled to structured contradiction reasoning and orthogonal data-driven validation. Benchmarking on published single-cell proteomic datasets from developing human brain and glioblastoma-associated neutrophils revealed systematic LLM failure modes, including context-insensitive marker vocabulary and misinterpretation of phagocytic or lytic cell states. We addressed these errors using a three-round prompt architecture that combines general biological principles with auto-generated dataset-specific constraints. In held-out validation on a skin tumour dataset acquired, the pipeline showed high concordance with FACS-sorted ground truth. In the caerulein-injured pancreas, orthogonal immunohistochemistry further supported annotations of macrophage, stellate and immune populations. The pipeline is fully automated under fixed settings, and available as Context-Aware Single-Cell Proteomics Analysis (CASPA), providing SCP laboratories and facilities with a reproducible workflow that delivers interpretable, confidence-quantified annotations suitable for downstream expert review.

bioinformatics↗

bioRxiv2026

Molidustat Targets a Synthetic Lethal Vulnerability in APC-Mutant Colorectal Cancer through GSTP1 and PHD2 Co-Inhibition

Mutations in the adenomatous polyposis coli (APC) gene are a defining feature of colorectal cancer (CRC) and impose metabolic and stress-adaptation requirements that may create exploitable vulnerabilities. Prolyl hydroxylase domain (PHD) inhibitors have been explored as therapeutic agents in CRC, however, their mechanisms of action and off-target effects remain elusive. Serendipitously, we found that Molidustat, a PHD2 inhibitor, induced cell death in APC mutant CRC cells. Ablation of PHD2 alone did not affect cell viability, suggesting an off-target mechanism. Using thermal proteome profiling and chemical proteomics, we identify glutathione S-transferase P1 (GSTP1) as a previously unrecognised off-target of Molidustat and demonstrate direct inhibition of its enzymatic activity. Genetic ablation of PHD2 alone did not phenocopy the cytotoxic effects of Molidustat, whereas combined loss of PHD2 and GSTP1 induced synergistic proteomic changes associated with cell-cycle suppression and apoptotic signalling. Integrated proteomic and metabolomic analyses further revealed energetic and metabolic perturbations specific to simultaneous GSTP1 and PHD2 loss. Consistent with these findings, APC-mutant colonic organoids displayed selective sensitivity to Molidustat that was not reproduced by hydroxylase inhibition alone, supporting a synthetic lethal interaction between GSTP1 and PHD2 in APC-mutant contexts. Together, these results identify a functional interaction between GSTP1 and PHD2 in a subset of colorectal cancer and suggest that off-target engagement of GSTP1 contributes to the anti-tumour activity of Molidustat.

cancer biology↗

bioRxiv2025

Overcoming preservation challenges to enable single-cell proteomics of fixed cell and tissue samples with retained proteome integrity

The ability to assay the molecular composition of biological systems with single-cell resolution has revolutionised our understanding of tissue heterogeneity and function. Recent advances in single-cell proteomics (SCP) now enable the unbiased quantification of the proteome to a depth of several thousand proteins across hundreds of cells. Yet the broader adoption beyond specialised groups remains limited due to the need for specific equipment and expertise. A major challenge in making these analyses more broadly available is sample preservation for transporting biological material to SCP-capable facilities. To address this issue and provide practical solutions; we first evaluated various cell preservation methods from monolayer culture samples, then tested our optimised methodology on both cultured cells and, for the first time, preserved animal tissue from an in vivo mouse model. Our findings highlight the feasibility of SCP analyses in preserved tissues, significantly expanding its current applicability. By optimising upstream processing, our approach enables robust single-cell proteome analysis of both cells and tissues, making SCP more accessible to the wider scientific community. Ultimately, this advancement expands the potential applications of SCP, particularly in disciplines where analysing rare or heterogeneous populations is beneficial.

biochemistry↗